The Relationship Between Online Visual Representation of a Scene and Long-Term Scene Memory

ERIC Educational Resources Information Center

Hollingworth, Andrew

2005-01-01

In 3 experiments the author investigated the relationship between the online visual representation of natural scenes and long-term visual memory. In a change detection task, a target object either changed or remained the same from an initial image of a natural scene to a test image. Two types of changes were possible: rotation in depth, or…

The Nature of Change Detection and Online Representations of Scenes

ERIC Educational Resources Information Center

Ryan,J ennifer D.; Cohen, Neal J.

2004-01-01

This article provides evidence for implicit change detection and for the contribution of multiple memory sources to online representations. Multiple eye-movement measures distinguished original from changed scenes, even when college students had no conscious awareness for the change. Patients with amnesia showed a systematic deficit on 1 class of…

Drivers' and non-drivers' performance in a change detection task with static driving scenes: is there a benefit of experience?

PubMed

Zhao, Nan; Chen, Wenfeng; Xuan, Yuming; Mehler, Bruce; Reimer, Bryan; Fu, Xiaolan

2014-01-01

The 'looked-but-failed-to-see' phenomenon is crucial to driving safety. Previous research utilising change detection tasks related to driving has reported inconsistent effects of driver experience on the ability to detect changes in static driving scenes. Reviewing these conflicting results, we suggest that drivers' increased ability to detect changes will only appear when the task requires a pattern of visual attention distribution typical of actual driving. By adding a distant fixation point on the road image, we developed a modified change blindness paradigm and measured detection performance of drivers and non-drivers. Drivers performed better than non-drivers only in scenes with a fixation point. Furthermore, experience effect interacted with the location of the change and the relevance of the change to driving. These results suggest that learning associated with driving experience reflects increased skill in the efficient distribution of visual attention across both the central focus area and peripheral objects. This article provides an explanation for the previously conflicting reports of driving experience effects in change detection tasks. We observed a measurable benefit of experience in static driving scenes, using a modified change blindness paradigm. These results have translational opportunities for picture-based training and testing tools to improve driver skill.

Maintaining perceptual constancy while remaining vigilant: left hemisphere change blindness and right hemisphere vigilance.

PubMed

Vos, Leia; Whitman, Douglas

2014-01-01

A considerable literature suggests that the right hemisphere is dominant in vigilance for novel and survival-related stimuli, such as predators, across a wide range of species. In contrast to vigilance for change, change blindness is a failure to detect obvious changes in a visual scene when they are obscured by a disruption in scene presentation. We studied lateralised change detection using a series of scenes with salient changes in either the left or right visual fields. In Study 1 left visual field changes were detected more rapidly than right visual field changes, confirming a right hemisphere advantage for change detection. Increasing stimulus difficulty resulted in greater right visual field detections and left hemisphere detection was more likely when change occurred in the right visual field on a prior trial. In Study 2 an intervening distractor task disrupted the influence of prior trials. Again, faster detection speeds were observed for the left visual field changes with a shift to a right visual field advantage with increasing time-to-detection. This suggests that a right hemisphere role for vigilance, or catching attention, and a left hemisphere role for target evaluation, or maintaining attention, is present at the earliest stage of change detection.

Good initialization model with constrained body structure for scene text recognition

NASA Astrophysics Data System (ADS)

Zhu, Anna; Wang, Guoyou; Dong, Yangbo

2016-09-01

Scene text recognition has gained significant attention in the computer vision community. Character detection and recognition are the promise of text recognition and affect the overall performance to a large extent. We proposed a good initialization model for scene character recognition from cropped text regions. We use constrained character's body structures with deformable part-based models to detect and recognize characters in various backgrounds. The character's body structures are achieved by an unsupervised discriminative clustering approach followed by a statistical model and a self-build minimum spanning tree model. Our method utilizes part appearance and location information, and combines character detection and recognition in cropped text region together. The evaluation results on the benchmark datasets demonstrate that our proposed scheme outperforms the state-of-the-art methods both on scene character recognition and word recognition aspects.

Updating Landsat-derived land-cover maps using change detection and masking techniques

NASA Technical Reports Server (NTRS)

Likens, W.; Maw, K.

1982-01-01

The California Integrated Remote Sensing System's San Bernardino County Project was devised to study the utilization of a data base at a number of jurisdictional levels. The present paper discusses the implementation of change-detection and masking techniques in the updating of Landsat-derived land-cover maps. A baseline landcover classification was first created from a 1976 image, then the adjusted 1976 image was compared with a 1979 scene by the techniques of (1) multidate image classification, (2) difference image-distribution tails thresholding, (3) difference image classification, and (4) multi-dimensional chi-square analysis of a difference image. The union of the results of methods 1, 3 and 4 was used to create a mask of possible change areas between 1976 and 1979, which served to limit analysis of the update image and reduce comparison errors in unchanged areas. The techniques of spatial smoothing of change-detection products, and of combining results of difference change-detection algorithms are also shown to improve Landsat change-detection accuracies.

The signature of undetected change: an exploratory electrotomographic investigation of gradual change blindness.

PubMed

Kiat, John E; Dodd, Michael D; Belli, Robert F; Cheadle, Jacob E

2018-05-01

Neuroimaging-based investigations of change blindness, a phenomenon in which seemingly obvious changes in visual scenes fail to be detected, have significantly advanced our understanding of visual awareness. The vast majority of prior investigations, however, utilize paradigms involving visual disruptions (e.g., intervening blank screens, saccadic movements, "mudsplashes"), making it difficult to isolate neural responses toward visual changes cleanly. To address this issue in this present study, high-density EEG data (256 channel) were collected from 25 participants using a paradigm in which visual changes were progressively introduced into detailed real-world scenes without the use of visual disruption. Oscillatory activity associated with undetected changes was contrasted with activity linked to their absence using standardized low-resolution brain electromagnetic tomography (sLORETA). Although an insufficient number of detections were present to allow for analysis of actual change detection, increased beta-2 activity in the right inferior parietal lobule (rIPL), a region repeatedly associated with change blindness in disruption paradigms, followed by increased theta activity in the right superior temporal gyrus (rSTG) was noted in undetected visual change responses relative to the absence of change. We propose the rIPL beta-2 activity to be associated with orienting attention toward visual changes, with the subsequent rise in rSTG theta activity being potentially linked with updating preconscious perceptual memory representations. NEW & NOTEWORTHY This study represents the first neuroimaging-based investigation of gradual change blindness, a visual phenomenon that has significant potential to shed light on the processes underlying visual detection and conscious perception. The use of gradual change materials is reflective of real-world visual phenomena and allows for cleaner isolation of signals associated with the neural registration of change relative to the use of abrupt change transients.

The fate of object memory traces under change detection and change blindness.

PubMed

Busch, Niko A

2013-07-03

Observers often fail to detect substantial changes in a visual scene. This so-called change blindness is often taken as evidence that visual representations are sparse and volatile. This notion rests on the assumption that the failure to detect a change implies that representations of the changing objects are lost all together. However, recent evidence suggests that under change blindness, object memory representations may be formed and stored, but not retrieved. This study investigated the fate of object memory representations when changes go unnoticed. Participants were presented with scenes consisting of real world objects, one of which changed on each trial, while recording event-related potentials (ERPs). Participants were first asked to localize where the change had occurred. In an additional recognition task, participants then discriminated old objects, either from the pre-change or the post-change scene, from entirely new objects. Neural traces of object memories were studied by comparing ERPs for old and novel objects. Participants performed poorly in the detection task and often failed to recognize objects from the scene, especially pre-change objects. However, a robust old/novel effect was observed in the ERP, even when participants were change blind and did not recognize the old object. This implicit memory trace was found both for pre-change and post-change objects. These findings suggest that object memories are stored even under change blindness. Thus, visual representations may not be as sparse and volatile as previously thought. Rather, change blindness may point to a failure to retrieve and use these representations for change detection. Copyright © 2013 Elsevier B.V. All rights reserved.

A method of 3D object recognition and localization in a cloud of points

NASA Astrophysics Data System (ADS)

Bielicki, Jerzy; Sitnik, Robert

2013-12-01

The proposed method given in this article is prepared for analysis of data in the form of cloud of points directly from 3D measurements. It is designed for use in the end-user applications that can directly be integrated with 3D scanning software. The method utilizes locally calculated feature vectors (FVs) in point cloud data. Recognition is based on comparison of the analyzed scene with reference object library. A global descriptor in the form of a set of spatially distributed FVs is created for each reference model. During the detection process, correlation of subsets of reference FVs with FVs calculated in the scene is computed. Features utilized in the algorithm are based on parameters, which qualitatively estimate mean and Gaussian curvatures. Replacement of differentiation with averaging in the curvatures estimation makes the algorithm more resistant to discontinuities and poor quality of the input data. Utilization of the FV subsets allows to detect partially occluded and cluttered objects in the scene, while additional spatial information maintains false positive rate at a reasonably low level.

Urban area change detection procedures with remote sensing data

NASA Technical Reports Server (NTRS)

Maxwell, E. L. (Principal Investigator); Riordan, C. J.

1980-01-01

The underlying factors affecting the detection and identification of nonurban to urban land cover change using satellite data were studied. Computer programs were developed to create a digital scene and to simulate the effect of the sensor point spread function (PSF) on the transfer of modulation from the scene to an image of the scene. The theory behind the development of a digital filter representing the PSF is given as well as an example of its application. Atmospheric effects on modulation transfer are also discussed. A user's guide and program listings are given.

CB Database: A change blindness database for objects in natural indoor scenes.

PubMed

Sareen, Preeti; Ehinger, Krista A; Wolfe, Jeremy M

2016-12-01

Change blindness has been a topic of interest in cognitive sciences for decades. Change detection experiments are frequently used for studying various research topics such as attention and perception. However, creating change detection stimuli is tedious and there is no open repository of such stimuli using natural scenes. We introduce the Change Blindness (CB) Database with object changes in 130 colored images of natural indoor scenes. The size and eccentricity are provided for all the changes as well as reaction time data from a baseline experiment. In addition, we have two specialized satellite databases that are subsets of the 130 images. In one set, changes are seen in rooms or in mirrors in those rooms (Mirror Change Database). In the other, changes occur in a room or out a window (Window Change Database). Both the sets have controlled background, change size, and eccentricity. The CB Database is intended to provide researchers with a stimulus set of natural scenes with defined stimulus parameters that can be used for a wide range of experiments. The CB Database can be found at http://search.bwh.harvard.edu/new/CBDatabase.html .

Advanced radiometric and interferometric milimeter-wave scene simulations

NASA Technical Reports Server (NTRS)

Hauss, B. I.; Moffa, P. J.; Steele, W. G.; Agravante, H.; Davidheiser, R.; Samec, T.; Young, S. K.

1993-01-01

Smart munitions and weapons utilize various imaging sensors (including passive IR, active and passive millimeter-wave, and visible wavebands) to detect/identify targets at short standoff ranges and in varied terrain backgrounds. In order to design and evaluate these sensors under a variety of conditions, a high-fidelity scene simulation capability is necessary. Such a capability for passive millimeter-wave scene simulation exists at TRW. TRW's Advanced Radiometric Millimeter-Wave Scene Simulation (ARMSS) code is a rigorous, benchmarked, end-to-end passive millimeter-wave scene simulation code for interpreting millimeter-wave data, establishing scene signatures and evaluating sensor performance. In passive millimeter-wave imaging, resolution is limited due to wavelength and aperture size. Where high resolution is required, the utility of passive millimeter-wave imaging is confined to short ranges. Recent developments in interferometry have made possible high resolution applications on military platforms. Interferometry or synthetic aperture radiometry allows the creation of a high resolution image with a sparsely filled aperture. Borrowing from research work in radio astronomy, we have developed and tested at TRW scene reconstruction algorithms that allow the recovery of the scene from a relatively small number of spatial frequency components. In this paper, the TRW modeling capability is described and numerical results are presented.

Scene text detection by leveraging multi-channel information and local context

NASA Astrophysics Data System (ADS)

Wang, Runmin; Qian, Shengyou; Yang, Jianfeng; Gao, Changxin

2018-03-01

As an important information carrier, texts play significant roles in many applications. However, text detection in unconstrained scenes is a challenging problem due to cluttered backgrounds, various appearances, uneven illumination, etc.. In this paper, an approach based on multi-channel information and local context is proposed to detect texts in natural scenes. According to character candidate detection plays a vital role in text detection system, Maximally Stable Extremal Regions(MSERs) and Graph-cut based method are integrated to obtain the character candidates by leveraging the multi-channel image information. A cascaded false positive elimination mechanism are constructed from the perspective of the character and the text line respectively. Since the local context information is very valuable for us, these information is utilized to retrieve the missing characters for boosting the text detection performance. Experimental results on two benchmark datasets, i.e., the ICDAR 2011 dataset and the ICDAR 2013 dataset, demonstrate that the proposed method have achieved the state-of-the-art performance.

Differences in change blindness to real-life scenes in adults with autism spectrum conditions.

PubMed

Ashwin, Chris; Wheelwright, Sally; Baron-Cohen, Simon

2017-01-01

People often fail to detect large changes to visual scenes following a brief interruption, an effect known as 'change blindness'. People with autism spectrum conditions (ASC) have superior attention to detail and better discrimination of targets, and often notice small details that are missed by others. Together these predict people with autism should show enhanced perception of changes in simple change detection paradigms, including reduced change blindness. However, change blindness studies to date have reported mixed results in ASC, which have sometimes included no differences to controls or even enhanced change blindness. Attenuated change blindness has only been reported to date in ASC in children and adolescents, with no study reporting reduced change blindness in adults with ASC. The present study used a change blindness flicker task to investigate the detection of changes in images of everyday life in adults with ASC (n = 22) and controls (n = 22) using a simple change detection task design and full range of original scenes as stimuli. Results showed the adults with ASC had reduced change blindness compared to adult controls for changes to items of marginal interest in scenes, with no group difference for changes to items of central interest. There were no group differences in overall response latencies to correctly detect changes nor in the overall number of missed detections in the experiment. However, the ASC group showed greater missed changes for marginal interest changes of location, showing some evidence of greater change blindness as well. These findings show both reduced change blindness to marginal interest changes in ASC, based on response latencies, as well as greater change blindness to changes of location of marginal interest items, based on detection rates. The findings of reduced change blindness are consistent with clinical reports that people with ASC often notice small changes to less salient items within their environment, and are in-line with theories of enhanced local processing and greater attention to detail in ASC. The findings of lower detection rates for one of the marginal interest conditions may be related to problems in shifting attention or an overly focused attention spotlight.

The Development of Change Blindness: Children's Attentional Priorities whilst Viewing Naturalistic Scenes

ERIC Educational Resources Information Center

Fletcher-Watson, S.; Collis, J. M.; Findlay, J. M.; Leekam, S. R.

2009-01-01

Change blindness describes the surprising difficulty of detecting large changes in visual scenes when changes occur during a visual disruption. In order to study the developmental course of this phenomenon, a modified version of the flicker paradigm, based on Rensink, O'Regan & Clark (1997), was given to three groups of children aged 6-12 years…

Experimental study of digital image processing techniques for LANDSAT data

NASA Technical Reports Server (NTRS)

Rifman, S. S. (Principal Investigator); Allendoerfer, W. B.; Caron, R. H.; Pemberton, L. J.; Mckinnon, D. M.; Polanski, G.; Simon, K. W.

1976-01-01

The author has identified the following significant results. Results are reported for: (1) subscene registration, (2) full scene rectification and registration, (3) resampling techniques, (4) and ground control point (GCP) extraction. Subscenes (354 pixels x 234 lines) were registered to approximately 1/4 pixel accuracy and evaluated by change detection imagery for three cases: (1) bulk data registration, (2) precision correction of a reference subscene using GCP data, and (3) independently precision processed subscenes. Full scene rectification and registration results were evaluated by using a correlation technique to measure registration errors of 0.3 pixel rms thoughout the full scene. Resampling evaluations of nearest neighbor and TRW cubic convolution processed data included change detection imagery and feature classification. Resampled data were also evaluated for an MSS scene containing specular solar reflections.

Eye Movements and Visual Memory for Scenes

DTIC Science & Technology

2005-01-01

Scene memory research has demonstrated that the memory representation of a semantically inconsistent object in a scene is more detailed and/or complete... memory during scene viewing, then changes to semantically inconsistent objects (which should be represented more com- pletely) should be detected more... semantic description. Due to the surprise nature of the visual memory test, any learning that occurred during the search portion of the experiment was

A dual-process account of auditory change detection.

PubMed

McAnally, Ken I; Martin, Russell L; Eramudugolla, Ranmalee; Stuart, Geoffrey W; Irvine, Dexter R F; Mattingley, Jason B

2010-08-01

Listeners can be "deaf" to a substantial change in a scene comprising multiple auditory objects unless their attention has been directed to the changed object. It is unclear whether auditory change detection relies on identification of the objects in pre- and post-change scenes. We compared the rates at which listeners correctly identify changed objects with those predicted by change-detection models based on signal detection theory (SDT) and high-threshold theory (HTT). Detected changes were not identified as accurately as predicted by models based on either theory, suggesting that some changes are detected by a process that does not support change identification. Undetected changes were identified as accurately as predicted by the HTT model but much less accurately than predicted by the SDT models. The process underlying change detection was investigated further by determining receiver-operating characteristics (ROCs). ROCs did not conform to those predicted by either a SDT or a HTT model but were well modeled by a dual-process that incorporated HTT and SDT components. The dual-process model also accurately predicted the rates at which detected and undetected changes were correctly identified.

Impact of LANDSAT MSS sensor differences on change detection analysis

NASA Technical Reports Server (NTRS)

Likens, W. C.; Wrigley, R. C.

1983-01-01

Some 512 by 512 pixel subwindows for simultaneously acquired scene pairs obtained by LANDSAT 2,3 and 4 multispectral band scanners were coregistered using LANDSAT 4 scenes as the base to which the other images were registered. Scattergrams between the coregistered scenes (a form of contingency analysis) were used to radiometrically compare data from the various sensors. Mode values were derived and used to visually fit a linear regression. Root mean square errors of the registration varied between .1 and 1.5 pixels. There appear to be no major problem preventing the use of LANDSAT 4 MSS with previous MSS sensors for change detection, provided the noise interference can be removed or minimized. Data normalizations for change detection should be based on the data rather than solely on calibration information. This allows simultaneous normalization of the atmosphere as well as the radiometry.

First experience with Remote Sensing methods and selected sensors in the monitoring of mining areas - a case study of the Belchatow open cast mine

NASA Astrophysics Data System (ADS)

Wajs, Jaroslaw

2018-01-01

The paper presents satellite imagery from active SENTINEL-1A and passive SENTINEL-2A/2B sensors for their application in the monitoring of mining areas focused on detecting land changes. Multispectral scenes of SENTINEL-2A/2B have allowed for detecting changes in land-cover near the region of interest (ROI), i.e. the Szczercow dumping site in the Belchatow open cast lignite mine, central Poland, Europe. Scenes from SENTINEL-1A/1B satellite have also been used in the research. Processing of the SLC signal enabled creating a return intensity map in VV polarization. The obtained SAR scene was reclassified and shows a strong return signal from the dumping site and the open pit. This fact may be used in detection and monitoring of changes occurring within the analysed engineering objects.

Detecting temporal changes in acoustic scenes: The variable benefit of selective attention.

PubMed

Demany, Laurent; Bayle, Yann; Puginier, Emilie; Semal, Catherine

2017-09-01

Four experiments investigated change detection in acoustic scenes consisting of a sum of five amplitude-modulated pure tones. As the tones were about 0.7 octave apart and were amplitude-modulated with different frequencies (in the range 2-32 Hz), they were perceived as separate streams. Listeners had to detect a change in the frequency (experiments 1 and 2) or the shape (experiments 3 and 4) of the modulation of one of the five tones, in the presence of an informative cue orienting selective attention either before the scene (pre-cue) or after it (post-cue). The changes left intensity unchanged and were not detectable in the spectral (tonotopic) domain. Performance was much better with pre-cues than with post-cues. Thus, change deafness was manifest in the absence of an appropriate focusing of attention when the change occurred, even though the streams and the changes to be detected were acoustically very simple (in contrast to the conditions used in previous demonstrations of change deafness). In one case, the results were consistent with a model based on the assumption that change detection was possible if and only if attention was endogenously focused on a single tone. However, it was also found that changes resulting in a steepening of amplitude rises were to some extent able to draw attention exogenously. Change detection was not markedly facilitated when the change produced a discontinuity in the modulation domain, contrary to what could be expected from the perspective of predictive coding. Copyright © 2017 Elsevier B.V. All rights reserved.

Saliency-Guided Detection of Unknown Objects in RGB-D Indoor Scenes.

PubMed

Bao, Jiatong; Jia, Yunyi; Cheng, Yu; Xi, Ning

2015-08-27

This paper studies the problem of detecting unknown objects within indoor environments in an active and natural manner. The visual saliency scheme utilizing both color and depth cues is proposed to arouse the interests of the machine system for detecting unknown objects at salient positions in a 3D scene. The 3D points at the salient positions are selected as seed points for generating object hypotheses using the 3D shape. We perform multi-class labeling on a Markov random field (MRF) over the voxels of the 3D scene, combining cues from object hypotheses and 3D shape. The results from MRF are further refined by merging the labeled objects, which are spatially connected and have high correlation between color histograms. Quantitative and qualitative evaluations on two benchmark RGB-D datasets illustrate the advantages of the proposed method. The experiments of object detection and manipulation performed on a mobile manipulator validate its effectiveness and practicability in robotic applications.

Saliency-Guided Detection of Unknown Objects in RGB-D Indoor Scenes

PubMed Central

Bao, Jiatong; Jia, Yunyi; Cheng, Yu; Xi, Ning

2015-01-01

This paper studies the problem of detecting unknown objects within indoor environments in an active and natural manner. The visual saliency scheme utilizing both color and depth cues is proposed to arouse the interests of the machine system for detecting unknown objects at salient positions in a 3D scene. The 3D points at the salient positions are selected as seed points for generating object hypotheses using the 3D shape. We perform multi-class labeling on a Markov random field (MRF) over the voxels of the 3D scene, combining cues from object hypotheses and 3D shape. The results from MRF are further refined by merging the labeled objects, which are spatially connected and have high correlation between color histograms. Quantitative and qualitative evaluations on two benchmark RGB-D datasets illustrate the advantages of the proposed method. The experiments of object detection and manipulation performed on a mobile manipulator validate its effectiveness and practicability in robotic applications. PMID:26343656

Spectral feature characterization methods for blood stain detection in crime scene backgrounds

NASA Astrophysics Data System (ADS)

Yang, Jie; Mathew, Jobin J.; Dube, Roger R.; Messinger, David W.

2016-05-01

Blood stains are one of the most important types of evidence for forensic investigation. They contain valuable DNA information, and the pattern of the stains can suggest specifics about the nature of the violence that transpired at the scene. Blood spectral signatures containing unique reflectance or absorption features are important both for forensic on-site investigation and laboratory testing. They can be used for target detection and identification applied to crime scene hyperspectral imagery, and also be utilized to analyze the spectral variation of blood on various backgrounds. Non-blood stains often mislead the detection and can generate false alarms at a real crime scene, especially for dark and red backgrounds. This paper measured the reflectance of liquid blood and 9 kinds of non-blood samples in the range of 350 nm - 2500 nm in various crime scene backgrounds, such as pure samples contained in petri dish with various thicknesses, mixed samples with different colors and materials of fabrics, and mixed samples with wood, all of which are examined to provide sub-visual evidence for detecting and recognizing blood from non-blood samples in a realistic crime scene. The spectral difference between blood and non-blood samples are examined and spectral features such as "peaks" and "depths" of reflectance are selected. Two blood stain detection methods are proposed in this paper. The first method uses index to denote the ratio of "depth" minus "peak" over"depth" add"peak" within a wavelength range of the reflectance spectrum. The second method uses relative band depth of the selected wavelength ranges of the reflectance spectrum. Results show that the index method is able to discriminate blood from non-blood samples in most tested crime scene backgrounds, but is not able to detect it from black felt. Whereas the relative band depth method is able to discriminate blood from non-blood samples on all of the tested background material types and colors.

Mapping and monitoring renewable resources with space SAR

NASA Technical Reports Server (NTRS)

Ulaby, F. T.; Brisco, B.; Dobson, M. C.; Moezzi, S.

1983-01-01

The SEASAT-A SAR and SIR-A imagery was examined to evaluate the quality and type of information that can be extracted and used to monitor renewable resources on Earth. Two tasks were carried out: (1) a land cover classification study which utilized two sets of imagery acquired by the SEASAT-A SAR, one set by SIR-A, and one LANDSAT set (4 bands); and (2) a change detection to examine differences between pairs of SEASAT-A SAR images and relates them to hydrologic and/or agronomic variations in the scene.

Reduced change blindness suggests enhanced attention to detail in individuals with autism.

PubMed

Smith, Hayley; Milne, Elizabeth

2009-03-01

The phenomenon of change blindness illustrates that a limited number of items within the visual scene are attended to at any one time. It has been suggested that individuals with autism focus attention on less contextually relevant aspects of the visual scene, show superior perceptual discrimination and notice details which are often ignored by typical observers. In this study we investigated change blindness in autism by asking participants to detect continuity errors deliberately introduced into a short film. Whether the continuity errors involved central/marginal or social/non-social aspects of the visual scene was varied. Thirty adolescent participants, 15 with autistic spectrum disorder (ASD) and 15 typically developing (TD) controls participated. The participants with ASD detected significantly more errors than the TD participants. Both groups identified more errors involving central rather than marginal aspects of the scene, although this effect was larger in the TD participants. There was no difference in the number of social or non-social errors detected by either group of participants. In line with previous data suggesting an abnormally broad attentional spotlight and enhanced perceptual function in individuals with ASD, the results of this study suggest enhanced awareness of the visual scene in ASD. The results of this study could reflect superior top-down control of visual search in autism, enhanced perceptual function, or inefficient filtering of visual information in ASD.

Evaluation of experimental UAV video change detection

NASA Astrophysics Data System (ADS)

Bartelsen, J.; Saur, G.; Teutsch, C.

2016-10-01

During the last ten years, the availability of images acquired from unmanned aerial vehicles (UAVs) has been continuously increasing due to the improvements and economic success of flight and sensor systems. From our point of view, reliable and automatic image-based change detection may contribute to overcoming several challenging problems in military reconnaissance, civil security, and disaster management. Changes within a scene can be caused by functional activities, i.e., footprints or skid marks, excavations, or humidity penetration; these might be recognizable in aerial images, but are almost overlooked when change detection is executed manually. With respect to the circumstances, these kinds of changes may be an indication of sabotage, terroristic activity, or threatening natural disasters. Although image-based change detection is possible from both ground and aerial perspectives, in this paper we primarily address the latter. We have applied an extended approach to change detection as described by Saur and Kruger,1 and Saur et al.2 and have built upon the ideas of Saur and Bartelsen.3 The commercial simulation environment Virtual Battle Space 3 (VBS3) is used to simulate aerial "before" and "after" image acquisition concerning flight path, weather conditions and objects within the scene and to obtain synthetic videos. Video frames, which depict the same part of the scene, including "before" and "after" changes and not necessarily from the same perspective, are registered pixel-wise against each other by a photogrammetric concept, which is based on a homography. The pixel-wise registration is used to apply an automatic difference analysis, which, to a limited extent, is able to suppress typical errors caused by imprecise frame registration, sensor noise, vegetation and especially parallax effects. The primary concern of this paper is to seriously evaluate the possibilities and limitations of our current approach for image-based change detection with respect to the flight path, viewpoint change and parametrization. Hence, based on synthetic "before" and "after" videos of a simulated scene, we estimated the precision and recall of automatically detected changes. In addition and based on our approach, we illustrate the results showing the change detection in short, but real video sequences. Future work will improve the photogrammetric approach for frame registration, and extensive real video material, capable of change detection, will be acquired.

Change deafness for real spatialized environmental scenes.

PubMed

Gaston, Jeremy; Dickerson, Kelly; Hipp, Daniel; Gerhardstein, Peter

2017-01-01

The everyday auditory environment is complex and dynamic; often, multiple sounds co-occur and compete for a listener's cognitive resources. 'Change deafness', framed as the auditory analog to the well-documented phenomenon of 'change blindness', describes the finding that changes presented within complex environments are often missed. The present study examines a number of stimulus factors that may influence change deafness under real-world listening conditions. Specifically, an AX (same-different) discrimination task was used to examine the effects of both spatial separation over a loudspeaker array and the type of change (sound source additions and removals) on discrimination of changes embedded in complex backgrounds. Results using signal detection theory and accuracy analyses indicated that, under most conditions, errors were significantly reduced for spatially distributed relative to non-spatial scenes. A second goal of the present study was to evaluate a possible link between memory for scene contents and change discrimination. Memory was evaluated by presenting a cued recall test following each trial of the discrimination task. Results using signal detection theory and accuracy analyses indicated that recall ability was similar in terms of accuracy, but there were reductions in sensitivity compared to previous reports. Finally, the present study used a large and representative sample of outdoor, urban, and environmental sounds, presented in unique combinations of nearly 1000 trials per participant. This enabled the exploration of the relationship between change perception and the perceptual similarity between change targets and background scene sounds. These (post hoc) analyses suggest both a categorical and a stimulus-level relationship between scene similarity and the magnitude of change errors.

Clandestine laboratory scene investigation and processing using portable GC/MS

NASA Astrophysics Data System (ADS)

Matejczyk, Raymond J.

1997-02-01

This presentation describes the use of portable gas chromatography/mass spectrometry for on-scene investigation and processing of clandestine laboratories. Clandestine laboratory investigations present special problems to forensic investigators. These crime scenes contain many chemical hazards that must be detected, identified and collected as evidence. Gas chromatography/mass spectrometry performed on-scene with a rugged, portable unit is capable of analyzing a variety of matrices for drugs and chemicals used in the manufacture of illicit drugs, such as methamphetamine. Technologies used to detect various materials at a scene have particular applications but do not address the wide range of samples, chemicals, matrices and mixtures that exist in clan labs. Typical analyses performed by GC/MS are for the purpose of positively establishing the identity of starting materials, chemicals and end-product collected from clandestine laboratories. Concerns for the public and investigator safety and the environment are also important factors for rapid on-scene data generation. Here is described the implementation of a portable multiple-inlet GC/MS system designed for rapid deployment to a scene to perform forensic investigations of clandestine drug manufacturing laboratories. GC/MS has long been held as the 'gold standard' in performing forensic chemical analyses. With the capability of GC/MS to separate and produce a 'chemical fingerprint' of compounds, it is utilized as an essential technique for detecting and positively identifying chemical evidence. Rapid and conclusive on-scene analysis of evidence will assist the forensic investigators in collecting only pertinent evidence thereby reducing the amount of evidence to be transported, reducing chain of custody concerns, reducing costs and hazards, maintaining sample integrity and speeding the completion of the investigative process.

Robust colour constancy in red-green dichromats

PubMed Central

Linhares, João M. M.; Moreira, Humberto; Lillo, Julio; Nascimento, Sérgio M. C.

2017-01-01

Colour discrimination has been widely studied in red-green (R-G) dichromats but the extent to which their colour constancy is affected remains unclear. This work estimated the extent of colour constancy for four normal trichromatic observers and seven R-G dichromats when viewing natural scenes under simulated daylight illuminants. Hyperspectral imaging data from natural scenes were used to generate the stimuli on a calibrated CRT display. In experiment 1, observers viewed a reference scene illuminated by daylight with a correlated colour temperature (CCT) of 6700K; observers then viewed sequentially two versions of the same scene, one illuminated by either a higher or lower CCT (condition 1, pure CCT change with constant luminance) or a higher or lower average luminance (condition 2, pure luminance change with a constant CCT). The observers’ task was to identify the version of the scene that looked different from the reference scene. Thresholds for detecting a pure CCT change or a pure luminance change were estimated, and it was found that those for R-G dichromats were marginally higher than for normal trichromats regarding CCT. In experiment 2, observers viewed sequentially a reference scene and a comparison scene with a CCT change or a luminance change above threshold for each observer. The observers’ task was to identify whether or not the change was an intensity change. No significant differences were found between the responses of normal trichromats and dichromats. These data suggest robust colour constancy mechanisms along daylight locus in R-G dichromacy. PMID:28662218

Robust colour constancy in red-green dichromats.

PubMed

Álvaro, Leticia; Linhares, João M M; Moreira, Humberto; Lillo, Julio; Nascimento, Sérgio M C

2017-01-01

Colour discrimination has been widely studied in red-green (R-G) dichromats but the extent to which their colour constancy is affected remains unclear. This work estimated the extent of colour constancy for four normal trichromatic observers and seven R-G dichromats when viewing natural scenes under simulated daylight illuminants. Hyperspectral imaging data from natural scenes were used to generate the stimuli on a calibrated CRT display. In experiment 1, observers viewed a reference scene illuminated by daylight with a correlated colour temperature (CCT) of 6700K; observers then viewed sequentially two versions of the same scene, one illuminated by either a higher or lower CCT (condition 1, pure CCT change with constant luminance) or a higher or lower average luminance (condition 2, pure luminance change with a constant CCT). The observers' task was to identify the version of the scene that looked different from the reference scene. Thresholds for detecting a pure CCT change or a pure luminance change were estimated, and it was found that those for R-G dichromats were marginally higher than for normal trichromats regarding CCT. In experiment 2, observers viewed sequentially a reference scene and a comparison scene with a CCT change or a luminance change above threshold for each observer. The observers' task was to identify whether or not the change was an intensity change. No significant differences were found between the responses of normal trichromats and dichromats. These data suggest robust colour constancy mechanisms along daylight locus in R-G dichromacy.

Visual encoding and fixation target selection in free viewing: presaccadic brain potentials

PubMed Central

Nikolaev, Andrey R.; Jurica, Peter; Nakatani, Chie; Plomp, Gijs; van Leeuwen, Cees

2013-01-01

In scrutinizing a scene, the eyes alternate between fixations and saccades. During a fixation, two component processes can be distinguished: visual encoding and selection of the next fixation target. We aimed to distinguish the neural correlates of these processes in the electrical brain activity prior to a saccade onset. Participants viewed color photographs of natural scenes, in preparation for a change detection task. Then, for each participant and each scene we computed an image heat map, with temperature representing the duration and density of fixations. The temperature difference between the start and end points of saccades was taken as a measure of the expected task-relevance of the information concentrated in specific regions of a scene. Visual encoding was evaluated according to whether subsequent change was correctly detected. Saccades with larger temperature difference were more likely to be followed by correct detection than ones with smaller temperature differences. The amplitude of presaccadic activity over anterior brain areas was larger for correct detection than for detection failure. This difference was observed for short “scrutinizing” but not for long “explorative” saccades, suggesting that presaccadic activity reflects top-down saccade guidance. Thus, successful encoding requires local scanning of scene regions which are expected to be task-relevant. Next, we evaluated fixation target selection. Saccades “moving up” in temperature were preceded by presaccadic activity of higher amplitude than those “moving down”. This finding suggests that presaccadic activity reflects attention deployed to the following fixation location. Our findings illustrate how presaccadic activity can elucidate concurrent brain processes related to the immediate goal of planning the next saccade and the larger-scale goal of constructing a robust representation of the visual scene. PMID:23818877

Slow changing postural cues cancel visual field dependence on self-tilt detection.

PubMed

Scotto Di Cesare, C; Macaluso, T; Mestre, D R; Bringoux, L

2015-01-01

Interindividual differences influence the multisensory integration process involved in spatial perception. Here, we assessed the effect of visual field dependence on self-tilt detection relative to upright, as a function of static vs. slow changing visual or postural cues. To that aim, we manipulated slow rotations (i.e., 0.05° s(-1)) of the body and/or the visual scene in pitch. Participants had to indicate whether they felt being tilted forward at successive angles. Results show that thresholds for self-tilt detection substantially differed between visual field dependent/independent subjects, when only the visual scene was rotated. This difference was no longer present when the body was actually rotated, whatever the visual scene condition (i.e., absent, static or rotated relative to the observer). These results suggest that the cancellation of visual field dependence by dynamic postural cues may rely on a multisensory reweighting process, where slow changing vestibular/somatosensory inputs may prevail over visual inputs. Copyright © 2014 Elsevier B.V. All rights reserved.

The Attentional Boost Effect: Transient increases in attention to one task enhance performance in a second task.

PubMed

Swallow, Khena M; Jiang, Yuhong V

2010-04-01

Recent work on event perception suggests that perceptual processing increases when events change. An important question is how such changes influence the way other information is processed, particularly during dual-task performance. In this study, participants monitored a long series of distractor items for an occasional target as they simultaneously encoded unrelated background scenes. The appearance of an occasional target could have two opposite effects on the secondary task: It could draw attention away from the second task, or, as a change in the ongoing event, it could improve secondary task performance. Results were consistent with the second possibility. Memory for scenes presented simultaneously with the targets was better than memory for scenes that preceded or followed the targets. This effect was observed when the primary detection task involved visual feature oddball detection, auditory oddball detection, and visual color-shape conjunction detection. It was eliminated when the detection task was omitted, and when it required an arbitrary response mapping. The appearance of occasional, task-relevant events appears to trigger a temporal orienting response that facilitates processing of concurrently attended information (Attentional Boost Effect). Copyright 2009 Elsevier B.V. All rights reserved.

The Attentional Boost Effect: Transient Increases in Attention to One Task Enhance Performance in a Second Task

PubMed Central

Swallow, Khena M.; Jiang, Yuhong V.

2009-01-01

Recent work on event perception suggests that perceptual processing increases when events change. An important question is how such changes influence the way other information is processed, particularly during dual-task performance. In this study, participants monitored a long series of distractor items for an occasional target as they simultaneously encoded unrelated background scenes. The appearance of an occasional target could have two opposite effects on the secondary task: It could draw attention away from the second task, or, as a change in the ongoing event, it could improve secondary task performance. Results were consistent with the second possibility. Memory for scenes presented simultaneously with the targets was better than memory for scenes that preceded or followed the targets. This effect was observed when the primary detection task involved visual feature oddball detection, auditory oddball detection, and visual color-shape conjunction detection. It was eliminated when the detection task was omitted, and when it required an arbitrary response mapping. The appearance of occasional, task-relevant events appears to trigger a temporal orienting response that facilitates processing of concurrently attended information (Attentional Boost Effect). PMID:20080232

Saliency predicts change detection in pictures of natural scenes.

PubMed

Wright, Michael J

2005-01-01

It has been proposed that the visual system encodes the salience of objects in the visual field in an explicit two-dimensional map that guides visual selective attention. Experiments were conducted to determine whether salience measurements applied to regions of pictures of outdoor scenes could predict the detection of changes in those regions. To obtain a quantitative measure of change detection, observers located changes in pairs of colour pictures presented across an interstimulus interval (ISI). Salience measurements were then obtained from different observers for image change regions using three independent methods, and all were positively correlated with change detection. Factor analysis extracted a single saliency factor that accounted for 62% of the variance contained in the four measures. Finally, estimates of the magnitude of the image change in each picture pair were obtained, using nine separate visual filters representing low-level vision features (luminance, colour, spatial frequency, orientation, edge density). None of the feature outputs was significantly associated with change detection or saliency. On the other hand it was shown that high-level (structural) properties of the changed region were related to saliency and to change detection: objects were more salient than shadows and more detectable when changed.

The effect of distraction on change detection in crowded acoustic scenes.

PubMed

Petsas, Theofilos; Harrison, Jemma; Kashino, Makio; Furukawa, Shigeto; Chait, Maria

2016-11-01

In this series of behavioural experiments we investigated the effect of distraction on the maintenance of acoustic scene information in short-term memory. Stimuli are artificial acoustic 'scenes' composed of several (up to twelve) concurrent tone-pip streams ('sources'). A gap (1000 ms) is inserted partway through the 'scene'; Changes in the form of an appearance of a new source or disappearance of an existing source, occur after the gap in 50% of the trials. Listeners were instructed to monitor the unfolding 'soundscapes' for these events. Distraction was measured by presenting distractor stimuli during the gap. Experiments 1 and 2 used a dual task design where listeners were required to perform a task with varying attentional demands ('High Demand' vs. 'Low Demand') on brief auditory (Experiment 1a) or visual (Experiment 1b) signals presented during the gap. Experiments 2 and 3 required participants to ignore distractor sounds and focus on the change detection task. Our results demonstrate that the maintenance of scene information in short-term memory is influenced by the availability of attentional and/or processing resources during the gap, and that this dependence appears to be modality specific. We also show that these processes are susceptible to bottom up driven distraction even in situations when the distractors are not novel, but occur on each trial. Change detection performance is systematically linked with the, independently determined, perceptual salience of the distractor sound. The findings also demonstrate that the present task may be a useful objective means for determining relative perceptual salience. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Broad attention to multiple individual objects may facilitate change detection with complex auditory scenes.

PubMed

Irsik, Vanessa C; Vanden Bosch der Nederlanden, Christina M; Snyder, Joel S

2016-11-01

Attention and other processing constraints limit the perception of objects in complex scenes, which has been studied extensively in the visual sense. We used a change deafness paradigm to examine how attention to particular objects helps and hurts the ability to notice changes within complex auditory scenes. In a counterbalanced design, we examined how cueing attention to particular objects affected performance in an auditory change-detection task through the use of valid or invalid cues and trials without cues (Experiment 1). We further examined how successful encoding predicted change-detection performance using an object-encoding task and we addressed whether performing the object-encoding task along with the change-detection task affected performance overall (Experiment 2). Participants had more error for invalid compared to valid and uncued trials, but this effect was reduced in Experiment 2 compared to Experiment 1. When the object-encoding task was present, listeners who completed the uncued condition first had less overall error than those who completed the cued condition first. All participants showed less change deafness when they successfully encoded change-relevant compared to irrelevant objects during valid and uncued trials. However, only participants who completed the uncued condition first also showed this effect during invalid cue trials, suggesting a broader scope of attention. These findings provide converging evidence that attention to change-relevant objects is crucial for successful detection of acoustic changes and that encouraging broad attention to multiple objects is the best way to reduce change deafness. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

[Visual representation of natural scenes in flicker changes].

PubMed

Nakashima, Ryoichi; Yokosawa, Kazuhiko

2010-08-01

Coherence theory in scene perception (Rensink, 2002) assumes the retention of volatile object representations on which attention is not focused. On the other hand, visual memory theory in scene perception (Hollingworth & Henderson, 2002) assumes that robust object representations are retained. In this study, we hypothesized that the difference between these two theories is derived from the difference of the experimental tasks that they are based on. In order to verify this hypothesis, we examined the properties of visual representation by using a change detection and memory task in a flicker paradigm. We measured the representations when participants were instructed to search for a change in a scene, and compared them with the intentional memory representations. The visual representations were retained in visual long-term memory even in the flicker paradigm, and were as robust as the intentional memory representations. However, the results indicate that the representations are unavailable for explicitly localizing a scene change, but are available for answering the recognition test. This suggests that coherence theory and visual memory theory are compatible.

Compressed Sensing in On-Grid MIMO Radar.

PubMed

Minner, Michael F

2015-01-01

The accurate detection of targets is a significant problem in multiple-input multiple-output (MIMO) radar. Recent advances of Compressive Sensing offer a means of efficiently accomplishing this task. The sparsity constraints needed to apply the techniques of Compressive Sensing to problems in radar systems have led to discretizations of the target scene in various domains, such as azimuth, time delay, and Doppler. Building upon recent work, we investigate the feasibility of on-grid Compressive Sensing-based MIMO radar via a threefold azimuth-delay-Doppler discretization for target detection and parameter estimation. We utilize a colocated random sensor array and transmit distinct linear chirps to a small scene with few, slowly moving targets. Relying upon standard far-field and narrowband assumptions, we analyze the efficacy of various recovery algorithms in determining the parameters of the scene through numerical simulations, with particular focus on the ℓ 1-squared Nonnegative Regularization method.

Spatial detection of tv channel logos as outliers from the content

NASA Astrophysics Data System (ADS)

Ekin, Ahmet; Braspenning, Ralph

2006-01-01

This paper proposes a purely image-based TV channel logo detection algorithm that can detect logos independently from their motion and transparency features. The proposed algorithm can robustly detect any type of logos, such as transparent and animated, without requiring any temporal constraints whereas known methods have to wait for the occurrence of large motion in the scene and assume stationary logos. The algorithm models logo pixels as outliers from the actual scene content that is represented by multiple 3-D histograms in the YC BC R space. We use four scene histograms corresponding to each of the four corners because the content characteristics change from one image corner to another. A further novelty of the proposed algorithm is that we define image corners and the areas where we compute the scene histograms by a cinematic technique called Golden Section Rule that is used by professionals. The robustness of the proposed algorithm is demonstrated over a dataset of representative TV content.

Figure-ground segmentation can occur without attention.

PubMed

Kimchi, Ruth; Peterson, Mary A

2008-07-01

The question of whether or not figure-ground segmentation can occur without attention is unresolved. Early theorists assumed it can, but the evidence is scant and open to alternative interpretations. Recent research indicating that attention can influence figure-ground segmentation raises the question anew. We examined this issue by asking participants to perform a demanding change-detection task on a small matrix presented on a task-irrelevant scene of alternating regions organized into figures and grounds by convexity. Independently of any change in the matrix, the figure-ground organization of the scene changed or remained the same. Changes in scene organization produced congruency effects on target-change judgments, even though, when probed with surprise questions, participants could report neither the figure-ground status of the region on which the matrix appeared nor any change in that status. When attending to the scene, participants reported figure-ground status and changes to it highly accurately. These results clearly demonstrate that figure-ground segmentation can occur without focal attention.

Segregating the neural correlates of physical and perceived change in auditory input using the change deafness effect.

PubMed

Puschmann, Sebastian; Weerda, Riklef; Klump, Georg; Thiel, Christiane M

2013-05-01

Psychophysical experiments show that auditory change detection can be disturbed in situations in which listeners have to monitor complex auditory input. We made use of this change deafness effect to segregate the neural correlates of physical change in auditory input from brain responses related to conscious change perception in an fMRI experiment. Participants listened to two successively presented complex auditory scenes, which consisted of six auditory streams, and had to decide whether scenes were identical or whether the frequency of one stream was changed between presentations. Our results show that physical changes in auditory input, independent of successful change detection, are represented at the level of auditory cortex. Activations related to conscious change perception, independent of physical change, were found in the insula and the ACC. Moreover, our data provide evidence for significant effective connectivity between auditory cortex and the insula in the case of correctly detected auditory changes, but not for missed changes. This underlines the importance of the insula/anterior cingulate network for conscious change detection.

Does scene context always facilitate retrieval of visual object representations?

PubMed

Nakashima, Ryoichi; Yokosawa, Kazuhiko

2011-04-01

An object-to-scene binding hypothesis maintains that visual object representations are stored as part of a larger scene representation or scene context, and that scene context facilitates retrieval of object representations (see, e.g., Hollingworth, Journal of Experimental Psychology: Learning, Memory and Cognition, 32, 58-69, 2006). Support for this hypothesis comes from data using an intentional memory task. In the present study, we examined whether scene context always facilitates retrieval of visual object representations. In two experiments, we investigated whether the scene context facilitates retrieval of object representations, using a new paradigm in which a memory task is appended to a repeated-flicker change detection task. Results indicated that in normal scene viewing, in which many simultaneous objects appear, scene context facilitation of the retrieval of object representations-henceforth termed object-to-scene binding-occurred only when the observer was required to retain much information for a task (i.e., an intentional memory task).

The elephant in the room: Inconsistency in scene viewing and representation.

PubMed

Spotorno, Sara; Tatler, Benjamin W

2017-10-01

We examined the extent to which semantic informativeness, consistency with expectations and perceptual salience contribute to object prioritization in scene viewing and representation. In scene viewing (Experiments 1-2), semantic guidance overshadowed perceptual guidance in determining fixation order, with the greatest prioritization for objects that were diagnostic of the scene's depicted event. Perceptual properties affected selection of consistent objects (regardless of their informativeness) but not of inconsistent objects. Semantic and perceptual properties also interacted in influencing foveal inspection, as inconsistent objects were fixated longer than low but not high salience diagnostic objects. While not studied in direct competition with each other (each studied in competition with diagnostic objects), we found that inconsistent objects were fixated earlier and for longer than consistent but marginally informative objects. In change detection (Experiment 3), perceptual guidance overshadowed semantic guidance, promoting detection of highly salient changes. A residual advantage for diagnosticity over inconsistency emerged only when selection prioritization could not be based on low-level features. Overall these findings show that semantic inconsistency is not prioritized within a scene when competing with other relevant information that is essential to scene understanding and respects observers' expectations. Moreover, they reveal that the relative dominance of semantic or perceptual properties during selection depends on ongoing task requirements. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

On improving IED object detection by exploiting scene geometry using stereo processing

NASA Astrophysics Data System (ADS)

van de Wouw, Dennis W. J. M.; Dubbelman, Gijs; de With, Peter H. N.

2015-03-01

Detecting changes in the environment with respect to an earlier data acquisition is important for several applications, such as finding Improvised Explosive Devices (IEDs). We explore and evaluate the benefit of depth sensing in the context of automatic change detection, where an existing monocular system is extended with a second camera in a fixed stereo setup. We then propose an alternative frame registration that exploits scene geometry, in particular the ground plane. Furthermore, change characterization is applied to localized depth maps to distinguish between 3D physical changes and shadows, which solves one of the main challenges of a monocular system. The proposed system is evaluated on real-world acquisitions, containing geo-tagged test objects of 18 18 9 cm up to a distance of 60 meters. The proposed extensions lead to a significant reduction of the false-alarm rate by a factor of 3, while simultaneously improving the detection score with 5%.

Change Deafness and the Organizational Properties of Sounds

ERIC Educational Resources Information Center

Gregg, Melissa K.; Samuel, Arthur G.

2008-01-01

Change blindness, or the failure to detect (often large) changes to visual scenes, has been demonstrated in a variety of different situations. Failures to detect auditory changes are far less studied, and thus little is known about the nature of change deafness. Five experiments were conducted to explore the processes involved in change deafness…

Interrupted Visual Searches Reveal Volatile Search Memory

ERIC Educational Resources Information Center

Shen, Y. Jeremy; Jiang, Yuhong V.

2006-01-01

This study investigated memory from interrupted visual searches. Participants conducted a change detection search task on polygons overlaid on scenes. Search was interrupted by various disruptions, including unfilled delay, passive viewing of other scenes, and additional search on new displays. Results showed that performance was unaffected by…

Real-time 3D change detection of IEDs

NASA Astrophysics Data System (ADS)

Wathen, Mitch; Link, Norah; Iles, Peter; Jinkerson, John; Mrstik, Paul; Kusevic, Kresimir; Kovats, David

2012-06-01

Road-side bombs are a real and continuing threat to soldiers in theater. CAE USA recently developed a prototype Volume based Intelligence Surveillance Reconnaissance (VISR) sensor platform for IED detection. This vehicle-mounted, prototype sensor system uses a high data rate LiDAR (1.33 million range measurements per second) to generate a 3D mapping of roadways. The mapped data is used as a reference to generate real-time change detection on future trips on the same roadways. The prototype VISR system is briefly described. The focus of this paper is the methodology used to process the 3D LiDAR data, in real-time, to detect small changes on and near the roadway ahead of a vehicle traveling at moderate speeds with sufficient warning to stop the vehicle at a safe distance from the threat. The system relies on accurate navigation equipment to geo-reference the reference run and the change-detection run. Since it was recognized early in the project that detection of small changes could not be achieved with accurate navigation solutions alone, a scene alignment algorithm was developed to register the reference run with the change detection run prior to applying the change detection algorithm. Good success was achieved in simultaneous real time processing of scene alignment plus change detection.

Estimating pixel variances in the scenes of staring sensors

DOEpatents

Simonson, Katherine M [Cedar Crest, NM; Ma, Tian J [Albuquerque, NM

2012-01-24

A technique for detecting changes in a scene perceived by a staring sensor is disclosed. The technique includes acquiring a reference image frame and a current image frame of a scene with the staring sensor. A raw difference frame is generated based upon differences between the reference image frame and the current image frame. Pixel error estimates are generated for each pixel in the raw difference frame based at least in part upon spatial error estimates related to spatial intensity gradients in the scene. The pixel error estimates are used to mitigate effects of camera jitter in the scene between the current image frame and the reference image frame.

Preliminary Comparisons of the Information Content and Utility of TM Versus MSS Data

NASA Technical Reports Server (NTRS)

Markham, B. L.

1984-01-01

Comparisons were made between subscenes from the first TM scene acquired of the Washington, D.C. area and a MSS scene acquired approximately one year earlier. Three types of analyses were conducted to compare TM and MSS data: a water body analysis, a principal components analysis and a spectral clustering analysis. The water body analysis compared the capability of the TM to the MSS for detecting small uniform targets. Of the 59 ponds located on aerial photographs 34 (58%) were detected by the TM with six commission errors (15%) and 13 (22%) were detected by the MSS with three commission errors (19%). The smallest water body detected by the TM was 16 meters; the smallest detected by the MSS was 40 meters. For the principal components analysis, means and covariance matrices were calculated for each subscene, and principal components images generated and characterized. In the spectral clustering comparison each scene was independently clustered and the clusters were assigned to informational classes. The preliminary comparison indicated that TM data provides enhancements over MSS in terms of (1) small target detection and (2) data dimensionality (even with 4-band data). The extra dimension, partially resultant from TM band 1, appears useful for built-up/non-built-up area separation.

Edge detection

NASA Astrophysics Data System (ADS)

Hildreth, E. C.

1985-09-01

For both biological systems and machines, vision begins with a large and unwieldly array of measurements of the amount of light reflected from surfaces in the environment. The goal of vision is to recover physical properties of objects in the scene such as the location of object boundaries and the structure, color and texture of object surfaces, from the two-dimensional image that is projected onto the eye or camera. This goal is not achieved in a single step: vision proceeds in stages, with each stage producing increasingly more useful descriptions of the image and then the scene. The first clues about the physical properties of the scene are provided by the changes of intensity in the image. The importance of intensity changes and edges in early visual processing has led to extensive research on their detection, description and use, both in computer and biological vision systems. This article reviews some of the theory that underlies the detection of edges, and the methods used to carry out this analysis.

a Novel Framework for Remote Sensing Image Scene Classification

NASA Astrophysics Data System (ADS)

Jiang, S.; Zhao, H.; Wu, W.; Tan, Q.

2018-04-01

High resolution remote sensing (HRRS) images scene classification aims to label an image with a specific semantic category. HRRS images contain more details of the ground objects and their spatial distribution patterns than low spatial resolution images. Scene classification can bridge the gap between low-level features and high-level semantics. It can be applied in urban planning, target detection and other fields. This paper proposes a novel framework for HRRS images scene classification. This framework combines the convolutional neural network (CNN) and XGBoost, which utilizes CNN as feature extractor and XGBoost as a classifier. Then, this framework is evaluated on two different HRRS images datasets: UC-Merced dataset and NWPU-RESISC45 dataset. Our framework achieved satisfying accuracies on two datasets, which is 95.57 % and 83.35 % respectively. From the experiments result, our framework has been proven to be effective for remote sensing images classification. Furthermore, we believe this framework will be more practical for further HRRS scene classification, since it costs less time on training stage.

Beyond scene gist: Objects guide search more than scene background.

PubMed

Koehler, Kathryn; Eckstein, Miguel P

2017-06-01

Although the facilitation of visual search by contextual information is well established, there is little understanding of the independent contributions of different types of contextual cues in scenes. Here we manipulated 3 types of contextual information: object co-occurrence, multiple object configurations, and background category. We isolated the benefits of each contextual cue to target detectability, its impact on decision bias, confidence, and the guidance of eye movements. We find that object-based information guides eye movements and facilitates perceptual judgments more than scene background. The degree of guidance and facilitation of each contextual cue can be related to its inherent informativeness about the target spatial location as measured by human explicit judgments about likely target locations. Our results improve the understanding of the contributions of distinct contextual scene components to search and suggest that the brain's utilization of cues to guide eye movements is linked to the cue's informativeness about the target's location. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Comparison on driving fatigue related hemodynamics activated by auditory and visual stimulus

NASA Astrophysics Data System (ADS)

Deng, Zishan; Gao, Yuan; Li, Ting

2018-02-01

As one of the main causes of traffic accidents, driving fatigue deserves researchers' attention and its detection and monitoring during long-term driving require a new technique to realize. Since functional near-infrared spectroscopy (fNIRS) can be applied to detect cerebral hemodynamic responses, we can promisingly expect its application in fatigue level detection. Here, we performed three different kinds of experiments on a driver and recorded his cerebral hemodynamic responses when driving for long hours utilizing our device based on fNIRS. Each experiment lasted for 7 hours and one of the three specific experimental tests, detecting the driver's response to sounds, traffic lights and direction signs respectively, was done every hour. The results showed that visual stimulus was easier to cause fatigue compared with auditory stimulus and visual stimulus induced by traffic lights scenes was easier to cause fatigue compared with visual stimulus induced by direction signs in the first few hours. We also found that fatigue related hemodynamics caused by auditory stimulus increased fastest, then traffic lights scenes, and direction signs scenes slowest. Our study successfully compared audio, visual color, and visual character stimulus in sensitivity to cause driving fatigue, which is meaningful for driving safety management.

Techniques for automatic large scale change analysis of temporal multispectral imagery

NASA Astrophysics Data System (ADS)

Mercovich, Ryan A.

Change detection in remotely sensed imagery is a multi-faceted problem with a wide variety of desired solutions. Automatic change detection and analysis to assist in the coverage of large areas at high resolution is a popular area of research in the remote sensing community. Beyond basic change detection, the analysis of change is essential to provide results that positively impact an image analyst's job when examining potentially changed areas. Present change detection algorithms are geared toward low resolution imagery, and require analyst input to provide anything more than a simple pixel level map of the magnitude of change that has occurred. One major problem with this approach is that change occurs in such large volume at small spatial scales that a simple change map is no longer useful. This research strives to create an algorithm based on a set of metrics that performs a large area search for change in high resolution multispectral image sequences and utilizes a variety of methods to identify different types of change. Rather than simply mapping the magnitude of any change in the scene, the goal of this research is to create a useful display of the different types of change in the image. The techniques presented in this dissertation are used to interpret large area images and provide useful information to an analyst about small regions that have undergone specific types of change while retaining image context to make further manual interpretation easier. This analyst cueing to reduce information overload in a large area search environment will have an impact in the areas of disaster recovery, search and rescue situations, and land use surveys among others. By utilizing a feature based approach founded on applying existing statistical methods and new and existing topological methods to high resolution temporal multispectral imagery, a novel change detection methodology is produced that can automatically provide useful information about the change occurring in large area and high resolution image sequences. The change detection and analysis algorithm developed could be adapted to many potential image change scenarios to perform automatic large scale analysis of change.

A study of payload specialist station monitor size constraints. [space shuttle orbiters

NASA Technical Reports Server (NTRS)

Kirkpatrick, M., III; Shields, N. L., Jr.; Malone, T. B.

1975-01-01

Constraints on the CRT display size for the shuttle orbiter cabin are studied. The viewing requirements placed on these monitors were assumed to involve display of imaged scenes providing visual feedback during payload operations and display of alphanumeric characters. Data on target recognition/resolution, target recognition, and range rate detection by human observers were utilized to determine viewing requirements for imaged scenes. Field-of-view and acuity requirements for a variety of payload operations were obtained along with the necessary detection capability in terms of range-to-target size ratios. The monitor size necessary to meet the acuity requirements was established. An empirical test was conducted to determine required recognition sizes for displayed alphanumeric characters. The results of the test were used to determine the number of characters which could be simultaneously displayed based on the recognition size requirements using the proposed monitor size. A CRT display of 20 x 20 cm is recommended. A portion of the display area is used for displaying imaged scenes and the remaining display area is used for alphanumeric characters pertaining to the displayed scene. The entire display is used for the character alone mode.

Edge detection and localization with edge pattern analysis and inflection characterization

NASA Astrophysics Data System (ADS)

Jiang, Bo

2012-05-01

In general edges are considered to be abrupt changes or discontinuities in two dimensional image signal intensity distributions. The accuracy of front-end edge detection methods in image processing impacts the eventual success of higher level pattern analysis downstream. To generalize edge detectors designed from a simple ideal step function model to real distortions in natural images, research on one dimensional edge pattern analysis to improve the accuracy of edge detection and localization proposes an edge detection algorithm, which is composed by three basic edge patterns, such as ramp, impulse, and step. After mathematical analysis, general rules for edge representation based upon the classification of edge types into three categories-ramp, impulse, and step (RIS) are developed to reduce detection and localization errors, especially reducing "double edge" effect that is one important drawback to the derivative method. But, when applying one dimensional edge pattern in two dimensional image processing, a new issue is naturally raised that the edge detector should correct marking inflections or junctions of edges. Research on human visual perception of objects and information theory pointed out that a pattern lexicon of "inflection micro-patterns" has larger information than a straight line. Also, research on scene perception gave an idea that contours have larger information are more important factor to determine the success of scene categorization. Therefore, inflections or junctions are extremely useful features, whose accurate description and reconstruction are significant in solving correspondence problems in computer vision. Therefore, aside from adoption of edge pattern analysis, inflection or junction characterization is also utilized to extend traditional derivative edge detection algorithm. Experiments were conducted to test my propositions about edge detection and localization accuracy improvements. The results support the idea that these edge detection method improvements are effective in enhancing the accuracy of edge detection and localization.

Robust drone detection for day/night counter-UAV with static VIS and SWIR cameras

NASA Astrophysics Data System (ADS)

Müller, Thomas

2017-05-01

Recent progress in the development of unmanned aerial vehicles (UAVs) has led to more and more situations in which drones like quadrocopters or octocopters pose a potential serious thread or could be used as a powerful tool for illegal activities. Therefore, counter-UAV systems are required in a lot of applications to detect approaching drones as early as possible. In this paper, an efficient and robust algorithm is presented for UAV detection using static VIS and SWIR cameras. Whereas VIS cameras with a high resolution enable to detect UAVs in the daytime in further distances, surveillance at night can be performed with a SWIR camera. First, a background estimation and structural adaptive change detection process detects movements and other changes in the observed scene. Afterwards, the local density of changes is computed used for background density learning and to build up the foreground model which are compared in order to finally get the UAV alarm result. The density model is used to filter out noise effects, on the one hand. On the other hand, moving scene parts like moving leaves in the wind or driving cars on a street can easily be learned in order to mask such areas out and suppress false alarms there. This scene learning is done automatically simply by processing without UAVs in order to capture the normal situation. The given results document the performance of the presented approach in VIS and SWIR in different situations.

A Probabilistic Model of Visual Working Memory: Incorporating Higher Order Regularities into Working Memory Capacity Estimates

ERIC Educational Resources Information Center

Brady, Timothy F.; Tenenbaum, Joshua B.

2013-01-01

When remembering a real-world scene, people encode both detailed information about specific objects and higher order information like the overall gist of the scene. However, formal models of change detection, like those used to estimate visual working memory capacity, assume observers encode only a simple memory representation that includes no…

Change Blindness Phenomena for Virtual Reality Display Systems.

PubMed

Steinicke, Frank; Bruder, Gerd; Hinrichs, Klaus; Willemsen, Pete

2011-09-01

In visual perception, change blindness describes the phenomenon that persons viewing a visual scene may apparently fail to detect significant changes in that scene. These phenomena have been observed in both computer-generated imagery and real-world scenes. Several studies have demonstrated that change blindness effects occur primarily during visual disruptions such as blinks or saccadic eye movements. However, until now the influence of stereoscopic vision on change blindness has not been studied thoroughly in the context of visual perception research. In this paper, we introduce change blindness techniques for stereoscopic virtual reality (VR) systems, providing the ability to substantially modify a virtual scene in a manner that is difficult for observers to perceive. We evaluate techniques for semiimmersive VR systems, i.e., a passive and active stereoscopic projection system as well as an immersive VR system, i.e., a head-mounted display, and compare the results to those of monoscopic viewing conditions. For stereoscopic viewing conditions, we found that change blindness phenomena occur with the same magnitude as in monoscopic viewing conditions. Furthermore, we have evaluated the potential of the presented techniques for allowing abrupt, and yet significant, changes of a stereoscopically displayed virtual reality environment.

Extended image differencing for change detection in UAV video mosaics

NASA Astrophysics Data System (ADS)

Saur, Günter; Krüger, Wolfgang; Schumann, Arne

2014-03-01

Change detection is one of the most important tasks when using unmanned aerial vehicles (UAV) for video reconnaissance and surveillance. We address changes of short time scale, i.e. the observations are taken in time distances from several minutes up to a few hours. Each observation is a short video sequence acquired by the UAV in near-nadir view and the relevant changes are, e.g., recently parked or moved vehicles. In this paper we extend our previous approach of image differencing for single video frames to video mosaics. A precise image-to-image registration combined with a robust matching approach is needed to stitch the video frames to a mosaic. Additionally, this matching algorithm is applied to mosaic pairs in order to align them to a common geometry. The resulting registered video mosaic pairs are the input of the change detection procedure based on extended image differencing. A change mask is generated by an adaptive threshold applied to a linear combination of difference images of intensity and gradient magnitude. The change detection algorithm has to distinguish between relevant and non-relevant changes. Examples for non-relevant changes are stereo disparity at 3D structures of the scene, changed size of shadows, and compression or transmission artifacts. The special effects of video mosaicking such as geometric distortions and artifacts at moving objects have to be considered, too. In our experiments we analyze the influence of these effects on the change detection results by considering several scenes. The results show that for video mosaics this task is more difficult than for single video frames. Therefore, we extended the image registration by estimating an elastic transformation using a thin plate spline approach. The results for mosaics are comparable to that of single video frames and are useful for interactive image exploitation due to a larger scene coverage.

A compressed sensing method with analytical results for lidar feature classification

NASA Astrophysics Data System (ADS)

Allen, Josef D.; Yuan, Jiangbo; Liu, Xiuwen; Rahmes, Mark

2011-04-01

We present an innovative way to autonomously classify LiDAR points into bare earth, building, vegetation, and other categories. One desirable product of LiDAR data is the automatic classification of the points in the scene. Our algorithm automatically classifies scene points using Compressed Sensing Methods via Orthogonal Matching Pursuit algorithms utilizing a generalized K-Means clustering algorithm to extract buildings and foliage from a Digital Surface Models (DSM). This technology reduces manual editing while being cost effective for large scale automated global scene modeling. Quantitative analyses are provided using Receiver Operating Characteristics (ROC) curves to show Probability of Detection and False Alarm of buildings vs. vegetation classification. Histograms are shown with sample size metrics. Our inpainting algorithms then fill the voids where buildings and vegetation were removed, utilizing Computational Fluid Dynamics (CFD) techniques and Partial Differential Equations (PDE) to create an accurate Digital Terrain Model (DTM) [6]. Inpainting preserves building height contour consistency and edge sharpness of identified inpainted regions. Qualitative results illustrate other benefits such as Terrain Inpainting's unique ability to minimize or eliminate undesirable terrain data artifacts.

Automatic event recognition and anomaly detection with attribute grammar by learning scene semantics

NASA Astrophysics Data System (ADS)

Qi, Lin; Yao, Zhenyu; Li, Li; Dong, Junyu

2007-11-01

In this paper we present a novel framework for automatic event recognition and abnormal behavior detection with attribute grammar by learning scene semantics. This framework combines learning scene semantics by trajectory analysis and constructing attribute grammar-based event representation. The scene and event information is learned automatically. Abnormal behaviors that disobey scene semantics or event grammars rules are detected. By this method, an approach to understanding video scenes is achieved. Further more, with this prior knowledge, the accuracy of abnormal event detection is increased.

3D change detection in staggered voxels model for robotic sensing and navigation

NASA Astrophysics Data System (ADS)

Liu, Ruixu; Hampshire, Brandon; Asari, Vijayan K.

2016-05-01

3D scene change detection is a challenging problem in robotic sensing and navigation. There are several unpredictable aspects in performing scene change detection. A change detection method which can support various applications in varying environmental conditions is proposed. Point cloud models are acquired from a RGB-D sensor, which provides the required color and depth information. Change detection is performed on robot view point cloud model. A bilateral filter smooths the surface and fills the holes as well as keeps the edge details on depth image. Registration of the point cloud model is implemented by using Random Sample Consensus (RANSAC) algorithm. It uses surface normal as the previous stage for the ground and wall estimate. After preprocessing the data, we create a point voxel model which defines voxel as surface or free space. Then we create a color model which defines each voxel that has a color by the mean of all points' color value in this voxel. The preliminary change detection is detected by XOR subtract on the point voxel model. Next, the eight neighbors for this center voxel are defined. If they are neither all `changed' voxels nor all `no changed' voxels, a histogram of location and hue channel color is estimated. The experimental evaluations performed to evaluate the capability of our algorithm show promising results for novel change detection that indicate all the changing objects with very limited false alarm rate.

Immersive Virtual Moon Scene System Based on Panoramic Camera Data of Chang'E-3

NASA Astrophysics Data System (ADS)

Gao, X.; Liu, J.; Mu, L.; Yan, W.; Zeng, X.; Zhang, X.; Li, C.

2014-12-01

The system "Immersive Virtual Moon Scene" is used to show the virtual environment of Moon surface in immersive environment. Utilizing stereo 360-degree imagery from panoramic camera of Yutu rover, the system enables the operator to visualize the terrain and the celestial background from the rover's point of view in 3D. To avoid image distortion, stereo 360-degree panorama stitched by 112 images is projected onto inside surface of sphere according to panorama orientation coordinates and camera parameters to build the virtual scene. Stars can be seen from the Moon at any time. So we render the sun, planets and stars according to time and rover's location based on Hipparcos catalogue as the background on the sphere. Immersing in the stereo virtual environment created by this imaged-based rendering technique, the operator can zoom, pan to interact with the virtual Moon scene and mark interesting objects. Hardware of the immersive virtual Moon system is made up of four high lumen projectors and a huge curve screen which is 31 meters long and 5.5 meters high. This system which take all panoramic camera data available and use it to create an immersive environment, enable operator to interact with the environment and mark interesting objects contributed heavily to establishment of science mission goals in Chang'E-3 mission. After Chang'E-3 mission, the lab with this system will be open to public. Besides this application, Moon terrain stereo animations based on Chang'E-1 and Chang'E-2 data will be showed to public on the huge screen in the lab. Based on the data of lunar exploration，we will made more immersive virtual moon scenes and animations to help the public understand more about the Moon in the future.

Change Analysis in Structural Laser Scanning Point Clouds: The Baseline Method

PubMed Central

Shen, Yueqian; Lindenbergh, Roderik; Wang, Jinhu

2016-01-01

A method is introduced for detecting changes from point clouds that avoids registration. For many applications, changes are detected between two scans of the same scene obtained at different times. Traditionally, these scans are aligned to a common coordinate system having the disadvantage that this registration step introduces additional errors. In addition, registration requires stable targets or features. To avoid these issues, we propose a change detection method based on so-called baselines. Baselines connect feature points within one scan. To analyze changes, baselines connecting corresponding points in two scans are compared. As feature points either targets or virtual points corresponding to some reconstructable feature in the scene are used. The new method is implemented on two scans sampling a masonry laboratory building before and after seismic testing, that resulted in damages in the order of several centimeters. The centres of the bricks of the laboratory building are automatically extracted to serve as virtual points. Baselines connecting virtual points and/or target points are extracted and compared with respect to a suitable structural coordinate system. Changes detected from the baseline analysis are compared to a traditional cloud to cloud change analysis demonstrating the potential of the new method for structural analysis. PMID:28029121

Change Analysis in Structural Laser Scanning Point Clouds: The Baseline Method.

PubMed

Shen, Yueqian; Lindenbergh, Roderik; Wang, Jinhu

2016-12-24

A method is introduced for detecting changes from point clouds that avoids registration. For many applications, changes are detected between two scans of the same scene obtained at different times. Traditionally, these scans are aligned to a common coordinate system having the disadvantage that this registration step introduces additional errors. In addition, registration requires stable targets or features. To avoid these issues, we propose a change detection method based on so-called baselines. Baselines connect feature points within one scan. To analyze changes, baselines connecting corresponding points in two scans are compared. As feature points either targets or virtual points corresponding to some reconstructable feature in the scene are used. The new method is implemented on two scans sampling a masonry laboratory building before and after seismic testing, that resulted in damages in the order of several centimeters. The centres of the bricks of the laboratory building are automatically extracted to serve as virtual points. Baselines connecting virtual points and/or target points are extracted and compared with respect to a suitable structural coordinate system. Changes detected from the baseline analysis are compared to a traditional cloud to cloud change analysis demonstrating the potential of the new method for structural analysis.

Children Use Object-Level Category Knowledge to Detect Changes in Complex Auditory Scenes

ERIC Educational Resources Information Center

Vanden Bosch der Nederlanden, Christina M.; Snyder, Joel S.; Hannon, Erin E.

2016-01-01

Children interact with and learn about all types of sound sources, including dogs, bells, trains, and human beings. Although it is clear that knowledge of semantic categories for everyday sights and sounds develops during childhood, there are very few studies examining how children use this knowledge to make sense of auditory scenes. We used a…

Direct versus indirect processing changes the influence of color in natural scene categorization.

PubMed

Otsuka, Sachio; Kawaguchi, Jun

2009-10-01

We examined whether participants would use a negative priming (NP) paradigm to categorize color and grayscale images of natural scenes that were presented peripherally and were ignored. We focused on (1) attentional resources allocated to natural scenes and (2) direct versus indirect processing of them. We set up low and high attention-load conditions, based on the set size of the searched stimuli in the prime display (one and five). Participants were required to detect and categorize the target objects in natural scenes in a central visual search task, ignoring peripheral natural images in both the prime and probe displays. The results showed that, irrespective of attention load, NP was observed for color scenes but not for grayscale scenes. We did not observe any effect of color information in central visual search, where participants responded directly to natural scenes. These results indicate that, in a situation in which participants indirectly process natural scenes, color information is critical to object categorization, but when the scenes are processed directly, color information does not contribute to categorization.

Census cities experiment in urban change detection

NASA Technical Reports Server (NTRS)

Wray, J. R. (Principal Investigator)

1973-01-01

The author has identified the following significant results. Work continues on mapping of 1970 urban land use from 1970 census contemporaneous aircraft photography. In addition, change detection analysis from 1972 aircraft photography is underway for several urban test sites. Land use maps, mosaics, and census overlays for the two largest urban test sites are nearing publication readiness. Preliminary examinations of ERTS-1 imagery of San Francisco Bay have been conducted which show that tracts of land of more than 10 acres in size which are undergoing development in an urban setting can be identified. In addition, each spectral band is being evaluated as to its utility for urban analyses. It has been found that MSS infrared band 7 helps to differentiate intra-urban land use details not found in other MSS bands or in the RBV coverage of the same scene. Good quality false CIR composites have been generated from 9 x 9 inch positive MSS bands using the Diazo process.

Inertial navigation sensor integrated obstacle detection system

NASA Technical Reports Server (NTRS)

Bhanu, Bir (Inventor); Roberts, Barry A. (Inventor)

1992-01-01

A system that incorporates inertial sensor information into optical flow computations to detect obstacles and to provide alternative navigational paths free from obstacles. The system is a maximally passive obstacle detection system that makes selective use of an active sensor. The active detection typically utilizes a laser. Passive sensor suite includes binocular stereo, motion stereo and variable fields-of-view. Optical flow computations involve extraction, derotation and matching of interest points from sequential frames of imagery, for range interpolation of the sensed scene, which in turn provides obstacle information for purposes of safe navigation.

Complex Dynamic Scene Perception: Effects of Attentional Set on Perceiving Single and Multiple Event Types

ERIC Educational Resources Information Center

Sanocki, Thomas; Sulman, Noah

2013-01-01

Three experiments measured the efficiency of monitoring complex scenes composed of changing objects, or events. All events lasted about 4 s, but in a given block of trials, could be of a single type (single task) or of multiple types (multitask, with a total of four event types). Overall accuracy of detecting target events amid distractors was…

Change blindness, aging, and cognition

PubMed Central

Rizzo, Matthew; Sparks, JonDavid; McEvoy, Sean; Viamonte, Sarah; Kellison, Ida; Vecera, Shaun P.

2011-01-01

Change blindness (CB), the inability to detect changes in visual scenes, may increase with age and early Alzheimer’s disease (AD). To test this hypothesis, participants were asked to localize changes in natural scenes. Dependent measures were response time (RT), hit rate, false positives (FP), and true sensitivity (d′). Increased age correlated with increased sensitivity and RT; AD predicted even slower RT. Accuracy and RT were negatively correlated. Differences in FP were nonsignificant. CB correlated with impaired attention, working memory, and executive function. Advanced age and AD were associated with increased CB, perhaps due to declining memory and attention. CB could affect real-world tasks, like automobile driving. PMID:19051127

Change blindness, aging, and cognition.

PubMed

Rizzo, Matthew; Sparks, Jondavid; McEvoy, Sean; Viamonte, Sarah; Kellison, Ida; Vecera, Shaun P

2009-02-01

Change blindness (CB), the inability to detect changes in visual scenes, may increase with age and early Alzheimer's disease (AD). To test this hypothesis, participants were asked to localize changes in natural scenes. Dependent measures were response time (RT), hit rate, false positives (FP), and true sensitivity (d'). Increased age correlated with increased sensitivity and RT; AD predicted even slower RT. Accuracy and RT were negatively correlated. Differences in FP were nonsignificant. CB correlated with impaired attention, working memory, and executive function. Advanced age and AD were associated with increased CB, perhaps due to declining memory and attention. CB could affect real-world tasks, like automobile driving.

Aircraft MSS data registration and vegetation classification of wetland change detection

USGS Publications Warehouse

Christensen, E.J.; Jensen, J.R.; Ramsey, Elijah W.; Mackey, H.E.

1988-01-01

Portions of the Savannah River floodplain swamp were evaluated for vegetation change using high resolution (5a??6 m) aircraft multispectral scanner (MSS) data. Image distortion from aircraft movement prevented precise image-to-image registration in some areas. However, when small scenes were used (200-250 ha), a first-order linear transformation provided registration accuracies of less than or equal to one pixel. A larger area was registered using a piecewise linear method. Five major wetland classes were identified and evaluated for change. Phenological differences and the variable distribution of vegetation limited wetland type discrimination. Using unsupervised methods and ground-collected vegetation data, overall classification accuracies ranged from 84 per cent to 87 per cent for each scene. Results suggest that high-resolution aircraft MSS data can be precisely registered, if small areas are used, and that wetland vegetation change can be accurately detected and monitored.

Real-time synchronized multiple-sensor IR/EO scene generation utilizing the SGI Onyx2

NASA Astrophysics Data System (ADS)

Makar, Robert J.; O'Toole, Brian E.

1998-07-01

An approach to utilize the symmetric multiprocessing environment of the Silicon Graphics Inc.R (SGI) Onyx2TM has been developed to support the generation of IR/EO scenes in real-time. This development, supported by the Naval Air Warfare Center Aircraft Division (NAWC/AD), focuses on high frame rate hardware-in-the-loop testing of multiple sensor avionics systems. In the past, real-time IR/EO scene generators have been developed as custom architectures that were often expensive and difficult to maintain. Previous COTS scene generation systems, designed and optimized for visual simulation, could not be adapted for accurate IR/EO sensor stimulation. The new Onyx2 connection mesh architecture made it possible to develop a more economical system while maintaining the fidelity needed to stimulate actual sensors. An SGI based Real-time IR/EO Scene Simulator (RISS) system was developed to utilize the Onyx2's fast multiprocessing hardware to perform real-time IR/EO scene radiance calculations. During real-time scene simulation, the multiprocessors are used to update polygon vertex locations and compute radiometrically accurate floating point radiance values. The output of this process can be utilized to drive a variety of scene rendering engines. Recent advancements in COTS graphics systems, such as the Silicon Graphics InfiniteRealityR make a total COTS solution possible for some classes of sensors. This paper will discuss the critical technologies that apply to infrared scene generation and hardware-in-the-loop testing using SGI compatible hardware. Specifically, the application of RISS high-fidelity real-time radiance algorithms on the SGI Onyx2's multiprocessing hardware will be discussed. Also, issues relating to external real-time control of multiple synchronized scene generation channels will be addressed.

A fuzzy measure approach to motion frame analysis for scene detection. M.S. Thesis - Houston Univ.

NASA Technical Reports Server (NTRS)

Leigh, Albert B.; Pal, Sankar K.

1992-01-01

This paper addresses a solution to the problem of scene estimation of motion video data in the fuzzy set theoretic framework. Using fuzzy image feature extractors, a new algorithm is developed to compute the change of information in each of two successive frames to classify scenes. This classification process of raw input visual data can be used to establish structure for correlation. The algorithm attempts to fulfill the need for nonlinear, frame-accurate access to video data for applications such as video editing and visual document archival/retrieval systems in multimedia environments.

A Saliency Guided Semi-Supervised Building Change Detection Method for High Resolution Remote Sensing Images

PubMed Central

Hou, Bin; Wang, Yunhong; Liu, Qingjie

2016-01-01

Characterizations of up to date information of the Earth’s surface are an important application providing insights to urban planning, resources monitoring and environmental studies. A large number of change detection (CD) methods have been developed to solve them by utilizing remote sensing (RS) images. The advent of high resolution (HR) remote sensing images further provides challenges to traditional CD methods and opportunities to object-based CD methods. While several kinds of geospatial objects are recognized, this manuscript mainly focuses on buildings. Specifically, we propose a novel automatic approach combining pixel-based strategies with object-based ones for detecting building changes with HR remote sensing images. A multiresolution contextual morphological transformation called extended morphological attribute profiles (EMAPs) allows the extraction of geometrical features related to the structures within the scene at different scales. Pixel-based post-classification is executed on EMAPs using hierarchical fuzzy clustering. Subsequently, the hierarchical fuzzy frequency vector histograms are formed based on the image-objects acquired by simple linear iterative clustering (SLIC) segmentation. Then, saliency and morphological building index (MBI) extracted on difference images are used to generate a pseudo training set. Ultimately, object-based semi-supervised classification is implemented on this training set by applying random forest (RF). Most of the important changes are detected by the proposed method in our experiments. This study was checked for effectiveness using visual evaluation and numerical evaluation. PMID:27618903

A Saliency Guided Semi-Supervised Building Change Detection Method for High Resolution Remote Sensing Images.

PubMed

Hou, Bin; Wang, Yunhong; Liu, Qingjie

2016-08-27

Characterizations of up to date information of the Earth's surface are an important application providing insights to urban planning, resources monitoring and environmental studies. A large number of change detection (CD) methods have been developed to solve them by utilizing remote sensing (RS) images. The advent of high resolution (HR) remote sensing images further provides challenges to traditional CD methods and opportunities to object-based CD methods. While several kinds of geospatial objects are recognized, this manuscript mainly focuses on buildings. Specifically, we propose a novel automatic approach combining pixel-based strategies with object-based ones for detecting building changes with HR remote sensing images. A multiresolution contextual morphological transformation called extended morphological attribute profiles (EMAPs) allows the extraction of geometrical features related to the structures within the scene at different scales. Pixel-based post-classification is executed on EMAPs using hierarchical fuzzy clustering. Subsequently, the hierarchical fuzzy frequency vector histograms are formed based on the image-objects acquired by simple linear iterative clustering (SLIC) segmentation. Then, saliency and morphological building index (MBI) extracted on difference images are used to generate a pseudo training set. Ultimately, object-based semi-supervised classification is implemented on this training set by applying random forest (RF). Most of the important changes are detected by the proposed method in our experiments. This study was checked for effectiveness using visual evaluation and numerical evaluation.

Faces Do Not Capture Special Attention in Children with Autism Spectrum Disorder: A Change Blindness Study

ERIC Educational Resources Information Center

Kikuchi, Yukiko; Senju, Atsushi; Tojo, Yoshikuni; Osanai, Hiroo; Hasegawa, Toshikazu

2009-01-01

Two experiments investigated attention of children with autism spectrum disorder (ASD) to faces and objects. In both experiments, children (7- to 15-year-olds) detected the difference between 2 visual scenes. Results in Experiment 1 revealed that typically developing children (n = 16) detected the change in faces faster than in objects, whereas…

What you fear will appear: detection of schematic spiders in spider fear.

PubMed

Peira, Nathalie; Golkar, Armita; Larsson, Maria; Wiens, Stefan

2010-01-01

Various experimental tasks suggest that fear guides attention. However, because these tasks often lack ecological validity, it is unclear to what extent results from these tasks can be generalized to real-life situations. In change detection tasks, a brief interruption of the visual input (i.e., a blank interval or a scene cut) often results in undetected changes in the scene. This setup resembles real-life viewing behavior and is used here to increase ecological validity of the attentional task without compromising control over the stimuli presented. Spider-fearful and nonfearful women detected schematic spiders and flowers that were added to one of two identical background pictures that alternated with a brief blank in between them (i.e., flicker paradigm). Results showed that spider-fearful women detected spiders (but not flowers) faster than did nonfearful women. Because spiders and flowers had similar low-level features, these findings suggest that fear guides attention on the basis of object features rather than simple low-level features.

Automatic Pedestrian Crossing Detection and Impairment Analysis Based on Mobile Mapping System

NASA Astrophysics Data System (ADS)

Liu, X.; Zhang, Y.; Li, Q.

2017-09-01

Pedestrian crossing, as an important part of transportation infrastructures, serves to secure pedestrians' lives and possessions and keep traffic flow in order. As a prominent feature in the street scene, detection of pedestrian crossing contributes to 3D road marking reconstruction and diminishing the adverse impact of outliers in 3D street scene reconstruction. Since pedestrian crossing is subject to wearing and tearing from heavy traffic flow, it is of great imperative to monitor its status quo. On this account, an approach of automatic pedestrian crossing detection using images from vehicle-based Mobile Mapping System is put forward and its defilement and impairment are analyzed in this paper. Firstly, pedestrian crossing classifier is trained with low recall rate. Then initial detections are refined by utilizing projection filtering, contour information analysis, and monocular vision. Finally, a pedestrian crossing detection and analysis system with high recall rate, precision and robustness will be achieved. This system works for pedestrian crossing detection under different situations and light conditions. It can recognize defiled and impaired crossings automatically in the meanwhile, which facilitates monitoring and maintenance of traffic facilities, so as to reduce potential traffic safety problems and secure lives and property.

Influence of visual clutter on the effect of navigated safety inspection: a case study on elevator installation.

PubMed

Liao, Pin-Chao; Sun, Xinlu; Liu, Mei; Shih, Yu-Nien

2018-01-11

Navigated safety inspection based on task-specific checklists can increase the hazard detection rate, theoretically with interference from scene complexity. Visual clutter, a proxy of scene complexity, can theoretically impair visual search performance, but its impact on the effect of safety inspection performance remains to be explored for the optimization of navigated inspection. This research aims to explore whether the relationship between working memory and hazard detection rate is moderated by visual clutter. Based on a perceptive model of hazard detection, we: (a) developed a mathematical influence model for construction hazard detection; (b) designed an experiment to observe the performance of hazard detection rate with adjusted working memory under different levels of visual clutter, while using an eye-tracking device to observe participants' visual search processes; (c) utilized logistic regression to analyze the developed model under various visual clutter. The effect of a strengthened working memory on the detection rate through increased search efficiency is more apparent in high visual clutter. This study confirms the role of visual clutter in construction-navigated inspections, thus serving as a foundation for the optimization of inspection planning.

Robust curb detection with fusion of 3D-Lidar and camera data.

PubMed

Tan, Jun; Li, Jian; An, Xiangjing; He, Hangen

2014-05-21

Curb detection is an essential component of Autonomous Land Vehicles (ALV), especially important for safe driving in urban environments. In this paper, we propose a fusion-based curb detection method through exploiting 3D-Lidar and camera data. More specifically, we first fuse the sparse 3D-Lidar points and high-resolution camera images together to recover a dense depth image of the captured scene. Based on the recovered dense depth image, we propose a filter-based method to estimate the normal direction within the image. Then, by using the multi-scale normal patterns based on the curb's geometric property, curb point features fitting the patterns are detected in the normal image row by row. After that, we construct a Markov Chain to model the consistency of curb points which utilizes the continuous property of the curb, and thus the optimal curb path which links the curb points together can be efficiently estimated by dynamic programming. Finally, we perform post-processing operations to filter the outliers, parameterize the curbs and give the confidence scores on the detected curbs. Extensive evaluations clearly show that our proposed method can detect curbs with strong robustness at real-time speed for both static and dynamic scenes.

Use of multi-sensor active fire detections to map fires in the United States: the future of monitoring trends in burn severity

USGS Publications Warehouse

Picotte, Joshua J.; Coan, Michael; Howard, Stephen M.

2014-01-01

The effort to utilize satellite-based MODIS, AVHRR, and GOES fire detections from the Hazard Monitoring System (HMS) to identify undocumented fires in Florida and improve the Monitoring Trends in Burn Severity (MTBS) mapping process has yielded promising results. This method was augmented using regression tree models to identify burned/not-burned pixels (BnB) in every Landsat scene (1984–2012) in Worldwide Referencing System 2 Path/Rows 16/40, 17/39, and 1839. The burned area delineations were combined with the HMS detections to create burned area polygons attributed with their date of fire detection. Within our study area, we processed 88,000 HMS points (2003–2012) and 1,800 Landsat scenes to identify approximately 300,000 burned area polygons. Six percent of these burned area polygons were larger than the 500-acre MTBS minimum size threshold. From this study, we conclude that the process can significantly improve understanding of fire occurrence and improve the efficiency and timeliness of assessing its impacts upon the landscape.

Grasp Preparation Improves Change Detection for Congruent Objects

ERIC Educational Resources Information Center

Symes, Ed; Tucker, Mike; Ellis, Rob; Vainio, Lari; Ottoboni, Giovanni

2008-01-01

A series of experiments provided converging support for the hypothesis that action preparation biases selective attention to action-congruent object features. When visual transients are masked in so-called "change-blindness scenes," viewers are blind to substantial changes between 2 otherwise identical pictures that flick back and forth. The…

Ecological Virtual Reality Evaluation of Neglect Symptoms (EVENS): Effects of Virtual Scene Complexity in the Assessment of Poststroke Unilateral Spatial Neglect.

PubMed

Ogourtsova, Tatiana; Archambault, Philippe; Sangani, Samir; Lamontagne, Anouk

2018-01-01

Unilateral spatial neglect (USN) is a highly prevalent and disabling poststroke impairment. USN is traditionally assessed with paper-and-pencil tests that lack ecological validity, generalization to real-life situations and are easily compensated for in chronic stages. Virtual reality (VR) can, however, counteract these limitations. We aimed to examine the feasibility of a novel assessment of USN symptoms in a functional shopping activity, the Ecological VR-based Evaluation of Neglect Symptoms (EVENS). EVENS is immersive and consists of simple and complex 3-dimensional scenes depicting grocery shopping shelves, where joystick-based object detection and navigation tasks are performed while seated. Effects of virtual scene complexity on navigational and detection abilities in patients with (USN+, n = 12) and without (USN-, n = 15) USN following a right hemisphere stroke and in age-matched healthy controls (HC, n = 9) were determined. Longer detection times, larger mediolateral deviations from ideal paths and longer navigation times were found in USN+ versus USN- and HC groups, particularly in the complex scene. EVENS detected lateralized and nonlateralized USN-related deficits, performance alterations that were dependent or independent of USN severity, and performance alterations in 3 USN- subjects versus HC. EVENS' environmental changing complexity, along with the functional tasks of far space detection and navigation can potentially be clinically relevant and warrant further empirical investigation. Findings are discussed in terms of attentional models, lateralized versus nonlateralized deficits in USN, and tasks-specific mechanisms.

Object detection in natural scenes: Independent effects of spatial and category-based attention.

PubMed

Stein, Timo; Peelen, Marius V

2017-04-01

Humans are remarkably efficient in detecting highly familiar object categories in natural scenes, with evidence suggesting that such object detection can be performed in the (near) absence of attention. Here we systematically explored the influences of both spatial attention and category-based attention on the accuracy of object detection in natural scenes. Manipulating both types of attention additionally allowed for addressing how these factors interact: whether the requirement for spatial attention depends on the extent to which observers are prepared to detect a specific object category-that is, on category-based attention. The results showed that the detection of targets from one category (animals or vehicles) was better than the detection of targets from two categories (animals and vehicles), demonstrating the beneficial effect of category-based attention. This effect did not depend on the semantic congruency of the target object and the background scene, indicating that observers attended to visual features diagnostic of the foreground target objects from the cued category. Importantly, in three experiments the detection of objects in scenes presented in the periphery was significantly impaired when observers simultaneously performed an attentionally demanding task at fixation, showing that spatial attention affects natural scene perception. In all experiments, the effects of category-based attention and spatial attention on object detection performance were additive rather than interactive. Finally, neither spatial nor category-based attention influenced metacognitive ability for object detection performance. These findings demonstrate that efficient object detection in natural scenes is independently facilitated by spatial and category-based attention.

Multiple pedestrian detection using IR LED stereo camera

NASA Astrophysics Data System (ADS)

Ling, Bo; Zeifman, Michael I.; Gibson, David R. P.

2007-09-01

As part of the U.S. Department of Transportations Intelligent Vehicle Initiative (IVI) program, the Federal Highway Administration (FHWA) is conducting R&D in vehicle safety and driver information systems. There is an increasing number of applications where pedestrian monitoring is of high importance. Visionbased pedestrian detection in outdoor scenes is still an open challenge. People dress in very different colors that sometimes blend with the background, wear hats or carry bags, and stand, walk and change directions unpredictably. The background is various, containing buildings, moving or parked cars, bicycles, street signs, signals, etc. Furthermore, existing pedestrian detection systems perform only during daytime, making it impossible to detect pedestrians at night. Under FHWA funding, we are developing a multi-pedestrian detection system using IR LED stereo camera. This system, without using any templates, detects the pedestrians through statistical pattern recognition utilizing 3D features extracted from the disparity map. A new IR LED stereo camera is being developed, which can help detect pedestrians during daytime and night time. Using the image differencing and denoising, we have also developed new methods to estimate the disparity map of pedestrians in near real time. Our system will have a hardware interface with the traffic controller through wireless communication. Once pedestrians are detected, traffic signals at the street intersections will change phases to alert the drivers of approaching vehicles. The initial test results using images collected at a street intersection show that our system can detect pedestrians in near real time.

Detection of multiple airborne targets from multisensor data

NASA Astrophysics Data System (ADS)

Foltz, Mark A.; Srivastava, Anuj; Miller, Michael I.; Grenander, Ulf

1995-08-01

Previously we presented a jump-diffusion based random sampling algorithm for generating conditional mean estimates of scene representations for the tracking and recongition of maneuvering airborne targets. These representations include target positions and orientations along their trajectories and the target type associated with each trajectory. Taking a Bayesian approach, a posterior measure is defined on the parameter space by combining sensor models with a sophisticated prior based on nonlinear airplane dynamics. The jump-diffusion algorithm constructs a Markov process which visits the elements of the parameter space with frequencies proportional to the posterior probability. It consititutes both the infinitesimal, local search via a sample path continuous diffusion transform and the larger, global steps through discrete jump moves. The jump moves involve the addition and deletion of elements from the scene configuration or changes in the target type assoviated with each target trajectory. One such move results in target detection by the addition of a track seed to the inference set. This provides initial track data for the tracking/recognition algorithm to estimate linear graph structures representing tracks using the other jump moves and the diffusion process, as described in our earlier work. Target detection ideally involves a continuous research over a continuum of the observation space. In this work we conclude that for practical implemenations the search space must be discretized with lattice granularity comparable to sensor resolution, and discuss how fast Fourier transforms are utilized for efficient calcuation of sufficient statistics given our array models. Some results are also presented from our implementation on a networked system including a massively parallel machine architecture and a silicon graphics onyx workstation.

Method for detecting surface motions and mapping small terrestrial or planetary surface deformations with synthetic aperture radar

NASA Technical Reports Server (NTRS)

Gabriel, Andrew K. (Inventor); Goldstein, Richard M. (Inventor); Zebker, Howard A. (Inventor)

1990-01-01

A technique based on synthetic aperture radar (SAR) interferometry is used to measure very small (1 cm or less) surface deformations with good resolution (10 m) over large areas (50 km). It can be used for accurate measurements of many geophysical phenomena, including swelling and buckling in fault zones, residual, vertical and lateral displacements from seismic events, and prevolcanic swelling. Two SAR images are made of a scene by two spaced antennas and a difference interferogram of the scene is made. After unwrapping phases of pixels of the difference interferogram, surface motion or deformation changes of the surface are observed. A second interferogram of the same scene is made from a different pair of images, at least one of which is made after some elapsed time. The second interferogram is then compared with the first interferogram to detect changes in line of sight position of pixels. By resolving line of sight observations into their vector components in other sets of interferograms along at least one other direction, lateral motions may be recovered in their entirety. Since in general, the SAR images are made from flight tracks that are separated, it is not possible to distinguish surface changes from the parallax caused by topography. However, a third image may be used to remove the topography and leave only the surface changes.

Comparison of algorithms for blood stain detection applied to forensic hyperspectral imagery

NASA Astrophysics Data System (ADS)

Yang, Jie; Messinger, David W.; Mathew, Jobin J.; Dube, Roger R.

2016-05-01

Blood stains are among the most important types of evidence for forensic investigation. They contain valuable DNA information, and the pattern of the stains can suggest specifics about the nature of the violence that transpired at the scene. Early detection of blood stains is particularly important since the blood reacts physically and chemically with air and materials over time. Accurate identification of blood remnants, including regions that might have been intentionally cleaned, is an important aspect of forensic investigation. Hyperspectral imaging might be a potential method to detect blood stains because it is non-contact and provides substantial spectral information that can be used to identify regions in a scene with trace amounts of blood. The potential complexity of scenes in which such vast violence occurs can be high when the range of scene material types and conditions containing blood stains at a crime scene are considered. Some stains are hard to detect by the unaided eye, especially if a conscious effort to clean the scene has occurred (we refer to these as "latent" blood stains). In this paper we present the initial results of a study of the use of hyperspectral imaging algorithms for blood detection in complex scenes. We describe a hyperspectral imaging system which generates images covering 400 nm - 700 nm visible range with a spectral resolution of 10 nm. Three image sets of 31 wavelength bands were generated using this camera for a simulated indoor crime scene in which blood stains were placed on a T-shirt and walls. To detect blood stains in the scene, Principal Component Analysis (PCA), Subspace Reed Xiaoli Detection (SRXD), and Topological Anomaly Detection (TAD) algorithms were used. Comparison of the three hyperspectral image analysis techniques shows that TAD is most suitable for detecting blood stains and discovering latent blood stains.

A Motion Detection Algorithm Using Local Phase Information

PubMed Central

Lazar, Aurel A.; Ukani, Nikul H.; Zhou, Yiyin

2016-01-01

Previous research demonstrated that global phase alone can be used to faithfully represent visual scenes. Here we provide a reconstruction algorithm by using only local phase information. We also demonstrate that local phase alone can be effectively used to detect local motion. The local phase-based motion detector is akin to models employed to detect motion in biological vision, for example, the Reichardt detector. The local phase-based motion detection algorithm introduced here consists of two building blocks. The first building block measures/evaluates the temporal change of the local phase. The temporal derivative of the local phase is shown to exhibit the structure of a second order Volterra kernel with two normalized inputs. We provide an efficient, FFT-based algorithm for implementing the change of the local phase. The second processing building block implements the detector; it compares the maximum of the Radon transform of the local phase derivative with a chosen threshold. We demonstrate examples of applying the local phase-based motion detection algorithm on several video sequences. We also show how the locally detected motion can be used for segmenting moving objects in video scenes and compare our local phase-based algorithm to segmentation achieved with a widely used optic flow algorithm. PMID:26880882

An application of cluster detection to scene analysis

NASA Technical Reports Server (NTRS)

Rosenfeld, A. H.; Lee, Y. H.

1971-01-01

Certain arrangements of local features in a scene tend to group together and to be seen as units. It is suggested that in some instances, this phenomenon might be interpretable as a process of cluster detection in a graph-structured space derived from the scene. This idea is illustrated using a class of scenes that contain only horizontal and vertical line segments.

The scene and the unseen: manipulating photographs for experiments on change blindness and scene memory: image manipulation for change blindness.

PubMed

Ball, Felix; Elzemann, Anne; Busch, Niko A

2014-09-01

The change blindness paradigm, in which participants often fail to notice substantial changes in a scene, is a popular tool for studying scene perception, visual memory, and the link between awareness and attention. Some of the most striking and popular examples of change blindness have been demonstrated with digital photographs of natural scenes; in most studies, however, much simpler displays, such as abstract stimuli or "free-floating" objects, are typically used. Although simple displays have undeniable advantages, natural scenes remain a very useful and attractive stimulus for change blindness research. To assist researchers interested in using natural-scene stimuli in change blindness experiments, we provide here a step-by-step tutorial on how to produce changes in natural-scene images with a freely available image-processing tool (GIMP). We explain how changes in a scene can be made by deleting objects or relocating them within the scene or by changing the color of an object, in just a few simple steps. We also explain how the physical properties of such changes can be analyzed using GIMP and MATLAB (a high-level scientific programming tool). Finally, we present an experiment confirming that scenes manipulated according to our guidelines are effective in inducing change blindness and demonstrating the relationship between change blindness and the physical properties of the change and inter-individual differences in performance measures. We expect that this tutorial will be useful for researchers interested in studying the mechanisms of change blindness, attention, or visual memory using natural scenes.

Biased normalized cuts for target detection in hyperspectral imagery

NASA Astrophysics Data System (ADS)

Zhang, Xuewen; Dorado-Munoz, Leidy P.; Messinger, David W.; Cahill, Nathan D.

2016-05-01

The Biased Normalized Cuts (BNC) algorithm is a useful technique for detecting targets or objects in RGB imagery. In this paper, we propose modifying BNC for the purpose of target detection in hyperspectral imagery. As opposed to other target detection algorithms that typically encode target information prior to dimensionality reduction, our proposed algorithm encodes target information after dimensionality reduction, enabling a user to detect different targets in interactive mode. To assess the proposed BNC algorithm, we utilize hyperspectral imagery (HSI) from the SHARE 2012 data campaign, and we explore the relationship between the number and the position of expert-provided target labels and the precision/recall of the remaining targets in the scene.

Inventory of forest and rangeland and detection of forest stress. [Manitou, Colorado, Atlanta, Georgia, and Black Hills test sites

NASA Technical Reports Server (NTRS)

Heller, R. C.; Aldrich, R. C.; Weber, F. P.; Driscoll, R. S. (Principal Investigator)

1973-01-01

The author has identified the following significant results. Eucalyptus tree stands killed by low temperatures in December 1972 were outlined by image enhancement of two separate dates of ERTS-1 images (January 22, 1973-I.D. 1183-18175 and April 22, 1973-I.D. 1273-18183). Three stands larger than 500 meters in size were detected very accurately. In Colorado, range and grassland communities were analyzed by visual interpretation of color composite scene I.D. 1028-17135. It was found that mixtures of plant litter, amount and kind of bare soil, and plant foliage cover made classification of grasslands very difficult. Changes in forest land use were detected on areas as small as 5 acres when ERTS-1 color composite scene 1264-15445 (April 13, 1973) was compared with 1966 ASCS index mosaics (scale 1:60,000). Verification of the changes were made from RB-57 underflight CIR transparencies (scale 1:120,000).

Manhole Cover Detection Using Vehicle-Based Multi-Sensor Data

NASA Astrophysics Data System (ADS)

Ji, S.; Shi, Y.; Shi, Z.

2012-07-01

A new method combined wit multi-view matching and feature extraction technique is developed to detect manhole covers on the streets using close-range images combined with GPS/IMU and LINDAR data. The covers are an important target on the road traffic as same as transport signs, traffic lights and zebra crossing but with more unified shapes. However, the different shoot angle and distance, ground material, complex street scene especially its shadow, and cars in the road have a great impact on the cover detection rate. The paper introduces a new method in edge detection and feature extraction in order to overcome these difficulties and greatly improve the detection rate. The LIDAR data are used to do scene segmentation and the street scene and cars are excluded from the roads. And edge detection method base on canny which sensitive to arcs and ellipses is applied on the segmented road scene and the interesting areas contain arcs are extracted and fitted to ellipse. The ellipse are then resampled for invariance to shooting angle and distance and then are matched to adjacent images for further checking if covers and . More than 1000 images with different scenes are used in our tests and the detection rate is analyzed. The results verified our method have its advantages in correct covers detection in the complex street scene.

Analysis of the procedures used to evaluate suicide crime scenes in Brazil: a statistical approach to interpret reports.

PubMed

Bruni, Aline Thaís; Velho, Jesus Antonio; Ferreira, Arthur Serra Lopes; Tasso, Maria Júlia; Ferrari, Raíssa Santos; Yoshida, Ricardo Luís; Dias, Marcos Salvador; Leite, Vitor Barbanti Pereira

2014-08-01

This study uses statistical techniques to evaluate reports on suicide scenes; it utilizes 80 reports from different locations in Brazil, randomly collected from both federal and state jurisdictions. We aimed to assess a heterogeneous group of cases in order to obtain an overall perspective of the problem. We evaluated variables regarding the characteristics of the crime scene, such as the detected traces (blood, instruments and clothes) that were found and we addressed the methodology employed by the experts. A qualitative approach using basic statistics revealed a wide distribution as to how the issue was addressed in the documents. We examined a quantitative approach involving an empirical equation and we used multivariate procedures to validate the quantitative methodology proposed for this empirical equation. The methodology successfully identified the main differences in the information presented in the reports, showing that there is no standardized method of analyzing evidences. Copyright © 2014 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.

Heterogeneity Measurement Based on Distance Measure for Polarimetric SAR Data

NASA Astrophysics Data System (ADS)

Xing, Xiaoli; Chen, Qihao; Liu, Xiuguo

2018-04-01

To effectively test the scene heterogeneity for polarimetric synthetic aperture radar (PolSAR) data, in this paper, the distance measure is introduced by utilizing the similarity between the sample and pixels. Moreover, given the influence of the distribution and modeling texture, the K distance measure is deduced according to the Wishart distance measure. Specifically, the average of the pixels in the local window replaces the class center coherency or covariance matrix. The Wishart and K distance measure are calculated between the average matrix and the pixels. Then, the ratio of the standard deviation to the mean is established for the Wishart and K distance measure, and the two features are defined and applied to reflect the complexity of the scene. The proposed heterogeneity measure is proceeded by integrating the two features using the Pauli basis. The experiments conducted on the single-look and multilook PolSAR data demonstrate the effectiveness of the proposed method for the detection of the scene heterogeneity.

Profiling the scent of weathered training aids for blood-detection dogs.

PubMed

Chilcote, Baree; Rust, LaTara; Nizio, Katie D; Forbes, Shari L

2018-03-01

At outdoor crime scenes, cadaver-detection and blood-detection dogs may be tasked with locating blood that is days, weeks or months old. Although it is known that the odour profile of blood will change during this time, it is currently unknown how the profile changes when exposed to the environment. Such variables must be studied in order to understand when the odour profile is no longer detectable by the scent-detection dogs and other crime scene tools should be implemented. In this study, blood was deposited onto concrete and varnished wood surfaces and weathered in an outdoor environment over a three-month period. Headspace samples were collected using solid phase microextraction (SPME) and analysed using comprehensive two-dimensional gas chromatography - time-of-flight mass spectrometry (GC×GC-TOFMS). The chemical odour profiles were compared with the behavioural responses of cadaver-detection and blood-detection dogs during training. Data interpretation using principal component analysis (PCA) and hierarchical cluster analysis (HCA) established that the blood odour could no longer be detected using SPME-GC×GC-TOFMS after two months of weathering on both surfaces. Conversely, the blood-detection dogs had difficulty locating the blood samples after one month of weathering on concrete and after one week of weathering on varnished wood. The scent-detection dogs evaluated herein had not been previously exposed to environmentally weathered blood samples during training. Given that this study was conducted to test the dogs' baseline abilities, it is expected that with repeated exposure, the dogs' capabilities would likely improve. The knowledge gained from this study can assist in providing law enforcement with more accurate training aids for blood-detection dogs and can improve their efficiency when deployed to outdoor crime scenes. Copyright © 2017 The Chartered Society of Forensic Sciences. Published by Elsevier B.V. All rights reserved.

Robust Curb Detection with Fusion of 3D-Lidar and Camera Data

PubMed Central

Tan, Jun; Li, Jian; An, Xiangjing; He, Hangen

2014-01-01

Curb detection is an essential component of Autonomous Land Vehicles (ALV), especially important for safe driving in urban environments. In this paper, we propose a fusion-based curb detection method through exploiting 3D-Lidar and camera data. More specifically, we first fuse the sparse 3D-Lidar points and high-resolution camera images together to recover a dense depth image of the captured scene. Based on the recovered dense depth image, we propose a filter-based method to estimate the normal direction within the image. Then, by using the multi-scale normal patterns based on the curb's geometric property, curb point features fitting the patterns are detected in the normal image row by row. After that, we construct a Markov Chain to model the consistency of curb points which utilizes the continuous property of the curb, and thus the optimal curb path which links the curb points together can be efficiently estimated by dynamic programming. Finally, we perform post-processing operations to filter the outliers, parameterize the curbs and give the confidence scores on the detected curbs. Extensive evaluations clearly show that our proposed method can detect curbs with strong robustness at real-time speed for both static and dynamic scenes. PMID:24854364

An Automated Directed Spectral Search Methodology for Small Target Detection

NASA Astrophysics Data System (ADS)

Grossman, Stanley I.

Much of the current efforts in remote sensing tackle macro-level problems such as determining the extent of wheat in a field, the general health of vegetation or the extent of mineral deposits in an area. However, for many of the remaining remote sensing challenges being studied currently, such as border protection, drug smuggling, treaty verification, and the war on terror, most targets are very small in nature - a vehicle or even a person. While in typical macro-level problems the objective vegetation is in the scene, for small target detection problems it is not usually known if the desired small target even exists in the scene, never mind finding it in abundance. The ability to find specific small targets, such as vehicles, typifies this problem. Complicating the analyst's life, the growing number of available sensors is generating mountains of imagery outstripping the analysts' ability to visually peruse them. This work presents the important factors influencing spectral exploitation using multispectral data and suggests a different approach to small target detection. The methodology of directed search is presented, including the use of scene-modeled spectral libraries, various search algorithms, and traditional statistical and ROC curve analysis. The work suggests a new metric to calibrate analysis labeled the analytic sweet spot as well as an estimation method for identifying the sweet spot threshold for an image. It also suggests a new visualization aid for highlighting the target in its entirety called nearest neighbor inflation (NNI). It brings these all together to propose that these additions to the target detection arena allow for the construction of a fully automated target detection scheme. This dissertation next details experiments to support the hypothesis that the optimum detection threshold is the analytic sweet spot and that the estimation method adequately predicts it. Experimental results and analysis are presented for the proposed directed search techniques of spectral image based small target detection. It offers evidence of the functionality of the NNI visualization and also provides evidence that the increased spectral dimensionality of the 8-band Worldview-2 datasets provides noteworthy improvement in results over traditional 4-band multispectral datasets. The final experiment presents the results from a prototype fully automated target detection scheme in support of the overarching premise. This work establishes the analytic sweet spot as the optimum threshold defined as the point where error detection rate curves -- false detections vs. missing detections -- cross. At this point the errors are minimized while the detection rate is maximized. It then demonstrates that taking the first moment statistic of the histogram of calculated target detection values from a detection search with test threshold set arbitrarily high will estimate the analytic sweet spot for that image. It also demonstrates that directed search techniques -- when utilized with appropriate scene-specific modeled signatures and atmospheric compensations -- perform at least as well as in-scene search techniques 88% of the time and grossly under-performing only 11% of the time; the in-scene only performs as well or better 50% of the time. It further demonstrates the clear advantage increased multispectral dimensionality brings to detection searches improving performance in 50% of the cases while performing at least as well 72% of the time. Lastly, it presents evidence that a fully automated prototype performs as anticipated laying the groundwork for further research into fully automated processes for small target detection.

Face, Body, and Center of Gravity Mediate Person Detection in Natural Scenes

ERIC Educational Resources Information Center

Bindemann, Markus; Scheepers, Christoph; Ferguson, Heather J.; Burton, A. Mike

2010-01-01

Person detection is an important prerequisite of social interaction, but is not well understood. Following suggestions that people in the visual field can capture a viewer's attention, this study examines the role of the face and the body for person detection in natural scenes. We observed that viewers tend first to look at the center of a scene,…

A view not to be missed: Salient scene content interferes with cognitive restoration

PubMed Central

Van der Jagt, Alexander P. N.; Craig, Tony; Brewer, Mark J.; Pearson, David G.

2017-01-01

Attention Restoration Theory (ART) states that built scenes place greater load on attentional resources than natural scenes. This is explained in terms of "hard" and "soft" fascination of built and natural scenes. Given a lack of direct empirical evidence for this assumption we propose that perceptual saliency of scene content can function as an empirically derived indicator of fascination. Saliency levels were established by measuring speed of scene category detection using a Go/No-Go detection paradigm. Experiment 1 shows that built scenes are more salient than natural scenes. Experiment 2 replicates these findings using greyscale images, ruling out a colour-based response strategy, and additionally shows that built objects in natural scenes affect saliency to a greater extent than the reverse. Experiment 3 demonstrates that the saliency of scene content is directly linked to cognitive restoration using an established restoration paradigm. Overall, these findings demonstrate an important link between the saliency of scene content and related cognitive restoration. PMID:28723975

A view not to be missed: Salient scene content interferes with cognitive restoration.

PubMed

Van der Jagt, Alexander P N; Craig, Tony; Brewer, Mark J; Pearson, David G

2017-01-01

Attention Restoration Theory (ART) states that built scenes place greater load on attentional resources than natural scenes. This is explained in terms of "hard" and "soft" fascination of built and natural scenes. Given a lack of direct empirical evidence for this assumption we propose that perceptual saliency of scene content can function as an empirically derived indicator of fascination. Saliency levels were established by measuring speed of scene category detection using a Go/No-Go detection paradigm. Experiment 1 shows that built scenes are more salient than natural scenes. Experiment 2 replicates these findings using greyscale images, ruling out a colour-based response strategy, and additionally shows that built objects in natural scenes affect saliency to a greater extent than the reverse. Experiment 3 demonstrates that the saliency of scene content is directly linked to cognitive restoration using an established restoration paradigm. Overall, these findings demonstrate an important link between the saliency of scene content and related cognitive restoration.

Shape-based human detection for threat assessment

NASA Astrophysics Data System (ADS)

Lee, Dah-Jye; Zhan, Pengcheng; Thomas, Aaron; Schoenberger, Robert B.

2004-07-01

Detection of intrusions for early threat assessment requires the capability of distinguishing whether the intrusion is a human, an animal, or other objects. Most low-cost security systems use simple electronic motion detection sensors to monitor motion or the location of objects within the perimeter. Although cost effective, these systems suffer from high rates of false alarm, especially when monitoring open environments. Any moving objects including animals can falsely trigger the security system. Other security systems that utilize video equipment require human interpretation of the scene in order to make real-time threat assessment. Shape-based human detection technique has been developed for accurate early threat assessments for open and remote environment. Potential threats are isolated from the static background scene using differential motion analysis and contours of the intruding objects are extracted for shape analysis. Contour points are simplified by removing redundant points connecting short and straight line segments and preserving only those with shape significance. Contours are represented in tangent space for comparison with shapes stored in database. Power cepstrum technique has been developed to search for the best matched contour in database and to distinguish a human from other objects from different viewing angles and distances.

Development of Yellow Sand Image Products Using Infrared Brightness Temperature Difference Method

NASA Astrophysics Data System (ADS)

Ha, J.; Kim, J.; Kwak, M.; Ha, K.

2007-12-01

A technique for detection of airborne yellow sand dust using meteorological satellite has been developed from various bands from ultraviolet to infrared channels. Among them, Infrared (IR) channels have an advantage of detecting aerosols over high reflecting surface as well as during nighttime. There had been suggestion of using brightness temperature difference (BTD) between 11 and 12¥ìm. We have found that the technique is highly depends on surface temperature, emissivity, and zenith angle, which results in changing the threshold of BTD. In order to overcome these problems, we have constructed the background brightness temperature threshold of BTD and then aerosol index (AI) has been determined from subtracting the background threshold from BTD of our interested scene. Along with this, we utilized high temporal coverage of geostationary satellite, MTSAT, to improve the reliability of the determined AI signal. The products have been evaluated by comparing the forecasted wind field with the movement fiend of AI. The statistical score test illustrates that this newly developed algorithm produces a promising result for detecting mineral dust by reducing the errors with respect to the current BTD method.

Human Relations Procedures Relevant to University Environmental Change.

ERIC Educational Resources Information Center

American Personnel and Guidance Association, Washington, DC.

The present college scene is in a state of flux and confusion. Several problems are receiving major priority: (1) student stress, (2) alienation of students, and (3) activism among students. Reasons for the above problems could include: (1) individual and inter-group stress, and (2) tension between groups. Procedures which have been utilized on…

Exploring inter-frame correlation analysis and wavelet-domain modeling for real-time caption detection in streaming video

NASA Astrophysics Data System (ADS)

Li, Jia; Tian, Yonghong; Gao, Wen

2008-01-01

In recent years, the amount of streaming video has grown rapidly on the Web. Often, retrieving these streaming videos offers the challenge of indexing and analyzing the media in real time because the streams must be treated as effectively infinite in length, thus precluding offline processing. Generally speaking, captions are important semantic clues for video indexing and retrieval. However, existing caption detection methods often have difficulties to make real-time detection for streaming video, and few of them concern on the differentiation of captions from scene texts and scrolling texts. In general, these texts have different roles in streaming video retrieval. To overcome these difficulties, this paper proposes a novel approach which explores the inter-frame correlation analysis and wavelet-domain modeling for real-time caption detection in streaming video. In our approach, the inter-frame correlation information is used to distinguish caption texts from scene texts and scrolling texts. Moreover, wavelet-domain Generalized Gaussian Models (GGMs) are utilized to automatically remove non-text regions from each frame and only keep caption regions for further processing. Experiment results show that our approach is able to offer real-time caption detection with high recall and low false alarm rate, and also can effectively discern caption texts from the other texts even in low resolutions.

The trait of sensory processing sensitivity and neural responses to changes in visual scenes

PubMed Central

Xu, Xiaomeng; Aron, Arthur; Aron, Elaine; Cao, Guikang; Feng, Tingyong; Weng, Xuchu

2011-01-01

This exploratory study examined the extent to which individual differences in sensory processing sensitivity (SPS), a temperament/personality trait characterized by social, emotional and physical sensitivity, are associated with neural response in visual areas in response to subtle changes in visual scenes. Sixteen participants completed the Highly Sensitive Person questionnaire, a standard measure of SPS. Subsequently, they were tested on a change detection task while undergoing functional magnetic resonance imaging (fMRI). SPS was associated with significantly greater activation in brain areas involved in high-order visual processing (i.e. right claustrum, left occipitotemporal, bilateral temporal and medial and posterior parietal regions) as well as in the right cerebellum, when detecting minor (vs major) changes in stimuli. These findings remained strong and significant after controlling for neuroticism and introversion, traits that are often correlated with SPS. These results provide the first evidence of neural differences associated with SPS, the first direct support for the sensory aspect of this trait that has been studied primarily for its social and affective implications, and preliminary evidence for heightened sensory processing in individuals high in SPS. PMID:20203139

Modeling human pilot cue utilization with applications to simulator fidelity assessment.

PubMed

Zeyada, Y; Hess, R A

2000-01-01

An analytical investigation to model the manner in which pilots perceive and utilize visual, proprioceptive, and vestibular cues in a ground-based flight simulator was undertaken. Data from a NASA Ames Research Center vertical motion simulator study of a simple, single-degree-of-freedom rotorcraft bob-up/down maneuver were employed in the investigation. The study was part of a larger research effort that has the creation of a methodology for determining flight simulator fidelity requirements as its ultimate goal. The study utilized a closed-loop feedback structure of the pilot/simulator system that included the pilot, the cockpit inceptor, the dynamics of the simulated vehicle, and the motion system. With the exception of time delays that accrued in visual scene production in the simulator, visual scene effects were not included in this study. Pilot/vehicle analysis and fuzzy-inference identification were employed to study the changes in fidelity that occurred as the characteristics of the motion system were varied over five configurations. The data from three of the five pilots who participated in the experimental study were analyzed in the fuzzy-inference identification. Results indicate that both the analytical pilot/vehicle analysis and the fuzzy-inference identification can be used to identify changes in simulator fidelity for the task examined.

Short-term change detection for UAV video

NASA Astrophysics Data System (ADS)

Saur, Günter; Krüger, Wolfgang

2012-11-01

In the last years, there has been an increased use of unmanned aerial vehicles (UAV) for video reconnaissance and surveillance. An important application in this context is change detection in UAV video data. Here we address short-term change detection, in which the time between observations ranges from several minutes to a few hours. We distinguish this task from video motion detection (shorter time scale) and from long-term change detection, based on time series of still images taken between several days, weeks, or even years. Examples for relevant changes we are looking for are recently parked or moved vehicles. As a pre-requisite, a precise image-to-image registration is needed. Images are selected on the basis of the geo-coordinates of the sensor's footprint and with respect to a certain minimal overlap. The automatic imagebased fine-registration adjusts the image pair to a common geometry by using a robust matching approach to handle outliers. The change detection algorithm has to distinguish between relevant and non-relevant changes. Examples for non-relevant changes are stereo disparity at 3D structures of the scene, changed length of shadows, and compression or transmission artifacts. To detect changes in image pairs we analyzed image differencing, local image correlation, and a transformation-based approach (multivariate alteration detection). As input we used color and gradient magnitude images. To cope with local misalignment of image structures we extended the approaches by a local neighborhood search. The algorithms are applied to several examples covering both urban and rural scenes. The local neighborhood search in combination with intensity and gradient magnitude differencing clearly improved the results. Extended image differencing performed better than both the correlation based approach and the multivariate alternation detection. The algorithms are adapted to be used in semi-automatic workflows for the ABUL video exploitation system of Fraunhofer IOSB, see Heinze et. al. 2010.1 In a further step we plan to incorporate more information from the video sequences to the change detection input images, e.g., by image enhancement or by along-track stereo which are available in the ABUL system.

The Q Continuum: Encounter with the Cloud Mask

NASA Astrophysics Data System (ADS)

Ackerman, S. A.; Frey, R.; Holz, R.; Philips, C.; Dutcher, S.

2017-12-01

We are developing a common cloud mask for MODIS and VIIRS observations, referred to as the MODIS VIIRS Continuity Mask (MVCM). Our focus is on extending the MODIS-heritage cloud detection approach in order to generate appropriate climate data records for clouds and climate studies. The MVCM is based on heritage from the MODIS cloud mask (MOD35 and MYD35) and employs a series of tests on MODIS reflectances and brightness temperatures. Cloud detection is based on contrasts (i.e., cloud versus background surface) at pixel resolution. The MVCM follows the same approach. These cloud masks use multiple cloud detection tests to indicate the confidence level that the observation is of a clear-sky scene. The outcome of a test ranges from 0 (cloudy) to 1 (clear-sky scene). Because of overlap in the sensitivities of the various spectral tests to the type of cloud, each test is considered in one of several groups. The final cloud mask is determined from the product of the minimum confidence of each group and is referred to as the Q value as defined in Ackerman et al (1998). In MOD35 and MYD35 processing, the Q value is not output, rather predetermined Q values determine the result: If Q ≥ .99 the scene is clear; .95 ≤ Q < .99 the pixel is probably a clear scene, .66 ≤ Q < .95 is probably cloudy and Q < .66 is cloudy. Thus representing Q discretely and not as a continuum. For the MVCM, the numerical value of the Q is output along with the classification of clear, probably clear, probably cloudy, and cloudy. Through comparisons with collocated CALIOP and MODIS observations, we will assess the categorization of the Q values as a function of scene type ). While validation studies have indicated the utility and statistical correctness of the cloud mask approach, the algorithm does not possess immeasurable power and perfection. This comparison will assess the time and space dependence of Q and assure that the laws of physics are followed, at least according to normal human notions. Using CALIOP as representing truth, a receiver operating characteristic curve (ROC) will be analyzed to determine the optimum Q for various scenes and seasons, thus providing a continuum of discriminating thresholds.

Measurements of scene spectral radiance variability

NASA Astrophysics Data System (ADS)

Seeley, Juliette A.; Wack, Edward C.; Mooney, Daniel L.; Muldoon, Michael; Shey, Shen; Upham, Carolyn A.; Harvey, John M.; Czerwinski, Richard N.; Jordan, Michael P.; Vallières, Alexandre; Chamberland, Martin

2006-05-01

Detection performance of LWIR passive standoff chemical agent sensors is strongly influenced by various scene parameters, such as atmospheric conditions, temperature contrast, concentration-path length product (CL), agent absorption coefficient, and scene spectral variability. Although temperature contrast, CL, and agent absorption coefficient affect the detected signal in a predictable manner, fluctuations in background scene spectral radiance have less intuitive consequences. The spectral nature of the scene is not problematic in and of itself; instead it is spatial and temporal fluctuations in the scene spectral radiance that cannot be entirely corrected for with data processing. In addition, the consequence of such variability is a function of the spectral signature of the agent that is being detected and is thus different for each agent. To bracket the performance of background-limited (low sensor NEDN), passive standoff chemical sensors in the range of relevant conditions, assessment of real scene data is necessary1. Currently, such data is not widely available2. To begin to span the range of relevant scene conditions, we have acquired high fidelity scene spectral radiance measurements with a Telops FTIR imaging spectrometer 3. We have acquired data in a variety of indoor and outdoor locations at different times of day and year. Some locations include indoor office environments, airports, urban and suburban scenes, waterways, and forest. We report agent-dependent clutter measurements for three of these backgrounds.

Urban Growth Detection Using Filtered Landsat Dense Time Trajectory in an Arid City

NASA Astrophysics Data System (ADS)

Ye, Z.; Schneider, A.

2014-12-01

Among all remote sensing environment monitoring techniques, time series analysis of biophysical index is drawing increasing attention. Although many of them studied forest disturbance and land cover change detection, few focused on urban growth mapping at medium spatial resolution. As Landsat archive becomes open accessible, methods using Landsat time-series imagery to detect urban growth is possible. It is found that a time trajectory from a newly developed urban area shows a dramatic drop of vegetation index. This enable the utilization of time trajectory analysis to distinguish impervious surface and crop land that has a different temporal biophysical pattern. Also, the time of change can be estimated, yet many challenges remain. Landsat data has lower temporal resolution, which may be worse when cloud-contaminated pixels and SLC-off effect exist. It is difficult to tease apart intra-annual, inter-annual, and land cover difference in a time series. Here, several methods of time trajectory analysis are utilized and compared to find a computationally efficient and accurate way on urban growth detection. A case study city, Ankara, Turkey is chosen for its arid climate and various landscape distributions. For preliminary research, Landsat TM and ETM+ scenes from 1998 to 2002 are chosen. NDVI, EVI, and SAVI are selected as research biophysical indices. The procedure starts with a seasonality filtering. Only areas with seasonality need to be filtered so as to decompose seasonality and extract overall trend. Harmonic transform, wavelet transform, and a pre-defined bell shape filter are used to estimate the overall trend in the time trajectory for each pixel. The point with significant drop in the trajectory is tagged as change point. After an urban change is detected, forward and backward checking is undertaken to make sure it is really new urban expansion other than short time crop fallow or forest disturbance. The method proposed here can capture most of the urban growth during research time period, although the accuracy of time point determination is a bit lower than this. Results from several biophysical indices and filtering methods are similar. Some fallows and bare lands in arid area are easily confused with urban impervious surface.

Optimizing Radiometric Fidelity to Enhance Aerial Image Change Detection Utilizing Digital Single Lens Reflex (DSLR) Cameras

NASA Astrophysics Data System (ADS)

Kerr, Andrew D.

Determining optimal imaging settings and best practices related to the capture of aerial imagery using consumer-grade digital single lens reflex (DSLR) cameras, should enable remote sensing scientists to generate consistent, high quality, and low cost image data sets. Radiometric optimization, image fidelity, image capture consistency and repeatability were evaluated in the context of detailed image-based change detection. The impetus for this research is in part, a dearth of relevant, contemporary literature, on the utilization of consumer grade DSLR cameras for remote sensing, and the best practices associated with their use. The main radiometric control settings on a DSLR camera, EV (Exposure Value), WB (White Balance), light metering, ISO, and aperture (f-stop), are variables that were altered and controlled over the course of several image capture missions. These variables were compared for their effects on dynamic range, intra-frame brightness variation, visual acuity, temporal consistency, and the detectability of simulated cracks placed in the images. This testing was conducted from a terrestrial, rather than an airborne collection platform, due to the large number of images per collection, and the desire to minimize inter-image misregistration. The results point to a range of slightly underexposed image exposure values as preferable for change detection and noise minimization fidelity. The makeup of the scene, the sensor, and aerial platform, influence the selection of the aperture and shutter speed which along with other variables, allow for estimation of the apparent image motion (AIM) motion blur in the resulting images. The importance of the image edges in the image application, will in part dictate the lowest usable f-stop, and allow the user to select a more optimal shutter speed and ISO. The single most important camera capture variable is exposure bias (EV), with a full dynamic range, wide distribution of DN values, and high visual contrast and acuity occurring around -0.7 to -0.3EV exposure bias. The ideal values for sensor gain, was found to be ISO 100, with ISO 200 a less desirable. This study offers researchers a better understanding of the effects of camera capture settings on RSI pairs and their influence on image-based change detection.

Cloud Top Scanning radiometer (CTS): User's guide

NASA Technical Reports Server (NTRS)

Brown, K. S.

1981-01-01

The CTS maps the Earth's surface with a resolution of 0.1 km from an altitude of 18km with 60km side-to-side coverage of the field. It has three spectral channels. The 0.625 micrometer centered visual channel detects reflectance to within 1 percent. The 6.75 micrometer centered water vapor channel detects changes in temperature of less than one degree Kelvin at 175 K. The 11.5 micrometer centered infrared window channel detects changes of less one half degree Kelvin at 175 K. The data can be converted graphically into three display images of the scene. Values for scene temperature and albedo are calculated from calibration equations. The equations were derived from in-situ and laboratory measurements. Intercomparisons of the flight data temperatures with ground based and other remote sensor results established the certainty of the derived temperature values to within 3 K over a wide temperature range (180 to 320 K). The system performance, calibration, and operation is successful and the engineering information describing this system should prove useful to scientists and potential users of the data.

SCEGRAM: An image database for semantic and syntactic inconsistencies in scenes.

PubMed

Öhlschläger, Sabine; Võ, Melissa Le-Hoa

2017-10-01

Our visual environment is not random, but follows compositional rules according to what objects are usually found where. Despite the growing interest in how such semantic and syntactic rules - a scene grammar - enable effective attentional guidance and object perception, no common image database containing highly-controlled object-scene modifications has been publically available. Such a database is essential in minimizing the risk that low-level features drive high-level effects of interest, which is being discussed as possible source of controversial study results. To generate the first database of this kind - SCEGRAM - we took photographs of 62 real-world indoor scenes in six consistency conditions that contain semantic and syntactic (both mild and extreme) violations as well as their combinations. Importantly, always two scenes were paired, so that an object was semantically consistent in one scene (e.g., ketchup in kitchen) and inconsistent in the other (e.g., ketchup in bathroom). Low-level salience did not differ between object-scene conditions and was generally moderate. Additionally, SCEGRAM contains consistency ratings for every object-scene condition, as well as object-absent scenes and object-only images. Finally, a cross-validation using eye-movements replicated previous results of longer dwell times for both semantic and syntactic inconsistencies compared to consistent controls. In sum, the SCEGRAM image database is the first to contain well-controlled semantic and syntactic object-scene inconsistencies that can be used in a broad range of cognitive paradigms (e.g., verbal and pictorial priming, change detection, object identification, etc.) including paradigms addressing developmental aspects of scene grammar. SCEGRAM can be retrieved for research purposes from http://www.scenegrammarlab.com/research/scegram-database/ .

Hardware accelerator design for change detection in smart camera

NASA Astrophysics Data System (ADS)

Singh, Sanjay; Dunga, Srinivasa Murali; Saini, Ravi; Mandal, A. S.; Shekhar, Chandra; Chaudhury, Santanu; Vohra, Anil

2011-10-01

Smart Cameras are important components in Human Computer Interaction. In any remote surveillance scenario, smart cameras have to take intelligent decisions to select frames of significant changes to minimize communication and processing overhead. Among many of the algorithms for change detection, one based on clustering based scheme was proposed for smart camera systems. However, such an algorithm could achieve low frame rate far from real-time requirements on a general purpose processors (like PowerPC) available on FPGAs. This paper proposes the hardware accelerator capable of detecting real time changes in a scene, which uses clustering based change detection scheme. The system is designed and simulated using VHDL and implemented on Xilinx XUP Virtex-IIPro FPGA board. Resulted frame rate is 30 frames per second for QVGA resolution in gray scale.

Developing a confidence metric for the Landsat land surface temperature product

NASA Astrophysics Data System (ADS)

Laraby, Kelly G.; Schott, John R.; Raqueno, Nina

2016-05-01

Land Surface Temperature (LST) is an important Earth system data record that is useful to fields such as change detection, climate research, environmental monitoring, and smaller scale applications such as agriculture. Certain Earth-observing satellites can be used to derive this metric, and it would be extremely useful if such imagery could be used to develop a global product. Through the support of the National Aeronautics and Space Administration (NASA) and the United States Geological Survey (USGS), a LST product for the Landsat series of satellites has been developed. Currently, it has been validated for scenes in North America, with plans to expand to a trusted global product. For ideal atmospheric conditions (e.g. stable atmosphere with no clouds nearby), the LST product underestimates the surface temperature by an average of 0.26 K. When clouds are directly above or near the pixel of interest, however, errors can extend to several Kelvin. As the product approaches public release, our major goal is to develop a quality metric that will provide the user with a per-pixel map of estimated LST errors. There are several sources of error that are involved in the LST calculation process, but performing standard error propagation is a difficult task due to the complexity of the atmospheric propagation component. To circumvent this difficulty, we propose to utilize the relationship between cloud proximity and the error seen in the LST process to help develop a quality metric. This method involves calculating the distance to the nearest cloud from a pixel of interest in a scene, and recording the LST error at that location. Performing this calculation for hundreds of scenes allows us to observe the average LST error for different ranges of distances to the nearest cloud. This paper describes this process in full, and presents results for a large set of Landsat scenes.

Registering coherent change detection products associated with large image sets and long capture intervals

DOEpatents

Perkins, David Nikolaus; Gonzales, Antonio I

2014-04-08

A set of co-registered coherent change detection (CCD) products is produced from a set of temporally separated synthetic aperture radar (SAR) images of a target scene. A plurality of transformations are determined, which transformations are respectively for transforming a plurality of the SAR images to a predetermined image coordinate system. The transformations are used to create, from a set of CCD products produced from the set of SAR images, a corresponding set of co-registered CCD products.

The Chronic Detrimental Impact of Interruptions in a Simulated Submarine Track Management Task.

PubMed

Loft, Shayne; Sadler, Andreas; Braithwaite, Janelle; Huf, Samuel

2015-12-01

The objective of this article is to examine the extent to which interruptions negatively impact situation awareness and long-term performance in a submarine track management task where pre- and postinterruption display scenes remained essentially identical. Interruptions in command and control task environments can degrade performance well beyond the first postinterruption action typically measured for sequential static tasks, because individuals need to recover their situation awareness for multiple unfolding display events. Participants in the current study returned to an unchanged display scene following interruption and therefore could be more immune to such long-term performance deficits. The task required participants to monitor a display to detect contact heading changes and to make enemy engagement decisions. Situation awareness (Situation Present Assessment Method) and subjective workload (NASA-Task Load Index) were measured. The interruption replaced the display for 20 s with a blank screen, during which participants completed a classification task. Situation awareness after returning from interruption was degraded. Participants were slower to make correct engagement decisions and slower and less accurate in detecting heading changes, despite these task decisions being made at least 40 s following the interruption. Interruptions negatively impacted situation awareness and long-term performance because participants needed to redetermine the location and spatial relationship between the displayed contacts when returning from interruption, either because their situation awareness for the preinterruption scene decayed or because they did not encode the preinterruption scene. Interruption in work contexts such as submarines is unavoidable, and further understanding of how operators are affected is required to improve work design and training. © 2015, Human Factors and Ergonomics Society.

Canine human scent identifications with post-blast debris collected from improvised explosive devices.

PubMed

Curran, Allison M; Prada, Paola A; Furton, Kenneth G

2010-06-15

In this study it is demonstrated that human odor collected from items recovered at a post-blast scene can be evaluated using human scent specific canine teams to locate and identify individuals who have been in contact with the improvised explosive device (IED) components and/or the delivery vehicle. The purpose of the experiments presented here was to document human scent survivability in both peroxide-based explosions as well as simulated roadside IEDs utilizing double-blind field trials. Human odor was collected from post-blast device and vehicle components. Human scent specific canine teams were then deployed at the blast scene and in locations removed from the blast scene to validate that human odor remains in sufficient quantities for reliable canine detection and identification. Human scent specific canines have shown the ability to identify individuals who have been in contact with IEDs using post-blast debris with an average success from site response of 82.2% verifying that this technology has great potential in criminal, investigative, and military applications. (c) 2010 Elsevier Ireland Ltd. All rights reserved.

Change detection and change blindness in pigeons (Columba livia).

PubMed

Herbranson, Walter T; Trinh, Yvan T; Xi, Patricia M; Arand, Mark P; Barker, Michael S K; Pratt, Theodore H

2014-05-01

Change blindness is a phenomenon in which even obvious details in a visual scene change without being noticed. Although change blindness has been studied extensively in humans, we do not yet know if it is a phenomenon that also occurs in other animals. Thus, investigation of change blindness in a nonhuman species may prove to be valuable by beginning to provide some insight into its ultimate causes. Pigeons learned a change detection task in which pecks to the location of a change in a sequence of stimulus displays were reinforced. They were worse at detecting changes if the stimulus displays were separated by a brief interstimulus interval, during which the display was blank, and this primary result matches the general pattern seen in previous studies of change blindness in humans. A second experiment attempted to identify specific stimulus characteristics that most reliably produced a failure to detect changes. Change detection was more difficult when interstimulus intervals were longer and when the change was iterated fewer times. ©2014 APA, all rights reserved.

A comparison of directed search target detection versus in-scene target detection in Worldview-2 datasets

NASA Astrophysics Data System (ADS)

Grossman, S.

2015-05-01

Since the events of September 11, 2001, the intelligence focus has moved from large order-of-battle targets to small targets of opportunity. Additionally, the business community has discovered the use of remotely sensed data to anticipate demand and derive data on their competition. This requires the finer spectral and spatial fidelity now available to recognize those targets. This work hypothesizes that directed searches using calibrated data perform at least as well as inscene manually intensive target detection searches. It uses calibrated Worldview-2 multispectral images with NEF generated signatures and standard detection algorithms to compare bespoke directed search capabilities against ENVI™ in-scene search capabilities. Multiple execution runs are performed at increasing thresholds to generate detection rates. These rates are plotted and statistically analyzed. While individual head-to-head comparison results vary, 88% of the directed searches performed at least as well as in-scene searches with 50% clearly outperforming in-scene methods. The results strongly support the premise that directed searches perform at least as well as comparable in-scene searches.

The Neural Dynamics of Attentional Selection in Natural Scenes.

PubMed

Kaiser, Daniel; Oosterhof, Nikolaas N; Peelen, Marius V

2016-10-12

The human visual system can only represent a small subset of the many objects present in cluttered scenes at any given time, such that objects compete for representation. Despite these processing limitations, the detection of object categories in cluttered natural scenes is remarkably rapid. How does the brain efficiently select goal-relevant objects from cluttered scenes? In the present study, we used multivariate decoding of magneto-encephalography (MEG) data to track the neural representation of within-scene objects as a function of top-down attentional set. Participants detected categorical targets (cars or people) in natural scenes. The presence of these categories within a scene was decoded from MEG sensor patterns by training linear classifiers on differentiating cars and people in isolation and testing these classifiers on scenes containing one of the two categories. The presence of a specific category in a scene could be reliably decoded from MEG response patterns as early as 160 ms, despite substantial scene clutter and variation in the visual appearance of each category. Strikingly, we find that these early categorical representations fully depend on the match between visual input and top-down attentional set: only objects that matched the current attentional set were processed to the category level within the first 200 ms after scene onset. A sensor-space searchlight analysis revealed that this early attention bias was localized to lateral occipitotemporal cortex, reflecting top-down modulation of visual processing. These results show that attention quickly resolves competition between objects in cluttered natural scenes, allowing for the rapid neural representation of goal-relevant objects. Efficient attentional selection is crucial in many everyday situations. For example, when driving a car, we need to quickly detect obstacles, such as pedestrians crossing the street, while ignoring irrelevant objects. How can humans efficiently perform such tasks, given the multitude of objects contained in real-world scenes? Here we used multivariate decoding of magnetoencephalogaphy data to characterize the neural underpinnings of attentional selection in natural scenes with high temporal precision. We show that brain activity quickly tracks the presence of objects in scenes, but crucially only for those objects that were immediately relevant for the participant. These results provide evidence for fast and efficient attentional selection that mediates the rapid detection of goal-relevant objects in real-world environments. Copyright © 2016 the authors 0270-6474/16/3610522-07$15.00/0.

Detection of chromatic and luminance distortions in natural scenes.

PubMed

Jennings, Ben J; Wang, Karen; Menzies, Samantha; Kingdom, Frederick A A

2015-09-01

A number of studies have measured visual thresholds for detecting spatial distortions applied to images of natural scenes. In one study, Bex [J. Vis.10(2), 1 (2010)10.1167/10.2.231534-7362] measured sensitivity to sinusoidal spatial modulations of image scale. Here, we measure sensitivity to sinusoidal scale distortions applied to the chromatic, luminance, or both layers of natural scene images. We first established that sensitivity does not depend on whether the undistorted comparison image was of the same or of a different scene. Next, we found that, when the luminance but not chromatic layer was distorted, performance was the same regardless of whether the chromatic layer was present, absent, or phase-scrambled; in other words, the chromatic layer, in whatever form, did not affect sensitivity to the luminance layer distortion. However, when the chromatic layer was distorted, sensitivity was higher when the luminance layer was intact compared to when absent or phase-scrambled. These detection threshold results complement the appearance of periodic distortions of the image scale: when the luminance layer is distorted visibly, the scene appears distorted, but when the chromatic layer is distorted visibly, there is little apparent scene distortion. We conclude that (a) observers have a built-in sense of how a normal image of a natural scene should appear, and (b) the detection of distortion in, as well as the apparent distortion of, natural scene images is mediated predominantly by the luminance layer and not chromatic layer.

Did limits on payments for tobacco placements in US movies affect how movies are made?

PubMed Central

Morgenstern, Matthis; Stoolmiller, Mike; Bergamini, Elaina; Sargent, James D

2017-01-01

Objective To compare how smoking was depicted in Hollywood movies before and after an intervention limiting paid product placement for cigarette brands. Design Correlational analysis. Setting/Participants Top box office hits released in the USA primarily between 1988 and 2011 (n=2134). Intervention The Master Settlement Agreement (MSA), implemented in 1998. Main outcome measures This study analyses trends for whether or not movies depicted smoking, and among movies with smoking, counts for character smoking scenes and average smoking scene duration. Results There was no detectable trend for any measure prior to the MSA. In 1999, 79% of movies contained smoking, and movies with smoking contained 8 scenes of character smoking, with the average duration of a character smoking scene being 81 s. After the MSA, there were significant negative post-MSA changes (p<0.05) for linear trends in proportion of movies with any smoking (which declined to 41% by 2011) and, in movies with smoking, counts of character smoking scenes (which declined to 4 by 2011). Between 1999 and 2000, there was an immediate and dramatic drop in average length of a character smoking scene, which decreased to 19 s, and remained there for the duration of the study. The probability that the drop of −62.5 (95% CI −55.1 to −70.0) seconds was due to chance was p<10−16. Conclusions This study's correlational data suggest that restricting payments for tobacco product placement coincided with profound changes in the duration of smoking depictions in movies. PMID:26822189

A habituation based approach for detection of visual changes in surveillance camera

NASA Astrophysics Data System (ADS)

Sha'abani, M. N. A. H.; Adan, N. F.; Sabani, M. S. M.; Abdullah, F.; Nadira, J. H. S.; Yasin, M. S. M.

2017-09-01

This paper investigates a habituation based approach in detecting visual changes using video surveillance systems in a passive environment. Various techniques have been introduced for dynamic environment such as motion detection, object classification and behaviour analysis. However, in a passive environment, most of the scenes recorded by the surveillance system are normal. Therefore, implementing a complex analysis all the time in the passive environment resulting on computationally expensive, especially when using a high video resolution. Thus, a mechanism of attention is required, where the system only responds to an abnormal event. This paper proposed a novelty detection mechanism in detecting visual changes and a habituation based approach to measure the level of novelty. The objective of the paper is to investigate the feasibility of the habituation based approach in detecting visual changes. Experiment results show that the approach are able to accurately detect the presence of novelty as deviations from the learned knowledge.

Physical Mechanism, Spectral Detection, and Potential Mitigation of 3D Cloud Effects on OCO-2 Radiances and Retrievals

NASA Astrophysics Data System (ADS)

Cochrane, S.; Schmidt, S.; Massie, S. T.; Iwabuchi, H.; Chen, H.

2017-12-01

Analysis of multiple partially cloudy scenes as observed by OCO-2 in nadir and target mode (published previously and reviewed here) revealed that XCO2 retrievals are systematically biased in presence of scattered clouds. The bias can only partially be removed by applying more stringent filtering, and it depends on the degree of scene inhomogeneity as quantified with collocated MODIS/Aqua imagery. The physical reason behind this effect was so far not well understood because in contrast to cloud-mediated biases in imagery-derived aerosol retrievals, passive gas absorption spectroscopy products do not depend on the absolute radiance level and should therefore be less sensitive to 3D cloud effects and surface albedo variability. However, preliminary evidence from 3D radiative transfer calculations suggested that clouds in the vicinity of an OCO-2 footprint not only offset the reflected radiance spectrum, but introduce a spectrally dependent perturbation that affects absorbing channels disproportionately, and therefore bias the spectroscopy products. To understand the nature of this effect for a variety of scenes, we developed the OCO-2 radiance simulator, which uses the available information on a scene (e.g., MODIS-derived surface albedo, cloud distribution, and other parameters) as the basis for 3D radiative transfer calculations that can predict the radiances observed by OCO-2. We present this new tool and show examples of its utility for a few specific scenes. More importantly, we draw conclusions about the physical mechanism behind this 3D cloud effect on radiances and ultimately OCO-2 retrievals, which involves not only the clouds themselves but also the surface. Harnessed with this understanding, we can now detect cloud vicinity effects in the OCO-2 spectra directly, without actually running the 3D radiance simulator. Potentially, it is even possible to mitigate these effects and thus increase data harvest in regions with ubiquitous cloud cover such as the Amazon. We will discuss some of the hurdles one faces when using only OCO-2 spectra to accomplish this goal, but also that scene context from the other A-Train instruments and the new radiance simulator tool can help overcome some of them.

Illumination discrimination in real and simulated scenes

PubMed Central

Radonjić, Ana; Pearce, Bradley; Aston, Stacey; Krieger, Avery; Dubin, Hilary; Cottaris, Nicolas P.; Brainard, David H.; Hurlbert, Anya C.

2016-01-01

Characterizing humans' ability to discriminate changes in illumination provides information about the visual system's representation of the distal stimulus. We have previously shown that humans are able to discriminate illumination changes and that sensitivity to such changes depends on their chromatic direction. Probing illumination discrimination further would be facilitated by the use of computer-graphics simulations, which would, in practice, enable a wider range of stimulus manipulations. There is no a priori guarantee, however, that results obtained with simulated scenes generalize to real illuminated scenes. To investigate this question, we measured illumination discrimination in real and simulated scenes that were well-matched in mean chromaticity and scene geometry. Illumination discrimination thresholds were essentially identical for the two stimulus types. As in our previous work, these thresholds varied with illumination change direction. We exploited the flexibility offered by the use of graphics simulations to investigate whether the differences across direction are preserved when the surfaces in the scene are varied. We show that varying the scene's surface ensemble in a manner that also changes mean scene chromaticity modulates the relative sensitivity to illumination changes along different chromatic directions. Thus, any characterization of sensitivity to changes in illumination must be defined relative to the set of surfaces in the scene. PMID:28558392

Depth-color fusion strategy for 3-D scene modeling with Kinect.

PubMed

Camplani, Massimo; Mantecon, Tomas; Salgado, Luis

2013-12-01

Low-cost depth cameras, such as Microsoft Kinect, have completely changed the world of human-computer interaction through controller-free gaming applications. Depth data provided by the Kinect sensor presents several noise-related problems that have to be tackled to improve the accuracy of the depth data, thus obtaining more reliable game control platforms and broadening its applicability. In this paper, we present a depth-color fusion strategy for 3-D modeling of indoor scenes with Kinect. Accurate depth and color models of the background elements are iteratively built, and used to detect moving objects in the scene. Kinect depth data is processed with an innovative adaptive joint-bilateral filter that efficiently combines depth and color by analyzing an edge-uncertainty map and the detected foreground regions. Results show that the proposed approach efficiently tackles main Kinect data problems: distance-dependent depth maps, spatial noise, and temporal random fluctuations are dramatically reduced; objects depth boundaries are refined, and nonmeasured depth pixels are interpolated. Moreover, a robust depth and color background model and accurate moving objects silhouette are generated.

A Dynamic Enhancement With Background Reduction Algorithm: Overview and Application to Satellite-Based Dust Storm Detection

NASA Astrophysics Data System (ADS)

Miller, Steven D.; Bankert, Richard L.; Solbrig, Jeremy E.; Forsythe, John M.; Noh, Yoo-Jeong; Grasso, Lewis D.

2017-12-01

This paper describes a Dynamic Enhancement Background Reduction Algorithm (DEBRA) applicable to multispectral satellite imaging radiometers. DEBRA uses ancillary information about the clear-sky background to reduce false detections of atmospheric parameters in complex scenes. Applied here to the detection of lofted dust, DEBRA enlists a surface emissivity database coupled with a climatological database of surface temperature to approximate the clear-sky equivalent signal for selected infrared-based multispectral dust detection tests. This background allows for suppression of false alarms caused by land surface features while retaining some ability to detect dust above those problematic surfaces. The algorithm is applicable to both day and nighttime observations and enables weighted combinations of dust detection tests. The results are provided quantitatively, as a detection confidence factor [0, 1], but are also readily visualized as enhanced imagery. Utilizing the DEBRA confidence factor as a scaling factor in false color red/green/blue imagery enables depiction of the targeted parameter in the context of the local meteorology and topography. In this way, the method holds utility to both automated clients and human analysts alike. Examples of DEBRA performance from notable dust storms and comparisons against other detection methods and independent observations are presented.

Design, optimisation and preliminary validation of a human specific loop-mediated amplification assay for the rapid detection of human DNA at forensic crime scenes.

PubMed

Hird, H J; Brown, M K

2017-11-01

The identification of samples at a crime scene which require forensic DNA typing has been the focus of recent research interest. We propose a simple, but sensitive analysis system which can be deployed at a crime scene to identify crime scene stains as human or non-human. The proposed system uses the isothermal amplification of DNA in a rapid assay format, which returns results in as little as 30min from sampling. The assay system runs on the Genie II device, a proven in-field detection system which could be deployed at a crime scene. The results presented here demonstrate that the system was sufficiently specific and sensitive and was able to detect the presence of human blood, semen and saliva on mock forensic samples. Copyright © 2017. Published by Elsevier B.V.

Hyperspectral target detection analysis of a cluttered scene from a virtual airborne sensor platform using MuSES

NASA Astrophysics Data System (ADS)

Packard, Corey D.; Viola, Timothy S.; Klein, Mark D.

2017-10-01

The ability to predict spectral electro-optical (EO) signatures for various targets against realistic, cluttered backgrounds is paramount for rigorous signature evaluation. Knowledge of background and target signatures, including plumes, is essential for a variety of scientific and defense-related applications including contrast analysis, camouflage development, automatic target recognition (ATR) algorithm development and scene material classification. The capability to simulate any desired mission scenario with forecast or historical weather is a tremendous asset for defense agencies, serving as a complement to (or substitute for) target and background signature measurement campaigns. In this paper, a systematic process for the physical temperature and visible-through-infrared radiance prediction of several diverse targets in a cluttered natural environment scene is presented. The ability of a virtual airborne sensor platform to detect and differentiate targets from a cluttered background, from a variety of sensor perspectives and across numerous wavelengths in differing atmospheric conditions, is considered. The process described utilizes the thermal and radiance simulation software MuSES and provides a repeatable, accurate approach for analyzing wavelength-dependent background and target (including plume) signatures in multiple band-integrated wavebands (multispectral) or hyperspectrally. The engineering workflow required to combine 3D geometric descriptions, thermal material properties, natural weather boundary conditions, all modes of heat transfer and spectral surface properties is summarized. This procedure includes geometric scene creation, material and optical property attribution, and transient physical temperature prediction. Radiance renderings, based on ray-tracing and the Sandford-Robertson BRDF model, are coupled with MODTRAN for the inclusion of atmospheric effects. This virtual hyperspectral/multispectral radiance prediction methodology has been extensively validated and provides a flexible process for signature evaluation and algorithm development.

Investigating the benefits of scene linking for a pathway HMD: from laboratory flight experiments to flight tests

NASA Astrophysics Data System (ADS)

Schmerwitz, Sven; Többen, Helmut; Lorenz, Bernd; Iijima, Tomoko; Kuritz-Kaiser, Anthea

2006-05-01

Pathway-in-the-sky displays enable pilots to accurately fly difficult trajectories. However, these displays may drive pilots' attention to the aircraft guidance task at the expense of other tasks particularly when the pathway display is located head-down. A pathway HUD may be a viable solution to overcome this disadvantage. Moreover, the pathway may mitigate the perceptual segregation between the static near domain and the dynamic far domain and hence, may improve attention switching between both sources. In order to more comprehensively overcome the perceptual near-to-far domain disconnect alphanumeric symbols could be attached to the pathway leading to a HUD design concept called 'scene-linking'. Two studies are presented that investigated this concept. The first study used a simplified laboratory flight experiment. Pilots (N=14) flew a curved trajectory through mountainous terrain and had to detect display events (discrete changes in a command speed indicator to be matched with current speed) and outside scene events (hostile SAM station on ground). The speed indicators were presented in superposition to the scenery either in fixed position or scene-linked to the pathway. Outside scene event detection was found improved with scene linking, however, flight-path tracking was markedly deteriorated. In the second study a scene-linked pathway concept was implemented on a monocular retinal scanning HMD and tested in real flights on a Do228 involving 5 test pilots. The flight test mainly focused at usability issues of the display in combination with an optical head tracker. Visual and instrument departure and approach tasks were evaluated comparing HMD navigation with standard instrument or terrestrial navigation. The study revealed limitations of the HMD regarding its see-through capability, field of view, weight and wearing comfort that showed to have a strong influence on pilot acceptance rather than rebutting the approach of the display concept as such.

Object memory and change detection: dissociation as a function of visual and conceptual similarity.

PubMed

Yeh, Yei-Yu; Yang, Cheng-Ta

2008-01-01

People often fail to detect a change between two visual scenes, a phenomenon referred to as change blindness. This study investigates how a post-change object's similarity to the pre-change object influences memory of the pre-change object and affects change detection. The results of Experiment 1 showed that similarity lowered detection sensitivity but did not affect the speed of identifying the pre-change object, suggesting that similarity between the pre- and post-change objects does not degrade the pre-change representation. Identification speed for the pre-change object was faster than naming the new object regardless of detection accuracy. Similarity also decreased detection sensitivity in Experiment 2 but improved the recognition of the pre-change object under both correct detection and detection failure. The similarity effect on recognition was greatly reduced when 20% of each pre-change stimulus was masked by random dots in Experiment 3. Together the results suggest that the level of pre-change representation under detection failure is equivalent to the level under correct detection and that the pre-change representation is almost complete. Similarity lowers detection sensitivity but improves explicit access in recognition. Dissociation arises between recognition and change detection as the two judgments rely on the match-to-mismatch signal and mismatch-to-match signal, respectively.

ERBE Geographic Scene and Monthly Snow Data

NASA Technical Reports Server (NTRS)

Coleman, Lisa H.; Flug, Beth T.; Gupta, Shalini; Kizer, Edward A.; Robbins, John L.

1997-01-01

The Earth Radiation Budget Experiment (ERBE) is a multisatellite system designed to measure the Earth's radiation budget. The ERBE data processing system consists of several software packages or sub-systems, each designed to perform a particular task. The primary task of the Inversion Subsystem is to reduce satellite altitude radiances to fluxes at the top of the Earth's atmosphere. To accomplish this, angular distribution models (ADM's) are required. These ADM's are a function of viewing and solar geometry and of the scene type as determined by the ERBE scene identification algorithm which is a part of the Inversion Subsystem. The Inversion Subsystem utilizes 12 scene types which are determined by the ERBE scene identification algorithm. The scene type is found by combining the most probable cloud cover, which is determined statistically by the scene identification algorithm, with the underlying geographic scene type. This Contractor Report describes how the geographic scene type is determined on a monthly basis.

Driving with indirect viewing sensors: understanding the visual perception issues

NASA Astrophysics Data System (ADS)

O'Kane, Barbara L.

1996-05-01

Visual perception is one of the most important elements of driving in that it enables the driver to understand and react appropriately to the situation along the path of the vehicle. The visual perception of the driver is enabled to the greatest extent while driving during the day. Noticeable decrements in visual acuity, range of vision, depth of field and color perception occur at night and under certain weather conditions. Indirect viewing sensors, utilizing various technologies and spectral bands, may assist the driver's normal mode of driving. Critical applications in the military as well as other official activities may require driving at night without headlights. In these latter cases, it is critical that the device, being the only source of scene information, provide the required scene cues needed for driving on, and often-times, off road. One can speculate about the scene information that a driver needs, such as road edges, terrain orientation, people and object detection in or near the path of the vehicle, and so on. But the perceptual qualities of the scene that give rise to these perceptions are little known and thus not quantified for evaluation of indirect viewing devices. This paper discusses driving with headlights and compares the scene content with that provided by a thermal system in the 8 - 12 micrometers micron spectral band, which may be used for driving at some time. The benefits and advantages of each are discussed as well as their limitations in providing information useful for the driver who must make rapid and critical decisions based upon the scene content available. General recommendations are made for potential avenues of development to overcome some of these limitations.

Automatically assessing properties of dynamic cameras for camera selection and rapid deployment of video content analysis tasks in large-scale ad-hoc networks

NASA Astrophysics Data System (ADS)

den Hollander, Richard J. M.; Bouma, Henri; van Rest, Jeroen H. C.; ten Hove, Johan-Martijn; ter Haar, Frank B.; Burghouts, Gertjan J.

2017-10-01

Video analytics is essential for managing large quantities of raw data that are produced by video surveillance systems (VSS) for the prevention, repression and investigation of crime and terrorism. Analytics is highly sensitive to changes in the scene, and for changes in the optical chain so a VSS with analytics needs careful configuration and prompt maintenance to avoid false alarms. However, there is a trend from static VSS consisting of fixed CCTV cameras towards more dynamic VSS deployments over public/private multi-organization networks, consisting of a wider variety of visual sensors, including pan-tilt-zoom (PTZ) cameras, body-worn cameras and cameras on moving platforms. This trend will lead to more dynamic scenes and more frequent changes in the optical chain, creating structural problems for analytics. If these problems are not adequately addressed, analytics will not be able to continue to meet end users' developing needs. In this paper, we present a three-part solution for managing the performance of complex analytics deployments. The first part is a register containing meta data describing relevant properties of the optical chain, such as intrinsic and extrinsic calibration, and parameters of the scene such as lighting conditions or measures for scene complexity (e.g. number of people). A second part frequently assesses these parameters in the deployed VSS, stores changes in the register, and signals relevant changes in the setup to the VSS administrator. A third part uses the information in the register to dynamically configure analytics tasks based on VSS operator input. In order to support the feasibility of this solution, we give an overview of related state-of-the-art technologies for autocalibration (self-calibration), scene recognition and lighting estimation in relation to person detection. The presented solution allows for rapid and robust deployment of Video Content Analysis (VCA) tasks in large scale ad-hoc networks.

Improved disparity map analysis through the fusion of monocular image segmentations

NASA Technical Reports Server (NTRS)

Perlant, Frederic P.; Mckeown, David M.

1991-01-01

The focus is to examine how estimates of three dimensional scene structure, as encoded in a scene disparity map, can be improved by the analysis of the original monocular imagery. The utilization of surface illumination information is provided by the segmentation of the monocular image into fine surface patches of nearly homogeneous intensity to remove mismatches generated during stereo matching. These patches are used to guide a statistical analysis of the disparity map based on the assumption that such patches correspond closely with physical surfaces in the scene. Such a technique is quite independent of whether the initial disparity map was generated by automated area-based or feature-based stereo matching. Stereo analysis results are presented on a complex urban scene containing various man-made and natural features. This scene contains a variety of problems including low building height with respect to the stereo baseline, buildings and roads in complex terrain, and highly textured buildings and terrain. The improvements are demonstrated due to monocular fusion with a set of different region-based image segmentations. The generality of this approach to stereo analysis and its utility in the development of general three dimensional scene interpretation systems are also discussed.

Adaptive Response Criteria in Road Hazard Detection Among Older Drivers

PubMed Central

Feng, Jing; Choi, HeeSun; Craik, Fergus I. M.; Levine, Brian; Moreno, Sylvain; Naglie, Gary; Zhu, Motao

2018-01-01

OBJECTIVES The majority of existing investigations on attention, aging, and driving have focused on the negative impacts of age-related declines in attention on hazard detection and driver performance. However, driving skills and behavioral compensation may accommodate the negative effects that age-related attentional decline places on driving performance. In this study, we examined an important question that had been largely neglected in the literature linking attention, aging, and driving: can top-down factors such as behavioral compensation, specifically adaptive response criteria, accommodate the negative impacts from age-related attention declines on hazard detection during driving? METHODS In the experiment, we used the Drive Aware Task, a task combining the driving context with well-controlled laboratory procedures measuring attention. We compared younger (n = 16, age 21 – 30) and older drivers (n = 21, age 65 – 79) on their attentional processing of hazards in driving scenes, indexed by percentage of correct and reaction time of hazard detection, as well as sensitivity and response criterion using the signal detection analysis. RESULTS Older drivers, in general, were less accurate and slower on the task than younger drivers. However, results from this experiment also revealed that older, but not younger, drivers adapted their response criteria when the traffic condition changed in the driving scenes. When there was more traffic in the driving scene, older drivers became more liberal in their responses, meaning that they were more likely to report that a driving hazard was detected. CONCLUSIONS Older drivers adopt compensatory strategies on hazard detection during driving . Our findings showed that, in the driving context, even at an old age our attentional functions are still adaptive according to environmental conditions. This leads to considerations on potential training methods to promote adaptive strategies which may help older drivers maintaining performance in road hazard detection. PMID:28898116

SWCD: a sliding window and self-regulated learning-based background updating method for change detection in videos

NASA Astrophysics Data System (ADS)

Işık, Şahin; Özkan, Kemal; Günal, Serkan; Gerek, Ömer Nezih

2018-03-01

Change detection with background subtraction process remains to be an unresolved issue and attracts research interest due to challenges encountered on static and dynamic scenes. The key challenge is about how to update dynamically changing backgrounds from frames with an adaptive and self-regulated feedback mechanism. In order to achieve this, we present an effective change detection algorithm for pixelwise changes. A sliding window approach combined with dynamic control of update parameters is introduced for updating background frames, which we called sliding window-based change detection. Comprehensive experiments on related test videos show that the integrated algorithm yields good objective and subjective performance by overcoming illumination variations, camera jitters, and intermittent object motions. It is argued that the obtained method makes a fair alternative in most types of foreground extraction scenarios; unlike case-specific methods, which normally fail for their nonconsidered scenarios.

Efficient wetland surface water detection and monitoring via Landsat: Comparison with in situ data from the Everglades Depth Estimation Network

USGS Publications Warehouse

Jones, John W.

2015-01-01

The U.S. Geological Survey is developing new Landsat science products. One, named Dynamic Surface Water Extent (DSWE), is focused on the representation of ground surface inundation as detected in cloud-/shadow-/snow-free pixels for scenes collected over the U.S. and its territories. Characterization of DSWE uncertainty to facilitate its appropriate use in science and resource management is a primary objective. A unique evaluation dataset developed from data made publicly available through the Everglades Depth Estimation Network (EDEN) was used to evaluate one candidate DSWE algorithm that is relatively simple, requires no scene-based calibration data, and is intended to detect inundation in the presence of marshland vegetation. A conceptual model of expected algorithm performance in vegetated wetland environments was postulated, tested and revised. Agreement scores were calculated at the level of scenes and vegetation communities, vegetation index classes, water depths, and individual EDEN gage sites for a variety of temporal aggregations. Landsat Archive cloud cover attribution errors were documented. Cloud cover had some effect on model performance. Error rates increased with vegetation cover. Relatively low error rates for locations of little/no vegetation were unexpectedly dominated by omission errors due to variable substrates and mixed pixel effects. Examined discrepancies between satellite and in situ modeled inundation demonstrated the utility of such comparisons for EDEN database improvement. Importantly, there seems no trend or bias in candidate algorithm performance as a function of time or general hydrologic conditions, an important finding for long-term monitoring. The developed database and knowledge gained from this analysis will be used for improved evaluation of candidate DSWE algorithms as well as other measurements made on Everglades surface inundation, surface water heights and vegetation using radar, lidar and hyperspectral instruments. Although no other sites have such an extensive in situ network or long-term records, the broader applicability of this and other candidate DSWE algorithms is being evaluated in other wetlands using this work as a guide. Continued interaction among DSWE producers and potential users will help determine whether the measured accuracies are adequate for practical utility in resource management.

Nighttime Foreground Pedestrian Detection Based on Three-Dimensional Voxel Surface Model.

PubMed

Li, Jing; Zhang, Fangbing; Wei, Lisong; Yang, Tao; Lu, Zhaoyang

2017-10-16

Pedestrian detection is among the most frequently-used preprocessing tasks in many surveillance application fields, from low-level people counting to high-level scene understanding. Even though many approaches perform well in the daytime with sufficient illumination, pedestrian detection at night is still a critical and challenging problem for video surveillance systems. To respond to this need, in this paper, we provide an affordable solution with a near-infrared stereo network camera, as well as a novel three-dimensional foreground pedestrian detection model. Specifically, instead of using an expensive thermal camera, we build a near-infrared stereo vision system with two calibrated network cameras and near-infrared lamps. The core of the system is a novel voxel surface model, which is able to estimate the dynamic changes of three-dimensional geometric information of the surveillance scene and to segment and locate foreground pedestrians in real time. A free update policy for unknown points is designed for model updating, and the extracted shadow of the pedestrian is adopted to remove foreground false alarms. To evaluate the performance of the proposed model, the system is deployed in several nighttime surveillance scenes. Experimental results demonstrate that our method is capable of nighttime pedestrian segmentation and detection in real time under heavy occlusion. In addition, the qualitative and quantitative comparison results show that our work outperforms classical background subtraction approaches and a recent RGB-D method, as well as achieving comparable performance with the state-of-the-art deep learning pedestrian detection method even with a much lower hardware cost.

Nighttime Foreground Pedestrian Detection Based on Three-Dimensional Voxel Surface Model

PubMed Central

Li, Jing; Zhang, Fangbing; Wei, Lisong; Lu, Zhaoyang

2017-01-01

Pedestrian detection is among the most frequently-used preprocessing tasks in many surveillance application fields, from low-level people counting to high-level scene understanding. Even though many approaches perform well in the daytime with sufficient illumination, pedestrian detection at night is still a critical and challenging problem for video surveillance systems. To respond to this need, in this paper, we provide an affordable solution with a near-infrared stereo network camera, as well as a novel three-dimensional foreground pedestrian detection model. Specifically, instead of using an expensive thermal camera, we build a near-infrared stereo vision system with two calibrated network cameras and near-infrared lamps. The core of the system is a novel voxel surface model, which is able to estimate the dynamic changes of three-dimensional geometric information of the surveillance scene and to segment and locate foreground pedestrians in real time. A free update policy for unknown points is designed for model updating, and the extracted shadow of the pedestrian is adopted to remove foreground false alarms. To evaluate the performance of the proposed model, the system is deployed in several nighttime surveillance scenes. Experimental results demonstrate that our method is capable of nighttime pedestrian segmentation and detection in real time under heavy occlusion. In addition, the qualitative and quantitative comparison results show that our work outperforms classical background subtraction approaches and a recent RGB-D method, as well as achieving comparable performance with the state-of-the-art deep learning pedestrian detection method even with a much lower hardware cost. PMID:29035295

Tracking the Effect of Algal Mats on Coral Bleaching Using Remote Sensing

NASA Astrophysics Data System (ADS)

El-Askary, H. M.; Johnson, S. H.; Idris, N.; Qurban, M. A. B.

2014-12-01

Benthic habitats rely on relatively stable environmental conditions for survival. The introduction of algal mats into an ecosystem can have a notable effect on the livelihood of organisms such as coral reefs by causing changes in the biogeochemistry of the surrounding water. Increasing levels of acidity and new competition for sunlight caused by congregations of cyanobacteria essentially starve coral reefs of natural resources. These changes are particularly prevalent in waters near quickly developing population centers, such as the ecologically diverse Arabian Gulf. While ground-truthing studies to determine the extensiveness of coral death proves useful on a microcosmic level, new ventures in remote sensing research allow scientists to utilize satellite data to track these changes on a broader scale. Satellite images acquired from Landsat 5, 1987, Landsat 7, 2000, and Landsat 8, 2013 along with higher resolution IKONOS data are digitally analyzed in order to create spectral libraries for relevant benthic types, which in turn can be used to perform supervised classifications and change detection analyses over a larger area. The supervised classifications performed over the three scenes show five significant marine-related classes, namely coral, mangroves, macro-algae, and seagrass, in different degrees of abundance, yet here we focus only on the algal mats impact on corals bleaching. The change detection analysis is introduced to study see the degree of algal mats impact on coral bleaching over the course of time with possible connection to the local meteorology and current climate scenarios.

Utilization of DIRSIG in support of real-time infrared scene generation

NASA Astrophysics Data System (ADS)

Sanders, Jeffrey S.; Brown, Scott D.

2000-07-01

Real-time infrared scene generation for hardware-in-the-loop has been a traditionally difficult challenge. Infrared scenes are usually generated using commercial hardware that was not designed to properly handle the thermal and environmental physics involved. Real-time infrared scenes typically lack details that are included in scenes rendered in no-real- time by ray-tracing programs such as the Digital Imaging and Remote Sensing Scene Generation (DIRSIG) program. However, executing DIRSIG in real-time while retaining all the physics is beyond current computational capabilities for many applications. DIRSIG is a first principles-based synthetic image generation model that produces multi- or hyper-spectral images in the 0.3 to 20 micron region of the electromagnetic spectrum. The DIRSIG model is an integrated collection of independent first principles based on sub-models, each of which works in conjunction to produce radiance field images with high radiometric fidelity. DIRSIG uses the MODTRAN radiation propagation model for exo-atmospheric irradiance, emitted and scattered radiances (upwelled and downwelled) and path transmission predictions. This radiometry submodel utilizes bidirectional reflectance data, accounts for specular and diffuse background contributions, and features path length dependent extinction and emission for transmissive bodies (plumes, clouds, etc.) which may be present in any target, background or solar path. This detailed environmental modeling greatly enhances the number of rendered features and hence, the fidelity of a rendered scene. While DIRSIG itself cannot currently be executed in real-time, its outputs can be used to provide scene inputs for real-time scene generators. These inputs can incorporate significant features such as target to background thermal interactions, static background object thermal shadowing, and partially transmissive countermeasures. All of these features represent significant improvements over the current state of the art in real-time IR scene generation.

Scene text recognition in mobile applications by character descriptor and structure configuration.

PubMed

Yi, Chucai; Tian, Yingli

2014-07-01

Text characters and strings in natural scene can provide valuable information for many applications. Extracting text directly from natural scene images or videos is a challenging task because of diverse text patterns and variant background interferences. This paper proposes a method of scene text recognition from detected text regions. In text detection, our previously proposed algorithms are applied to obtain text regions from scene image. First, we design a discriminative character descriptor by combining several state-of-the-art feature detectors and descriptors. Second, we model character structure at each character class by designing stroke configuration maps. Our algorithm design is compatible with the application of scene text extraction in smart mobile devices. An Android-based demo system is developed to show the effectiveness of our proposed method on scene text information extraction from nearby objects. The demo system also provides us some insight into algorithm design and performance improvement of scene text extraction. The evaluation results on benchmark data sets demonstrate that our proposed scheme of text recognition is comparable with the best existing methods.

Did limits on payments for tobacco placements in US movies affect how movies are made?

PubMed

Morgenstern, Matthis; Stoolmiller, Mike; Bergamini, Elaina; Sargent, James D

2017-01-01

To compare how smoking was depicted in Hollywood movies before and after an intervention limiting paid product placement for cigarette brands. Correlational analysis. Top box office hits released in the USA primarily between 1988 and 2011 (n=2134). The Master Settlement Agreement (MSA), implemented in 1998. This study analyses trends for whether or not movies depicted smoking, and among movies with smoking, counts for character smoking scenes and average smoking scene duration. There was no detectable trend for any measure prior to the MSA. In 1999, 79% of movies contained smoking, and movies with smoking contained 8 scenes of character smoking, with the average duration of a character smoking scene being 81 s. After the MSA, there were significant negative post-MSA changes (p<0.05) for linear trends in proportion of movies with any smoking (which declined to 41% by 2011) and, in movies with smoking, counts of character smoking scenes (which declined to 4 by 2011). Between 1999 and 2000, there was an immediate and dramatic drop in average length of a character smoking scene, which decreased to 19 s, and remained there for the duration of the study. The probability that the drop of -62.5 (95% CI -55.1 to -70.0) seconds was due to chance was p<10 -16 . This study's correlational data suggest that restricting payments for tobacco product placement coincided with profound changes in the duration of smoking depictions in movies. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Anomaly detection in hyperspectral imagery: statistics vs. graph-based algorithms

NASA Astrophysics Data System (ADS)

Berkson, Emily E.; Messinger, David W.

2016-05-01

Anomaly detection (AD) algorithms are frequently applied to hyperspectral imagery, but different algorithms produce different outlier results depending on the image scene content and the assumed background model. This work provides the first comparison of anomaly score distributions between common statistics-based anomaly detection algorithms (RX and subspace-RX) and the graph-based Topological Anomaly Detector (TAD). Anomaly scores in statistical AD algorithms should theoretically approximate a chi-squared distribution; however, this is rarely the case with real hyperspectral imagery. The expected distribution of scores found with graph-based methods remains unclear. We also look for general trends in algorithm performance with varied scene content. Three separate scenes were extracted from the hyperspectral MegaScene image taken over downtown Rochester, NY with the VIS-NIR-SWIR ProSpecTIR instrument. In order of most to least cluttered, we study an urban, suburban, and rural scene. The three AD algorithms were applied to each scene, and the distributions of the most anomalous 5% of pixels were compared. We find that subspace-RX performs better than RX, because the data becomes more normal when the highest variance principal components are removed. We also see that compared to statistical detectors, anomalies detected by TAD are easier to separate from the background. Due to their different underlying assumptions, the statistical and graph-based algorithms highlighted different anomalies within the urban scene. These results will lead to a deeper understanding of these algorithms and their applicability across different types of imagery.

You think you know where you looked? You better look again.

PubMed

Võ, Melissa L-H; Aizenman, Avigael M; Wolfe, Jeremy M

2016-10-01

People are surprisingly bad at knowing where they have looked in a scene. We tested participants' ability to recall their own eye movements in 2 experiments using natural or artificial scenes. In each experiment, participants performed a change-detection (Exp.1) or search (Exp.2) task. On 25% of trials, after 3 seconds of viewing the scene, participants were asked to indicate where they thought they had just fixated. They responded by making mouse clicks on 12 locations in the unchanged scene. After 135 trials, observers saw 10 new scenes and were asked to put 12 clicks where they thought someone else would have looked. Although observers located their own fixations more successfully than a random model, their performance was no better than when they were guessing someone else's fixations. Performance with artificial scenes was worse, though judging one's own fixations was slightly superior. Even after repeating the fixation-location task on 30 scenes immediately after scene viewing, performance was far from the prediction of an ideal observer. Memory for our own fixation locations appears to add next to nothing beyond what common sense tells us about the likely fixations of others. These results have important implications for socially important visual search tasks. For example, a radiologist might think he has looked at "everything" in an image, but eye tracking data suggest that this is not so. Such shortcomings might be avoided by providing observers with better insights of where they have looked. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Cross-sensor comparisons between Landsat 5 TM and IRS-P6 AWiFS and disturbance detection using integrated Landsat and AWiFS time-series images

USGS Publications Warehouse

Chen, Xuexia; Vogelmann, James E.; Chander, Gyanesh; Ji, Lei; Tolk, Brian; Huang, Chengquan; Rollins, Matthew

2013-01-01

Routine acquisition of Landsat 5 Thematic Mapper (TM) data was discontinued recently and Landsat 7 Enhanced Thematic Mapper Plus (ETM+) has an ongoing problem with the scan line corrector (SLC), thereby creating spatial gaps when covering images obtained during the process. Since temporal and spatial discontinuities of Landsat data are now imminent, it is therefore important to investigate other potential satellite data that can be used to replace Landsat data. We thus cross-compared two near-simultaneous images obtained from Landsat 5 TM and the Indian Remote Sensing (IRS)-P6 Advanced Wide Field Sensor (AWiFS), both captured on 29 May 2007 over Los Angeles, CA. TM and AWiFS reflectances were compared for the green, red, near-infrared (NIR), and shortwave infrared (SWIR) bands, as well as the normalized difference vegetation index (NDVI) based on manually selected polygons in homogeneous areas. All R2 values of linear regressions were found to be higher than 0.99. The temporally invariant cluster (TIC) method was used to calculate the NDVI correlation between the TM and AWiFS images. The NDVI regression line derived from selected polygons passed through several invariant cluster centres of the TIC density maps and demonstrated that both the scene-dependent polygon regression method and TIC method can generate accurate radiometric normalization. A scene-independent normalization method was also used to normalize the AWiFS data. Image agreement assessment demonstrated that the scene-dependent normalization using homogeneous polygons provided slightly higher accuracy values than those obtained by the scene-independent method. Finally, the non-normalized and relatively normalized ‘Landsat-like’ AWiFS 2007 images were integrated into 1984 to 2010 Landsat time-series stacks (LTSS) for disturbance detection using the Vegetation Change Tracker (VCT) model. Both scene-dependent and scene-independent normalized AWiFS data sets could generate disturbance maps similar to what were generated using the LTSS data set, and their kappa coefficients were higher than 0.97. These results indicate that AWiFS can be used instead of Landsat data to detect multitemporal disturbance in the event of Landsat data discontinuity.

Clustering approaches to feature change detection

NASA Astrophysics Data System (ADS)

G-Michael, Tesfaye; Gunzburger, Max; Peterson, Janet

2018-05-01

The automated detection of changes occurring between multi-temporal images is of significant importance in a wide range of medical, environmental, safety, as well as many other settings. The usage of k-means clustering is explored as a means for detecting objects added to a scene. The silhouette score for the clustering is used to define the optimal number of clusters that should be used. For simple images having a limited number of colors, new objects can be detected by examining the change between the optimal number of clusters for the original and modified images. For more complex images, new objects may need to be identified by examining the relative areas covered by corresponding clusters in the original and modified images. Which method is preferable depends on the composition and range of colors present in the images. In addition to describing the clustering and change detection methodology of our proposed approach, we provide some simple illustrations of its application.

Implementation of jump-diffusion algorithms for understanding FLIR scenes

NASA Astrophysics Data System (ADS)

Lanterman, Aaron D.; Miller, Michael I.; Snyder, Donald L.

1995-07-01

Our pattern theoretic approach to the automated understanding of forward-looking infrared (FLIR) images brings the traditionally separate endeavors of detection, tracking, and recognition together into a unified jump-diffusion process. New objects are detected and object types are recognized through discrete jump moves. Between jumps, the location and orientation of objects are estimated via continuous diffusions. An hypothesized scene, simulated from the emissive characteristics of the hypothesized scene elements, is compared with the collected data by a likelihood function based on sensor statistics. This likelihood is combined with a prior distribution defined over the set of possible scenes to form a posterior distribution. The jump-diffusion process empirically generates the posterior distribution. Both the diffusion and jump operations involve the simulation of a scene produced by a hypothesized configuration. Scene simulation is most effectively accomplished by pipelined rendering engines such as silicon graphics. We demonstrate the execution of our algorithm on a silicon graphics onyx/reality engine.

Integration and segregation in auditory scene analysis

NASA Astrophysics Data System (ADS)

Sussman, Elyse S.

2005-03-01

Assessment of the neural correlates of auditory scene analysis, using an index of sound change detection that does not require the listener to attend to the sounds [a component of event-related brain potentials called the mismatch negativity (MMN)], has previously demonstrated that segregation processes can occur without attention focused on the sounds and that within-stream contextual factors influence how sound elements are integrated and represented in auditory memory. The current study investigated the relationship between the segregation and integration processes when they were called upon to function together. The pattern of MMN results showed that the integration of sound elements within a sound stream occurred after the segregation of sounds into independent streams and, further, that the individual streams were subject to contextual effects. These results are consistent with a view of auditory processing that suggests that the auditory scene is rapidly organized into distinct streams and the integration of sequential elements to perceptual units takes place on the already formed streams. This would allow for the flexibility required to identify changing within-stream sound patterns, needed to appreciate music or comprehend speech..

New scene change control scheme based on pseudoskipped picture

NASA Astrophysics Data System (ADS)

Lee, Youngsun; Lee, Jinwhan; Chang, Hyunsik; Nam, Jae Y.

1997-01-01

A new scene change control scheme which improves the video coding performance for sequences that have many scene changed pictures is proposed in this paper. The scene changed pictures except intra-coded picture usually need more bits than normal pictures in order to maintain constant picture quality. The major idea of this paper is how to obtain extra bits which are needed to encode scene changed pictures. We encode a B picture which is located before a scene changed picture like a skipped picture. We call such a B picture as a pseudo-skipped picture. By generating the pseudo-skipped picture like a skipped picture. We call such a B picture as a pseudo-skipped picture. By generating the pseudo-skipped picture, we can save some bits and they are added to the originally allocated target bits to encode the scene changed picture. The simulation results show that the proposed algorithm improves encoding performance about 0.5 to approximately 2.0 dB of PSNR compared to MPEG-2 TM5 rate controls scheme. In addition, the suggested algorithm is compatible with MPEG-2 video syntax and the picture repetition is not recognizable.

IKONOS geometric characterization

USGS Publications Warehouse

Helder, Dennis; Coan, Michael; Patrick, Kevin; Gaska, Peter

2003-01-01

The IKONOS spacecraft acquired images on July 3, 17, and 25, and August 13, 2001 of Brookings SD, a small city in east central South Dakota, and on May 22, June 30, and July 30, 2000, of the rural area around the EROS Data Center. South Dakota State University (SDSU) evaluated the Brookings scenes and the USGS EROS Data Center (EDC) evaluated the other scenes. The images evaluated by SDSU utilized various natural objects and man-made features as identifiable targets randomly distribution throughout the scenes, while the images evaluated by EDC utilized pre-marked artificial points (panel points) to provide the best possible targets distributed in a grid pattern. Space Imaging provided products at different processing levels to each institution. For each scene, the pixel (line, sample) locations of the various targets were compared to field observed, survey-grade Global Positioning System locations. Patterns of error distribution for each product were plotted, and a variety of statistical statements of accuracy are made. The IKONOS sensor also acquired 12 pairs of stereo images of globally distributed scenes between April 2000 and April 2001. For each scene, analysts at the National Imagery and Mapping Agency (NIMA) compared derived photogrammetric coordinates to their corresponding NIMA field-surveyed ground control point (GCPs). NIMA analysts determined horizontal and vertical accuracies by averaging the differences between the derived photogrammetric points and the field-surveyed GCPs for all 12 stereo pairs. Patterns of error distribution for each scene are presented.

Text Extraction from Scene Images by Character Appearance and Structure Modeling

PubMed Central

Yi, Chucai; Tian, Yingli

2012-01-01

In this paper, we propose a novel algorithm to detect text information from natural scene images. Scene text classification and detection are still open research topics. Our proposed algorithm is able to model both character appearance and structure to generate representative and discriminative text descriptors. The contributions of this paper include three aspects: 1) a new character appearance model by a structure correlation algorithm which extracts discriminative appearance features from detected interest points of character samples; 2) a new text descriptor based on structons and correlatons, which model character structure by structure differences among character samples and structure component co-occurrence; and 3) a new text region localization method by combining color decomposition, character contour refinement, and string line alignment to localize character candidates and refine detected text regions. We perform three groups of experiments to evaluate the effectiveness of our proposed algorithm, including text classification, text detection, and character identification. The evaluation results on benchmark datasets demonstrate that our algorithm achieves the state-of-the-art performance on scene text classification and detection, and significantly outperforms the existing algorithms for character identification. PMID:23316111

Just Another Social Scene: Evidence for Decreased Attention to Negative Social Scenes in High-Functioning Autism

ERIC Educational Resources Information Center

Santos, Andreia; Chaminade, Thierry; Da Fonseca, David; Silva, Catarina; Rosset, Delphine; Deruelle, Christine

2012-01-01

The adaptive threat-detection advantage takes the form of a preferential orienting of attention to threatening scenes. In this study, we compared attention to social scenes in 15 high-functioning individuals with autism (ASD) and matched typically developing (TD) individuals. Eye-tracking was recorded while participants were presented with pairs…

Contrast discrimination, non-uniform patterns and change blindness.

PubMed Central

Scott-Brown, K C; Orbach, H S

1998-01-01

Change blindness--our inability to detect large changes in natural scenes when saccades, blinks and other transients interrupt visual input--seems to contradict psychophysical evidence for our exquisite sensitivity to contrast changes. Can the type of effects described as 'change blindness' be observed with simple, multi-element stimuli, amenable to psychophysical analysis? Such stimuli, composed of five mixed contrast elements, elicited a striking increase in contrast increment thresholds compared to those for an isolated element. Cue presentation prior to the stimulus substantially reduced thresholds, as for change blindness with natural scenes. On one hand, explanations for change blindness based on abstract and sketchy representations in short-term visual memory seem inappropriate for this low-level image property of contrast where there is ample evidence for exquisite performance on memory tasks. On the other hand, the highly increased thresholds for mixed contrast elements, and the decreased thresholds when a cue is present, argue against any simple early attentional or sensory explanation for change blindness. Thus, psychophysical results for very simple patterns cannot straightforwardly predict results even for the slightly more complicated patterns studied here. PMID:9872004

Using Deep Learning Algorithm to Enhance Image-review Software for Surveillance Cameras

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cui, Yonggang; Thomas, Maikael A.

We propose the development of proven deep learning algorithms to flag objects and events of interest in Next Generation Surveillance System (NGSS) surveillance to make IAEA image review more efficient. Video surveillance is one of the core monitoring technologies used by the IAEA Department of Safeguards when implementing safeguards at nuclear facilities worldwide. The current image review software GARS has limited automated functions, such as scene-change detection, black image detection and missing scene analysis, but struggles with highly cluttered backgrounds. A cutting-edge algorithm to be developed in this project will enable efficient and effective searches in images and video streamsmore » by identifying and tracking safeguards relevant objects and detect anomalies in their vicinity. In this project, we will develop the algorithm, test it with the IAEA surveillance cameras and data sets collected at simulated nuclear facilities at BNL and SNL, and implement it in a software program for potential integration into the IAEA’s IRAP (Integrated Review and Analysis Program).« less

How high is visual short-term memory capacity for object layout?

PubMed

Sanocki, Thomas; Sellers, Eric; Mittelstadt, Jeff; Sulman, Noah

2010-05-01

Previous research measuring visual short-term memory (VSTM) suggests that the capacity for representing the layout of objects is fairly high. In four experiments, we further explored the capacity of VSTM for layout of objects, using the change detection method. In Experiment 1, participants retained most of the elements in displays of 4 to 8 elements. In Experiments 2 and 3, with up to 20 elements, participants retained many of them, reaching a capacity of 13.4 stimulus elements. In Experiment 4, participants retained much of a complex naturalistic scene. In most cases, increasing display size caused only modest reductions in performance, consistent with the idea of configural, variable-resolution grouping. The results indicate that participants can retain a substantial amount of scene layout information (objects and locations) in short-term memory. We propose that this is a case of remote visual understanding, where observers' ability to integrate information from a scene is paramount.

Advanced interactive display formats for terminal area traffic control

NASA Technical Reports Server (NTRS)

Grunwald, Arthur J.

1996-01-01

This report describes the basic design considerations for perspective air traffic control displays. A software framework has been developed for manual viewing parameter setting (MVPS) in preparation for continued, ongoing developments on automated viewing parameter setting (AVPS) schemes. Two distinct modes of MVPS operations are considered, both of which utilize manipulation pointers imbedded in the three-dimensional scene: (1) direct manipulation of the viewing parameters -- in this mode the manipulation pointers act like the control-input device, through which the viewing parameter changes are made. Part of the parameters are rate controlled, and part of them position controlled. This mode is intended for making fast, iterative small changes in the parameters. (2) Indirect manipulation of the viewing parameters -- this mode is intended primarily for introducing large, predetermined changes in the parameters. Requests for changes in viewing parameter setting are entered manually by the operator by moving viewing parameter manipulation pointers on the screen. The motion of these pointers, which are an integral part of the 3-D scene, is limited to the boundaries of the screen. This arrangement has been chosen in order to preserve the correspondence between the spatial lay-outs of the new and the old viewing parameter setting, a feature which contributes to preventing spatial disorientation of the operator. For all viewing operations, e.g. rotation, translation and ranging, the actual change is executed automatically by the system, through gradual transitions with an exponentially damped, sinusoidal velocity profile, in this work referred to as 'slewing' motions. The slewing functions, which eliminate discontinuities in the viewing parameter changes, are designed primarily for enhancing the operator's impression that he, or she, is dealing with an actually existing physical system, rather than an abstract computer-generated scene. The proposed, continued research efforts will deal with the development of automated viewing parameter setting schemes. These schemes employ an optimization strategy, aimed at identifying the best possible vantage point, from which the air traffic control scene can be viewed for a given traffic situation. They determine whether a change in viewing parameter setting is required and determine the dynamic path along which the change to the new viewing parameter setting should take place.

Investigation of several aspects of LANDSAT-4 data quality

NASA Technical Reports Server (NTRS)

Wrigley, R. C. (Principal Investigator)

1983-01-01

No insurmountable problems in change detection analysis were found when portions of scenes collected simultaneously by LANDSAT 4 MSS and either LANDSAT 2 or 3. The cause of the periodic noise in LANDSAT 4 MSS images which had a RMS value of approximately 2DN should be corrected in the LANDSAT D instrument before its launch. Analysis of the P-tape of the Arkansas scene shows bands within the same focal plane very well registered except for the thermal band which was misregistered by approximately three 28.5 meter pixels in both directions. It is possible to derive tight confidence bounds for the registration errors. Preliminary analyses of the Sacramento and Arkansas scenes reveals a very high degree of consistency with earlier results for bands 3 vs 1, 3 vs 4, and 3 vs 5. Results are presented in table form. It is suggested that attention be given to the standard deviations of registrations errors to judge whether or not they will be within specification once any known mean registration errors are corrected. Techniques used for MTF analysis of a Washington scene produced noisy results.

Faces do not capture special attention in children with autism spectrum disorder: a change blindness study.

PubMed

Kikuchi, Yukiko; Senju, Atsushi; Tojo, Yoshikuni; Osanai, Hiroo; Hasegawa, Toshikazu

2009-01-01

Two experiments investigated attention of children with autism spectrum disorder (ASD) to faces and objects. In both experiments, children (7- to 15-year-olds) detected the difference between 2 visual scenes. Results in Experiment 1 revealed that typically developing children (n = 16) detected the change in faces faster than in objects, whereas children with ASD (n = 16) were equally fast in detecting changes in faces and objects. These results were replicated in Experiment 2 (n = 16 in children with ASD and 22 in typically developing children), which does not require face recognition skill. Results suggest that children with ASD lack an attentional bias toward others' faces, which could contribute to their atypical social orienting.

[Perception of objects and scenes in age-related macular degeneration].

PubMed

Tran, T H C; Boucart, M

2012-01-01

Vision related quality of life questionnaires suggest that patients with AMD exhibit difficulties in finding objects and in mobility. In the natural environment, objects seldom appear in isolation. They appear in a spatial context which may obscure them in part or place obstacles in the patient's path. Furthermore, the luminance of a natural scene varies as a function of the hour of the day and the light source, which can alter perception. This study aims to evaluate recognition of objects and natural scenes by patients with AMD, by using photographs of such scenes. Studies demonstrate that AMD patients are able to categorize scenes as nature scenes or urban scenes and to discriminate indoor from outdoor scenes with a high degree of precision. They detect objects better in isolation, in color, or against a white background than in their natural contexts. These patients encounter more difficulties than normally sighted individuals in detecting objects in a low-contrast, black-and-white scene. These results may have implications for rehabilitation, for layout of texts and magazines for the reading-impaired and for the rearrangement of the spatial environment of older AMD patients in order to facilitate mobility, finding objects and reducing the risk of falls. Copyright © 2011 Elsevier Masson SAS. All rights reserved.

Perception of Objects in Natural Scenes: Is It Really Attention Free?

ERIC Educational Resources Information Center

Evans, Karla K.; Treisman, Anne

2005-01-01

Studies have suggested attention-free semantic processing of natural scenes in which concurrent tasks leave category detection unimpaired (e.g., F. Li, R. VanRullen, C. Koch, & P. Perona, 2002). Could this ability reflect detection of disjunctive feature sets rather than high-level binding? Participants detected an animal target in a rapid serial…

A Methodology for Evaluating the Fidelity of Ground-Based Flight Simulators

NASA Technical Reports Server (NTRS)

Zeyada, Y.; Hess, R. A.

1999-01-01

An analytical and experimental investigation was undertaken to model the manner in which pilots perceive and utilize visual, proprioceptive, and vestibular cues in a ground-based flight simulator. The study was part of a larger research effort which has the creation of a methodology for determining flight simulator fidelity requirements as its ultimate goal. The study utilized a closed-loop feedback structure of the pilot/simulator system which included the pilot, the cockpit inceptor, the dynamics of the simulated vehicle and the motion system. With the exception of time delays which accrued in visual scene production in the simulator, visual scene effects were not included in this study. The NASA Ames Vertical Motion Simulator was used in a simple, single-degree of freedom rotorcraft bob-up/down maneuver. Pilot/vehicle analysis and fuzzy-inference identification were employed to study the changes in fidelity which occurred as the characteristics of the motion system were varied over five configurations i The data from three of the five pilots that participated in the experimental study were analyzed in the fuzzy inference identification. Results indicate that both the analytical pilot/vehicle analysis and the fuzzyinference identification can be used to reflect changes in simulator fidelity for the task examined.

A Methodology for Evaluating the Fidelity of Ground-Based Flight Simulators

NASA Technical Reports Server (NTRS)

Zeyada, Y.; Hess, R. A.

1999-01-01

An analytical and experimental investigation was undertaken to model the manner in which pilots perceive and utilize visual, proprioceptive, and vestibular cues in a ground-based flight simulator. The study was part of a larger research effort which has the creation of a methodology for determining flight simulator fidelity requirements as its ultimate goal. The study utilized a closed-loop feedback structure of the pilot/simulator system which included the pilot, the cockpit inceptor, the dynamics of the simulated vehicle and the motion system. With the exception of time delays which accrued in visual scene production in the simulator, visual scene effects were not included in this study. The NASA Ames Vertical Motion Simulator was used in a simple, single-degree of freedom rotorcraft bob-up/down maneuver. Pilot/vehicle analysis and fuzzy-inference identification were employed to study the changes in fidelity which occurred as the characteristics of the motion system were varied over five configurations. The data from three of the five pilots that participated in the experimental study were analyzed in the fuzzy-inference identification. Results indicate that both the analytical pilot/vehicle analysis and the fuzzy-inference identification can be used to reflect changes in simulator fidelity for the task examined.

Snow Coverage Analysis Using ASTER over the Sierra Nevada Mountain Range

NASA Astrophysics Data System (ADS)

Ross, B.

2017-12-01

Snow has strong impacts on human behavior, state and local activities, and the economy. The Sierra Nevada snowpack is California's most important natural reservoir of water. Such snow is melting sooner and faster. A recent California drought study showed that there was a deficit of 1.5 million acre-feet of water in 2014 due to the fast melting rates. Scientists have been using the Moderate Resolution Imaging Spectrometer (MODIS) which is available at the spatial resolution of 500-meter, to analyze the changes in snow coverage. While such analysis provides us with the valuable information, it would be more beneficial to employ the imageries at a higher spatial resolution for snow studies. Advanced Spaceborne Thermal Emission and Reflectance Radiometer (ASTER), which acquires the high-resolution imageries ranging from 15-meter to 90-meter, has recently become freely available to the public. Our study utilized two scenes obtained from ASTER to investigate the changes in snow extent over the Sierra Nevada's mountain area for an 8-year period. These two scenes were collected on April 11, 2007 and April 16, 2015 covering the same geographic region. Normalized Difference Snow Index (NDSI) was adopted to delineate the snow coverage in each scene. Our study shows a substantial decrease of snow coverage in the studied geographic region by pixel count.

Multisensor Fusion for Change Detection

NASA Astrophysics Data System (ADS)

Schenk, T.; Csatho, B.

2005-12-01

Combining sensors that record different properties of a 3-D scene leads to complementary and redundant information. If fused properly, a more robust and complete scene description becomes available. Moreover, fusion facilitates automatic procedures for object reconstruction and modeling. For example, aerial imaging sensors, hyperspectral scanning systems, and airborne laser scanning systems generate complementary data. We describe how data from these sensors can be fused for such diverse applications as mapping surface erosion and landslides, reconstructing urban scenes, monitoring urban land use and urban sprawl, and deriving velocities and surface changes of glaciers and ice sheets. An absolute prerequisite for successful fusion is a rigorous co-registration of the sensors involved. We establish a common 3-D reference frame by using sensor invariant features. Such features are caused by the same object space phenomena and are extracted in multiple steps from the individual sensors. After extracting, segmenting and grouping the features into more abstract entities, we discuss ways on how to automatically establish correspondences. This is followed by a brief description of rigorous mathematical models suitable to deal with linear and area features. In contrast to traditional, point-based registration methods, lineal and areal features lend themselves to a more robust and more accurate registration. More important, the chances to automate the registration process increases significantly. The result of the co-registration of the sensors is a unique transformation between the individual sensors and the object space. This makes spatial reasoning of extracted information more versatile; reasoning can be performed in sensor space or in 3-D space where domain knowledge about features and objects constrains reasoning processes, reduces the search space, and helps to make the problem well-posed. We demonstrate the feasibility of the proposed multisensor fusion approach with detecting surface elevation changes on the Byrd Glacier, Antarctica, with aerial imagery from 1980s and ICESat laser altimetry data from 2003-05. Change detection from such disparate data sets is an intricate fusion problem, beginning with sensor alignment, and on to reasoning with spatial information as to where changes occurred and to what extent.

Sea-Based Infrared Scene Interpretation by Background Type Classification and Coastal Region Detection for Small Target Detection

PubMed Central

Kim, Sungho

2015-01-01

Sea-based infrared search and track (IRST) is important for homeland security by detecting missiles and asymmetric boats. This paper proposes a novel scheme to interpret various infrared scenes by classifying the infrared background types and detecting the coastal regions in omni-directional images. The background type or region-selective small infrared target detector should be deployed to maximize the detection rate and to minimize the number of false alarms. A spatial filter-based small target detector is suitable for identifying stationary incoming targets in remote sea areas with sky only. Many false detections can occur if there is an image sector containing a coastal region, due to ground clutter and the difficulty in finding true targets using the same spatial filter-based detector. A temporal filter-based detector was used to handle these problems. Therefore, the scene type and coastal region information is critical to the success of IRST in real-world applications. In this paper, the infrared scene type was determined using the relationships between the sensor line-of-sight (LOS) and a horizontal line in an image. The proposed coastal region detector can be activated if the background type of the probing sector is determined to be a coastal region. Coastal regions can be detected by fusing the region map and curve map. The experimental results on real infrared images highlight the feasibility of the proposed sea-based scene interpretation. In addition, the effects of the proposed scheme were analyzed further by applying region-adaptive small target detection. PMID:26404308

The nature-disorder paradox: A perceptual study on how nature is disorderly yet aesthetically preferred.

PubMed

Kotabe, Hiroki P; Kardan, Omid; Berman, Marc G

2017-08-01

Natural environments have powerful aesthetic appeal linked to their capacity for psychological restoration. In contrast, disorderly environments are aesthetically aversive, and have various detrimental psychological effects. But in our research, we have repeatedly found that natural environments are perceptually disorderly. What could explain this paradox? We present 3 competing hypotheses: the aesthetic preference for naturalness is more powerful than the aesthetic aversion to disorder (the nature-trumps-disorder hypothesis ); disorder is trivial to aesthetic preference in natural contexts (the harmless-disorder hypothesis ); and disorder is aesthetically preferred in natural contexts (the beneficial-disorder hypothesis ). Utilizing novel methods of perceptual study and diverse stimuli, we rule in the nature-trumps-disorder hypothesis and rule out the harmless-disorder and beneficial-disorder hypotheses. In examining perceptual mechanisms, we find evidence that high-level scene semantics are both necessary and sufficient for the nature-trumps-disorder effect. Necessity is evidenced by the effect disappearing in experiments utilizing only low-level visual stimuli (i.e., where scene semantics have been removed) and experiments utilizing a rapid-scene-presentation procedure that obscures scene semantics. Sufficiency is evidenced by the effect reappearing in experiments utilizing noun stimuli which remove low-level visual features. Furthermore, we present evidence that the interaction of scene semantics with low-level visual features amplifies the nature-trumps-disorder effect-the effect is weaker both when statistically adjusting for quantified low-level visual features and when using noun stimuli which remove low-level visual features. These results have implications for psychological theories bearing on the joint influence of low- and high-level perceptual inputs on affect and cognition, as well as for aesthetic design. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Multispectral Terrain Background Simulation Techniques For Use In Airborne Sensor Evaluation

NASA Astrophysics Data System (ADS)

Weinberg, Michael; Wohlers, Ronald; Conant, John; Powers, Edward

1988-08-01

A background simulation code developed at Aerodyne Research, Inc., called AERIE is designed to reflect the major sources of clutter that are of concern to staring and scanning sensors of the type being considered for various airborne threat warning (both aircraft and missiles) sensors. The code is a first principles model that could be used to produce a consistent image of the terrain for various spectral bands, i.e., provide the proper scene correlation both spectrally and spatially. The code utilizes both topographic and cultural features to model terrain, typically from DMA data, with a statistical overlay of the critical underlying surface properties (reflectance, emittance, and thermal factors) to simulate the resulting texture in the scene. Strong solar scattering from water surfaces is included with allowance for wind driven surface roughness. Clouds can be superimposed on the scene using physical cloud models and an analytical representation of the reflectivity obtained from scattering off spherical particles. The scene generator is augmented by collateral codes that allow for the generation of images at finer resolution. These codes provide interpolation of the basic DMA databases using fractal procedures that preserve the high frequency power spectral density behavior of the original scene. Scenes are presented illustrating variations in altitude, radiance, resolution, material, thermal factors, and emissivities. The basic models utilized for simulation of the various scene components and various "engineering level" approximations are incorporated to reduce the computational complexity of the simulation.

Psychophysical Criteria for Visual Simulation Systems.

DTIC Science & Technology

1980-05-01

definitive data were found to estab- lish detection thresholds; therefore, this is one area where a psycho- physical study was recommended. Differential size...The specific functional relationships needinq quantification were the following: 1. The effect of Horizontal Aniseikonia on Target Detection and...Transition Technique 6. The Effects of Scene Complexity and Separation on the Detection of Scene Misalignment 7. Absolute Brightness Levels in

Interactive MPEG-4 low-bit-rate speech/audio transmission over the Internet

NASA Astrophysics Data System (ADS)

Liu, Fang; Kim, JongWon; Kuo, C.-C. Jay

1999-11-01

The recently developed MPEG-4 technology enables the coding and transmission of natural and synthetic audio-visual data in the form of objects. In an effort to extend the object-based functionality of MPEG-4 to real-time Internet applications, architectural prototypes of multiplex layer and transport layer tailored for transmission of MPEG-4 data over IP are under debate among Internet Engineering Task Force (IETF), and MPEG-4 systems Ad Hoc group. In this paper, we present an architecture for interactive MPEG-4 speech/audio transmission system over the Internet. It utilities a framework of Real Time Streaming Protocol (RTSP) over Real-time Transport Protocol (RTP) to provide controlled, on-demand delivery of real time speech/audio data. Based on a client-server model, a couple of low bit-rate bit streams (real-time speech/audio, pre- encoded speech/audio) are multiplexed and transmitted via a single RTP channel to the receiver. The MPEG-4 Scene Description (SD) and Object Descriptor (OD) bit streams are securely sent through the RTSP control channel. Upon receiving, an initial MPEG-4 audio- visual scene is constructed after de-multiplexing, decoding of bit streams, and scene composition. A receiver is allowed to manipulate the initial audio-visual scene presentation locally, or interactively arrange scene changes by sending requests to the server. A server may also choose to update the client with new streams and list of contents for user selection.

Small-size pedestrian detection in large scene based on fast R-CNN

NASA Astrophysics Data System (ADS)

Wang, Shengke; Yang, Na; Duan, Lianghua; Liu, Lu; Dong, Junyu

2018-04-01

Pedestrian detection is a canonical sub-problem of object detection with high demand during recent years. Although recent deep learning object detectors such as Fast/Faster R-CNN have shown excellent performance for general object detection, they have limited success for small size pedestrian detection in large-view scene. We study that the insufficient resolution of feature maps lead to the unsatisfactory accuracy when handling small instances. In this paper, we investigate issues involving Fast R-CNN for pedestrian detection. Driven by the observations, we propose a very simple but effective baseline for pedestrian detection based on Fast R-CNN, employing the DPM detector to generate proposals for accuracy, and training a fast R-CNN style network to jointly optimize small size pedestrian detection with skip connection concatenating feature from different layers to solving coarseness of feature maps. And the accuracy is improved in our research for small size pedestrian detection in the real large scene.

Mapping simulated scenes with skeletal remains using differential GPS in open environments: an assessment of accuracy and practicality.

PubMed

Walter, Brittany S; Schultz, John J

2013-05-10

Scene mapping is an integral aspect of processing a scene with scattered human remains. By utilizing the appropriate mapping technique, investigators can accurately document the location of human remains and maintain a precise geospatial record of evidence. One option that has not received much attention for mapping forensic evidence is the differential global positioning (DGPS) unit, as this technology now provides decreased positional error suitable for mapping scenes. Because of the lack of knowledge concerning this utility in mapping a scene, controlled research is necessary to determine the practicality of using newer and enhanced DGPS units in mapping scattered human remains. The purpose of this research was to quantify the accuracy of a DGPS unit for mapping skeletal dispersals and to determine the applicability of this utility in mapping a scene with dispersed remains. First, the accuracy of the DGPS unit in open environments was determined using known survey markers in open areas. Secondly, three simulated scenes exhibiting different types of dispersals were constructed and mapped in an open environment using the DGPS. Variables considered during data collection included the extent of the dispersal, data collection time, data collected on different days, and different postprocessing techniques. Data were differentially postprocessed and compared in a geographic information system (GIS) to evaluate the most efficient recordation methods. Results of this study demonstrate that the DGPS is a viable option for mapping dispersed human remains in open areas. The accuracy of collected point data was 11.52 and 9.55 cm for 50- and 100-s collection times, respectfully, and the orientation and maximum length of long bones was maintained. Also, the use of error buffers for point data of bones in maps demonstrated the error of the DGPS unit, while showing that the context of the dispersed skeleton was accurately maintained. Furthermore, the application of a DGPS for accurate scene mapping is discussed and guidelines concerning the implementation of this technology for mapping human scattered skeletal remains in open environments are provided. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

MODIS. Volume 2: MODIS level 1 geolocation, characterization and calibration algorithm theoretical basis document, version 1

NASA Technical Reports Server (NTRS)

Barker, John L.; Harnden, Joann M. K.; Montgomery, Harry; Anuta, Paul; Kvaran, Geir; Knight, ED; Bryant, Tom; Mckay, AL; Smid, Jon; Knowles, Dan, Jr.

1994-01-01

The EOS Moderate Resolution Imaging Spectrometer (MODIS) is being developed by NASA for flight on the Earth Observing System (EOS) series of satellites, the first of which (EOS-AM-1) is scheduled for launch in 1998. This document describes the algorithms and their theoretical basis for the MODIS Level 1B characterization, calibration, and geolocation algorithms which must produce radiometrically, spectrally, and spatially calibrated data with sufficient accuracy so that Global change research programs can detect minute changes in biogeophysical parameters. The document first describes the geolocation algorithm which determines geodetic latitude, longitude, and elevation of each MODIS pixel and the determination of geometric parameters for each observation (satellite zenith angle, satellite azimuth, range to the satellite, solar zenith angle, and solar azimuth). Next, the utilization of the MODIS onboard calibration sources, which consist of the Spectroradiometric Calibration Assembly (SRCA), Solar Diffuser (SD), Solar Diffuser Stability Monitor (SDSM), and the Blackbody (BB), is treated. Characterization of these sources and integration of measurements into the calibration process is described. Finally, the use of external sources, including the Moon, instrumented sites on the Earth (called vicarious calibration), and unsupervised normalization sites having invariant reflectance and emissive properties is treated. Finally, algorithms for generating utility masks needed for scene-based calibration are discussed. Eight appendices are provided, covering instrument design and additional algorithm details.

Successful Detection of Floods in Real Time Onboard EO1 Through NASA's ST6 Autonomous Sciencecraft Experiment (ASE)

NASA Astrophysics Data System (ADS)

Ip, F.; Dohm, J. M.; Baker, V. R.; Castano, R.; Cichy, B.; Chien, S.; Davies, A.; Doggett, T.; Greeley, R.

2004-12-01

For the first time, a spacecraft has the ability to autonomously detect and react to flood events. Flood detection and the investigation of flooding dynamics in real time from space have never been done before at least not until now. Part of the challenge for the hydrological community has been the difficulty of obtaining cloud-free scenes from orbit at sufficient temporal and spatial resolutions to accurately assess flooding. In addition, the large spatial extent of drainage networks coupled with the size of the data sets necessary to be downlinked from satellites add to the difficulty of monitoring flooding from space. Technology developed as part of the Autonomous Sciencecraft Experiment (ASE) creates the new capability to autonomously detect, assess, and react to dynamic events, thereby enabling the monitoring of transient processes such as flooding in real time. In addition to being able to autonomously process the imaged data onboard the spacecraft for the first time and search the data for specific spectral features, the ASE Science Team has developed and tested change detection algorithms for the Hyperion spectrometer on EO-1. For flood events, if a change is detected in the onboard processed image (i.e. an increase in the number of ¡wet¡" pixels relative to a baseline image where the system is in normal flow condition or relatively dry), the spacecraft is autonomously retasked to obtain additional scenes. For instance, in February 2004 a rare flooding of the Australian Diamantina River was captured by EO-1. In addition, in August during ASE onboard testing a Zambezi River scene in Central Africa was successfully triggered by the classifier to autonomously take another observation. Yet another successful trigger-response flooding test scenario of the Yellow River in China was captured by ASE on 8/18/04. These exciting results pave the way for future smart reconnaissance missions of transient processes on Earth and beyond. Acknowledgments: We are grateful to the City of Tucson and Tucson Water for their support and cooperation.

A new type of change blindness: smooth, isoluminant color changes are monitored on a coarse spatial scale.

PubMed

Goddard, Erin; Clifford, Colin W G

2013-04-22

Attending selectively to changes in our visual environment may help filter less important, unchanging information within a scene. Here, we demonstrate that color changes can go unnoticed even when they occur throughout an otherwise static image. The novelty of this demonstration is that it does not rely upon masking by a visual disruption or stimulus motion, nor does it require the change to be very gradual and restricted to a small section of the image. Using a two-interval, forced-choice change-detection task and an odd-one-out localization task, we showed that subjects were slowest to respond and least accurate (implying that change was hardest to detect) when the color changes were isoluminant, smoothly varying, and asynchronous with one another. This profound change blindness offers new constraints for theories of visual change detection, implying that, in the absence of transient signals, changes in color are typically monitored at a coarse spatial scale.

A comparison of moving object detection methods for real-time moving object detection

NASA Astrophysics Data System (ADS)

Roshan, Aditya; Zhang, Yun

2014-06-01

Moving object detection has a wide variety of applications from traffic monitoring, site monitoring, automatic theft identification, face detection to military surveillance. Many methods have been developed across the globe for moving object detection, but it is very difficult to find one which can work globally in all situations and with different types of videos. The purpose of this paper is to evaluate existing moving object detection methods which can be implemented in software on a desktop or laptop, for real time object detection. There are several moving object detection methods noted in the literature, but few of them are suitable for real time moving object detection. Most of the methods which provide for real time movement are further limited by the number of objects and the scene complexity. This paper evaluates the four most commonly used moving object detection methods as background subtraction technique, Gaussian mixture model, wavelet based and optical flow based methods. The work is based on evaluation of these four moving object detection methods using two (2) different sets of cameras and two (2) different scenes. The moving object detection methods have been implemented using MatLab and results are compared based on completeness of detected objects, noise, light change sensitivity, processing time etc. After comparison, it is observed that optical flow based method took least processing time and successfully detected boundary of moving objects which also implies that it can be implemented for real-time moving object detection.

A system for learning statistical motion patterns.

PubMed

Hu, Weiming; Xiao, Xuejuan; Fu, Zhouyu; Xie, Dan; Tan, Tieniu; Maybank, Steve

2006-09-01

Analysis of motion patterns is an effective approach for anomaly detection and behavior prediction. Current approaches for the analysis of motion patterns depend on known scenes, where objects move in predefined ways. It is highly desirable to automatically construct object motion patterns which reflect the knowledge of the scene. In this paper, we present a system for automatically learning motion patterns for anomaly detection and behavior prediction based on a proposed algorithm for robustly tracking multiple objects. In the tracking algorithm, foreground pixels are clustered using a fast accurate fuzzy K-means algorithm. Growing and prediction of the cluster centroids of foreground pixels ensure that each cluster centroid is associated with a moving object in the scene. In the algorithm for learning motion patterns, trajectories are clustered hierarchically using spatial and temporal information and then each motion pattern is represented with a chain of Gaussian distributions. Based on the learned statistical motion patterns, statistical methods are used to detect anomalies and predict behaviors. Our system is tested using image sequences acquired, respectively, from a crowded real traffic scene and a model traffic scene. Experimental results show the robustness of the tracking algorithm, the efficiency of the algorithm for learning motion patterns, and the encouraging performance of algorithms for anomaly detection and behavior prediction.

A rain pixel recovery algorithm for videos with highly dynamic scenes.

PubMed

Jie Chen; Lap-Pui Chau

2014-03-01

Rain removal is a very useful and important technique in applications such as security surveillance and movie editing. Several rain removal algorithms have been proposed these years, where photometric, chromatic, and probabilistic properties of the rain have been exploited to detect and remove the rainy effect. Current methods generally work well with light rain and relatively static scenes, when dealing with heavier rainfall in dynamic scenes, these methods give very poor visual results. The proposed algorithm is based on motion segmentation of dynamic scene. After applying photometric and chromatic constraints for rain detection, rain removal filters are applied on pixels such that their dynamic property as well as motion occlusion clue are considered; both spatial and temporal informations are then adaptively exploited during rain pixel recovery. Results show that the proposed algorithm has a much better performance for rainy scenes with large motion than existing algorithms.

Extension Scripts to caffe for Running COWC Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mundhenk, T. Nathan; Konjevod, Goran; Sakla, Wesam A.

2016-07-14

These are scripts In python whlch extend the functlonallty of the open source software Caffe and allow 1t to scan an overhead scene of Images and detect or count cars from that scene. tt returns the number of cars or the location of cars as a marked scene lmase.

False predictions about the detectability of visual changes: the role of beliefs about attention, memory, and the continuity of attended objects in causing change blindness blindness.

PubMed

Levin, Daniel T; Drivdahl, Sarah B; Momen, Nausheen; Beck, Melissa R

2002-12-01

Recently, a number of experiments have emphasized the degree to which subjects fail to detect large changes in visual scenes. This finding, referred to as "change blindness," is often considered surprising because many people have the intuition that such changes should be easy to detect. documented this intuition by showing that the majority of subjects believe they would notice changes that are actually very rarely detected. Thus subjects exhibit a metacognitive error we refer to as "change blindness blindness." Here, we test whether CBB is caused by a misestimation of the perceptual experience associated with visual changes and show that it persists even when the pre- and postchange views are separated by long delays. In addition, subjects overestimate their change detection ability both when the relevant changes are illustrated by still pictures, and when they are illustrated using videos showing the changes occurring in real time. We conclude that CBB is a robust phenomenon that cannot be accounted for by failure to understand the specific perceptual experience associated with a change. Copyright 2002 Elsevier Science (USA)

Feature diagnosticity and task context shape activity in human scene-selective cortex.

PubMed

Lowe, Matthew X; Gallivan, Jason P; Ferber, Susanne; Cant, Jonathan S

2016-01-15

Scenes are constructed from multiple visual features, yet previous research investigating scene processing has often focused on the contributions of single features in isolation. In the real world, features rarely exist independently of one another and likely converge to inform scene identity in unique ways. Here, we utilize fMRI and pattern classification techniques to examine the interactions between task context (i.e., attend to diagnostic global scene features; texture or layout) and high-level scene attributes (content and spatial boundary) to test the novel hypothesis that scene-selective cortex represents multiple visual features, the importance of which varies according to their diagnostic relevance across scene categories and task demands. Our results show for the first time that scene representations are driven by interactions between multiple visual features and high-level scene attributes. Specifically, univariate analysis of scene-selective cortex revealed that task context and feature diagnosticity shape activity differentially across scene categories. Examination using multivariate decoding methods revealed results consistent with univariate findings, but also evidence for an interaction between high-level scene attributes and diagnostic visual features within scene categories. Critically, these findings suggest visual feature representations are not distributed uniformly across scene categories but are shaped by task context and feature diagnosticity. Thus, we propose that scene-selective cortex constructs a flexible representation of the environment by integrating multiple diagnostically relevant visual features, the nature of which varies according to the particular scene being perceived and the goals of the observer. Copyright © 2015 Elsevier Inc. All rights reserved.

Contributions of low- and high-level properties to neural processing of visual scenes in the human brain.

PubMed

Groen, Iris I A; Silson, Edward H; Baker, Chris I

2017-02-19

Visual scene analysis in humans has been characterized by the presence of regions in extrastriate cortex that are selectively responsive to scenes compared with objects or faces. While these regions have often been interpreted as representing high-level properties of scenes (e.g. category), they also exhibit substantial sensitivity to low-level (e.g. spatial frequency) and mid-level (e.g. spatial layout) properties, and it is unclear how these disparate findings can be united in a single framework. In this opinion piece, we suggest that this problem can be resolved by questioning the utility of the classical low- to high-level framework of visual perception for scene processing, and discuss why low- and mid-level properties may be particularly diagnostic for the behavioural goals specific to scene perception as compared to object recognition. In particular, we highlight the contributions of low-level vision to scene representation by reviewing (i) retinotopic biases and receptive field properties of scene-selective regions and (ii) the temporal dynamics of scene perception that demonstrate overlap of low- and mid-level feature representations with those of scene category. We discuss the relevance of these findings for scene perception and suggest a more expansive framework for visual scene analysis.This article is part of the themed issue 'Auditory and visual scene analysis'. © 2017 The Author(s).

Contributions of low- and high-level properties to neural processing of visual scenes in the human brain

PubMed Central

2017-01-01

Visual scene analysis in humans has been characterized by the presence of regions in extrastriate cortex that are selectively responsive to scenes compared with objects or faces. While these regions have often been interpreted as representing high-level properties of scenes (e.g. category), they also exhibit substantial sensitivity to low-level (e.g. spatial frequency) and mid-level (e.g. spatial layout) properties, and it is unclear how these disparate findings can be united in a single framework. In this opinion piece, we suggest that this problem can be resolved by questioning the utility of the classical low- to high-level framework of visual perception for scene processing, and discuss why low- and mid-level properties may be particularly diagnostic for the behavioural goals specific to scene perception as compared to object recognition. In particular, we highlight the contributions of low-level vision to scene representation by reviewing (i) retinotopic biases and receptive field properties of scene-selective regions and (ii) the temporal dynamics of scene perception that demonstrate overlap of low- and mid-level feature representations with those of scene category. We discuss the relevance of these findings for scene perception and suggest a more expansive framework for visual scene analysis. This article is part of the themed issue ‘Auditory and visual scene analysis’. PMID:28044013

Nonexplicit change detection in complex dynamic settings: what eye movements reveal.

PubMed

Vachon, François; Vallières, Benoît R; Jones, Dylan M; Tremblay, Sébastien

2012-12-01

We employed a computer-controlled command-and-control (C2) simulation and recorded eye movements to examine the extent and nature of the inability to detect critical changes in dynamic displays when change detection is implicit (i.e., requires no explicit report) to the operator's task. Change blindness-the failure to notice significant changes to a visual scene-may have dire consequences on performance in C2 and surveillance operations. Participants performed a radar-based risk-assessment task involving multiple subtasks. Although participants were not required to explicitly report critical changes to the operational display, change detection was critical in informing decision making. Participants' eye movements were used as an index of visual attention across the display. Nonfixated (i.e., unattended) changes were more likely to be missed than were fixated (i.e., attended) changes, supporting the idea that focused attention is necessary for conscious change detection. The finding of significant pupil dilation for changes undetected but fixated suggests that attended changes can nonetheless be missed because of a failure of attentional processes. Change blindness in complex dynamic displays takes the form of failures in establishing task-appropriate patterns of attentional allocation. These findings have implications in the design of change-detection support tools for dynamic displays and work procedure in C2 and surveillance.

Thermal bioaerosol cloud tracking with Bayesian classification

NASA Astrophysics Data System (ADS)

Smith, Christian W.; Dupuis, Julia R.; Schundler, Elizabeth C.; Marinelli, William J.

2017-05-01

The development of a wide area, bioaerosol early warning capability employing existing uncooled thermal imaging systems used for persistent perimeter surveillance is discussed. The capability exploits thermal imagers with other available data streams including meteorological data and employs a recursive Bayesian classifier to detect, track, and classify observed thermal objects with attributes consistent with a bioaerosol plume. Target detection is achieved based on similarity to a phenomenological model which predicts the scene-dependent thermal signature of bioaerosol plumes. Change detection in thermal sensor data is combined with local meteorological data to locate targets with the appropriate thermal characteristics. Target motion is tracked utilizing a Kalman filter and nearly constant velocity motion model for cloud state estimation. Track management is performed using a logic-based upkeep system, and data association is accomplished using a combinatorial optimization technique. Bioaerosol threat classification is determined using a recursive Bayesian classifier to quantify the threat probability of each tracked object. The classifier can accept additional inputs from visible imagers, acoustic sensors, and point biological sensors to improve classification confidence. This capability was successfully demonstrated for bioaerosol simulant releases during field testing at Dugway Proving Grounds. Standoff detection at a range of 700m was achieved for as little as 500g of anthrax simulant. Developmental test results will be reviewed for a range of simulant releases, and future development and transition plans for the bioaerosol early warning platform will be discussed.

Supporting dynamic change detection: using the right tool for the task.

PubMed

Vallières, Benoît R; Hodgetts, Helen M; Vachon, François; Tremblay, Sébastien

2016-01-01

Detecting task-relevant changes in a visual scene is necessary for successfully monitoring and managing dynamic command and control situations. Change blindness-the failure to notice visual changes-is an important source of human error. Change History EXplicit (CHEX) is a tool developed to aid change detection and maintain situation awareness; and in the current study we test the generality of its ability to facilitate the detection of changes when this subtask is embedded within a broader dynamic decision-making task. A multitasking air-warfare simulation required participants to perform radar-based subtasks, for which change detection was a necessary aspect of the higher-order goal of protecting one's own ship. In this task, however, CHEX rendered the operator even more vulnerable to attentional failures in change detection and increased perceived workload. Such support was only effective when participants performed a change detection task without concurrent subtasks. Results are interpreted in terms of the NSEEV model of attention behavior (Steelman, McCarley, & Wickens, Hum. Factors 53:142-153, 2011; J. Exp. Psychol. Appl. 19:403-419, 2013), and suggest that decision aids for use in multitasking contexts must be designed to fit within the available workload capacity of the user so that they may truly augment cognition.

Landsat imagery and its treatment in a publicly available data portal to monitor flow velocity variations of Greenland outlet glaciers

NASA Astrophysics Data System (ADS)

Scheinert, M.; Rosenau, R.; Ebermann, B.; Horwath, M.

2016-12-01

Utilizing the freely available Landsat archive we have set up a monitoring system to process and provide flow-velocity fields for more than 300 outlet glaciers along the margin of the Greenland ice sheet. We will present major processing steps. These include, among others, an improved orthorectification that is based on the Global Digital Elevation Map V2 (GDEM-V2) of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER). For those Landsat 7 products which feature the scan line corrector (SLC) failure a destriping correction was applied. An adaptive, recursive filter approach was applied in order to remove outliers. Altogether, the enhanced processing leads to a higher accuracy of the flow-velocity fields. By mid-2016 we succeeded in incorporating more than 37,000 optical multi-sensoral scenes from Landsat 1 to 8. These scenes cover the period from 1972 to 2015. Until now, for almost 300 glaciers we processed more than 100,000 flow-velocity fields for the time span until 2012. For the time until 2015 velocity fields were inferred only for the fastest flowing glaciers. However, new recordings of Landsat 7 and Landsat 8 as well as the availability of further scenes through the Landsat Global Archive Consolidation (LGAC) effort will help to enlarge the database. With a further quality check, we can provide more than 40,000 flow-velocity for public accessibility. More products will be added continuously while the almost automated processing is ongoing. The long time span enables to determine trends of the flow velocity over different (long) periods. A major achievement can be seen in the fact that a high temporal resolution facilitates the analysis of seasonal flow-velocity variations. We will discuss prominent examples of the non-uniform pattern of ice flow velocity changes. For this, a powerful tool is provided by the monitoring system and its web-based data portal. It allows to study the flow-velocity changes in time and space, and to possibly identify distinctive patterns. Rapid changes like surge events can be detected and analyzed in detail. The presentation will demonstrate how the data portal enables to interactively perform the calculation of profiles or time series for locations the user can select on the map. Also, the user can choose from different options to download the examined data.

An intelligent crowdsourcing system for forensic analysis of surveillance video

NASA Astrophysics Data System (ADS)

Tahboub, Khalid; Gadgil, Neeraj; Ribera, Javier; Delgado, Blanca; Delp, Edward J.

2015-03-01

Video surveillance systems are of a great value for public safety. With an exponential increase in the number of cameras, videos obtained from surveillance systems are often archived for forensic purposes. Many automatic methods have been proposed to do video analytics such as anomaly detection and human activity recognition. However, such methods face significant challenges due to object occlusions, shadows and scene illumination changes. In recent years, crowdsourcing has become an effective tool that utilizes human intelligence to perform tasks that are challenging for machines. In this paper, we present an intelligent crowdsourcing system for forensic analysis of surveillance video that includes the video recorded as a part of search and rescue missions and large-scale investigation tasks. We describe a method to enhance crowdsourcing by incorporating human detection, re-identification and tracking. At the core of our system, we use a hierarchal pyramid model to distinguish the crowd members based on their ability, experience and performance record. Our proposed system operates in an autonomous fashion and produces a final output of the crowdsourcing analysis consisting of a set of video segments detailing the events of interest as one storyline.

Infrared Thermal Imaging System on a Mobile Phone

PubMed Central

Lee, Fu-Feng; Chen, Feng; Liu, Jing

2015-01-01

A novel concept towards pervasively available low-cost infrared thermal imaging system lunched on a mobile phone (MTIS) was proposed and demonstrated in this article. Through digestion on the evolutional development of milestone technologies in the area, it can be found that the portable and low-cost design would become the main stream of thermal imager for civilian purposes. As a representative trial towards this important goal, a MTIS consisting of a thermal infrared module (TIM) and mobile phone with embedded exclusive software (IRAPP) was presented. The basic strategy for the TIM construction is illustrated, including sensor adoption and optical specification. The user-oriented software was developed in the Android environment by considering its popularity and expandability. Computational algorithms with non-uniformity correction and scene-change detection are established to optimize the imaging quality and efficiency of TIM. The performance experiments and analysis indicated that the currently available detective distance for the MTIS is about 29 m. Furthermore, some family-targeted utilization enabled by MTIS was also outlined, such as sudden infant death syndrome (SIDS) prevention, etc. This work suggests a ubiquitous way of significantly extending thermal infrared image into rather wide areas especially health care in the coming time. PMID:25942639

Thematic Mapper Data Quality and Performance Assessment in Renewable Resources/agriculture Remote Sensing

NASA Technical Reports Server (NTRS)

Bizzell, R. M.; Prior, H. L.

1984-01-01

It is believed that the increased spatial resolution will provide solutions to proportion estimation error due to mixed pixels, and the increased spectral resolution will provide for the identification of important agricultural features such as crop stage, and condition. The results of analyses conducted relative to these hypothesis from sample segments extracted from the 4-band Detroit scene and the 7-band Mississippi County, Arkansas engineering test scene are described. Several studies were conducted to evaluate the geometric and radiometric performance of the TM to determine data viability for the more pertinent investigations of TM utility. In most cases this requirement was more than sufficiently satisfied. This allowed the opportunity to take advantage of detailed ground observations for several of the sample segments to assess class separability and detection of other important features with TM. The results presented regarding these TM characteristics show that not only is the increased definition of the within scene variance captured by the increased spatial and spectral resolution, but that the mid-IR bands (5 and 7) are necessary for optimum crop type classification. Both qualitative and quantitative results are presented that describe the improvements gained with the TM both relative to the MSS and on its own merit.

Violence detection based on histogram of optical flow orientation

NASA Astrophysics Data System (ADS)

Yang, Zhijie; Zhang, Tao; Yang, Jie; Wu, Qiang; Bai, Li; Yao, Lixiu

2013-12-01

In this paper, we propose a novel approach for violence detection and localization in a public scene. Currently, violence detection is considerably under-researched compared with the common action recognition. Although existing methods can detect the presence of violence in a video, they cannot precisely locate the regions in the scene where violence is happening. This paper will tackle the challenge and propose a novel method to locate the violence location in the scene, which is important for public surveillance. The Gaussian Mixed Model is extended into the optical flow domain in order to detect candidate violence regions. In each region, a new descriptor, Histogram of Optical Flow Orientation (HOFO), is proposed to measure the spatial-temporal features. A linear SVM is trained based on the descriptor. The performance of the method is demonstrated on the publicly available data sets, BEHAVE and CAVIAR.

Text String Detection from Natural Scenes by Structure-based Partition and Grouping

PubMed Central

Yi, Chucai; Tian, YingLi

2012-01-01

Text information in natural scene images serves as important clues for many image-based applications such as scene understanding, content-based image retrieval, assistive navigation, and automatic geocoding. However, locating text from complex background with multiple colors is a challenging task. In this paper, we explore a new framework to detect text strings with arbitrary orientations in complex natural scene images. Our proposed framework of text string detection consists of two steps: 1) Image partition to find text character candidates based on local gradient features and color uniformity of character components. 2) Character candidate grouping to detect text strings based on joint structural features of text characters in each text string such as character size differences, distances between neighboring characters, and character alignment. By assuming that a text string has at least three characters, we propose two algorithms of text string detection: 1) adjacent character grouping method, and 2) text line grouping method. The adjacent character grouping method calculates the sibling groups of each character candidate as string segments and then merges the intersecting sibling groups into text string. The text line grouping method performs Hough transform to fit text line among the centroids of text candidates. Each fitted text line describes the orientation of a potential text string. The detected text string is presented by a rectangle region covering all characters whose centroids are cascaded in its text line. To improve efficiency and accuracy, our algorithms are carried out in multi-scales. The proposed methods outperform the state-of-the-art results on the public Robust Reading Dataset which contains text only in horizontal orientation. Furthermore, the effectiveness of our methods to detect text strings with arbitrary orientations is evaluated on the Oriented Scene Text Dataset collected by ourselves containing text strings in non-horizontal orientations. PMID:21411405

Text string detection from natural scenes by structure-based partition and grouping.

PubMed

Yi, Chucai; Tian, YingLi

2011-09-01

Text information in natural scene images serves as important clues for many image-based applications such as scene understanding, content-based image retrieval, assistive navigation, and automatic geocoding. However, locating text from a complex background with multiple colors is a challenging task. In this paper, we explore a new framework to detect text strings with arbitrary orientations in complex natural scene images. Our proposed framework of text string detection consists of two steps: 1) image partition to find text character candidates based on local gradient features and color uniformity of character components and 2) character candidate grouping to detect text strings based on joint structural features of text characters in each text string such as character size differences, distances between neighboring characters, and character alignment. By assuming that a text string has at least three characters, we propose two algorithms of text string detection: 1) adjacent character grouping method and 2) text line grouping method. The adjacent character grouping method calculates the sibling groups of each character candidate as string segments and then merges the intersecting sibling groups into text string. The text line grouping method performs Hough transform to fit text line among the centroids of text candidates. Each fitted text line describes the orientation of a potential text string. The detected text string is presented by a rectangle region covering all characters whose centroids are cascaded in its text line. To improve efficiency and accuracy, our algorithms are carried out in multi-scales. The proposed methods outperform the state-of-the-art results on the public Robust Reading Dataset, which contains text only in horizontal orientation. Furthermore, the effectiveness of our methods to detect text strings with arbitrary orientations is evaluated on the Oriented Scene Text Dataset collected by ourselves containing text strings in nonhorizontal orientations.

Motion detection and compensation in infrared retinal image sequences.

PubMed

Scharcanski, J; Schardosim, L R; Santos, D; Stuchi, A

2013-01-01

Infrared image data captured by non-mydriatic digital retinography systems often are used in the diagnosis and treatment of the diabetic macular edema (DME). Infrared illumination is less aggressive to the patient retina, and retinal studies can be carried out without pupil dilation. However, sequences of infrared eye fundus images of static scenes, tend to present pixel intensity fluctuations in time, and noisy and background illumination changes pose a challenge to most motion detection methods proposed in the literature. In this paper, we present a retinal motion detection method that is adaptive to background noise and illumination changes. Our experimental results indicate that this method is suitable for detecting retinal motion in infrared image sequences, and compensate the detected motion, which is relevant in retinal laser treatment systems for DME. Copyright © 2013 Elsevier Ltd. All rights reserved.

Infrared small target detection in heavy sky scene clutter based on sparse representation

NASA Astrophysics Data System (ADS)

Liu, Depeng; Li, Zhengzhou; Liu, Bing; Chen, Wenhao; Liu, Tianmei; Cao, Lei

2017-09-01

A novel infrared small target detection method based on sky clutter and target sparse representation is proposed in this paper to cope with the representing uncertainty of clutter and target. The sky scene background clutter is described by fractal random field, and it is perceived and eliminated via the sparse representation on fractal background over-complete dictionary (FBOD). The infrared small target signal is simulated by generalized Gaussian intensity model, and it is expressed by the generalized Gaussian target over-complete dictionary (GGTOD), which could describe small target more efficiently than traditional structured dictionaries. Infrared image is decomposed on the union of FBOD and GGTOD, and the sparse representation energy that target signal and background clutter decomposed on GGTOD differ so distinctly that it is adopted to distinguish target from clutter. Some experiments are induced and the experimental results show that the proposed approach could improve the small target detection performance especially under heavy clutter for background clutter could be efficiently perceived and suppressed by FBOD and the changing target could also be represented accurately by GGTOD.

Detecting changes in real-world objects: The relationship between visual long-term memory and change blindness.

PubMed

Brady, Timothy F; Konkle, Talia; Oliva, Aude; Alvarez, George A

2009-01-01

A large body of literature has shown that observers often fail to notice significant changes in visual scenes, even when these changes happen right in front of their eyes. For instance, people often fail to notice if their conversation partner is switched to another person, or if large background objects suddenly disappear.1,2 These 'change blindness' studies have led to the inference that the amount of information we remember about each item in a visual scene may be quite low.1 However, in recent work we have demonstrated that long-term memory is capable of storing a massive number of visual objects with significant detail about each item.3 In the present paper we attempt to reconcile these findings by demonstrating that observers do not experience 'change blindness' with the real world objects used in our previous experiment if they are given sufficient time to encode each item. The results reported here suggest that one of the major causes of change blindness for real-world objects is a lack of encoding time or attention to each object (see also refs. 4 and 5).

The utility of polarimetry within passive military imaging systems

NASA Astrophysics Data System (ADS)

Hickman, Duncan L.; Smith, Moira I.; Kim, Kyung Su; Choi, Hyun-Jin

2017-10-01

An ongoing challenge for many military imaging systems is the detection and classification of weak target signatures in a cluttered environment. In such cases, the use of image contrast and relative target motion alone does not always provide a sufficient level of target discrimination to give operational confidence and it is therefore necessary to consider the use of other discriminatory scene information. Polarisation is one such source of information and this paper reports on an extensive series of polarimetric trials undertaken across the visible, NIR, SWIR, MWIR and LWIR spectral bands. Using this data, the benefits and limitations of polarisation discrimination are reviewed in the context of practical military scenarios. It is shown that polarisation signatures vary with viewing geometry and atmospheric conditions. This would lead to an unpredictable performance level if the sensor discrimination was based solely on polarisation. However, by carefully combining polarisation with other scene information, useful operational benefits can be obtained and this is illustrated through a consideration of different data fusion approaches.

Forensic identification of blood in the presence of contaminations using Raman microspectroscopy coupled with advanced statistics: effect of sand, dust, and soil.

PubMed

Sikirzhytskaya, Aliaksandra; Sikirzhytski, Vitali; McLaughlin, Gregory; Lednev, Igor K

2013-09-01

Body fluid traces recovered at crime scenes are among the most common and important types of forensic evidence. However, the ability to characterize a biological stain at a crime scene nondestructively has not yet been demonstrated. Here, we expand the Raman spectroscopic approach for the identification of dry traces of pure body fluids to address the problem of heterogeneous contamination, which can impair the performance of conventional methods. The concept of multidimensional Raman signatures was utilized for the identification of blood in dry traces contaminated with sand, dust, and soil. Multiple Raman spectra were acquired from the samples via automatic scanning, and the contribution of blood was evaluated through the fitting quality using spectroscopic signature components. The spatial mapping technique allowed for detection of "hot spots" dominated by blood contribution. The proposed method has great potential for blood identification in highly contaminated samples. © 2013 American Academy of Forensic Sciences.

Rendering visual events as sounds: Spatial attention capture by auditory augmented reality.

PubMed

Stone, Scott A; Tata, Matthew S

2017-01-01

Many salient visual events tend to coincide with auditory events, such as seeing and hearing a car pass by. Information from the visual and auditory senses can be used to create a stable percept of the stimulus. Having access to related coincident visual and auditory information can help for spatial tasks such as localization. However not all visual information has analogous auditory percepts, such as viewing a computer monitor. Here, we describe a system capable of detecting and augmenting visual salient events into localizable auditory events. The system uses a neuromorphic camera (DAVIS 240B) to detect logarithmic changes of brightness intensity in the scene, which can be interpreted as salient visual events. Participants were blindfolded and asked to use the device to detect new objects in the scene, as well as determine direction of motion for a moving visual object. Results suggest the system is robust enough to allow for the simple detection of new salient stimuli, as well accurately encoding direction of visual motion. Future successes are probable as neuromorphic devices are likely to become faster and smaller in the future, making this system much more feasible.

Rendering visual events as sounds: Spatial attention capture by auditory augmented reality

PubMed Central

Tata, Matthew S.

2017-01-01

Many salient visual events tend to coincide with auditory events, such as seeing and hearing a car pass by. Information from the visual and auditory senses can be used to create a stable percept of the stimulus. Having access to related coincident visual and auditory information can help for spatial tasks such as localization. However not all visual information has analogous auditory percepts, such as viewing a computer monitor. Here, we describe a system capable of detecting and augmenting visual salient events into localizable auditory events. The system uses a neuromorphic camera (DAVIS 240B) to detect logarithmic changes of brightness intensity in the scene, which can be interpreted as salient visual events. Participants were blindfolded and asked to use the device to detect new objects in the scene, as well as determine direction of motion for a moving visual object. Results suggest the system is robust enough to allow for the simple detection of new salient stimuli, as well accurately encoding direction of visual motion. Future successes are probable as neuromorphic devices are likely to become faster and smaller in the future, making this system much more feasible. PMID:28792518

Remote sensing depth invariant index parameters in shallow benthic habitats for bottom type classification.

NASA Astrophysics Data System (ADS)

Gapper, J.; El-Askary, H. M.; Linstead, E.

2017-12-01

Ground cover prediction of benthic habitats using remote sensing imagery requires substantial feature engineering. Artifacts that confound the ground cover characteristics must be severely reduced or eliminated while the distinguishing features must be exposed. In particular, the impact of wavelength attenuation in the water column means that a machine learning algorithm will primarily detect depth. However, the per pixel depths are difficult to know on a grand scale. Previous research has taken an in situ approach to applying depth invariant index on a small area of interest within a Landsat 8 scene. We aim to abstract this process for application to entire Landsat scene as well as other locations in order to study change detection in shallow benthic zones on a global scale. We have developed a methodology and applied it to more than 25 different Landsat 8 scenes. The images were first preprocessed to mask land, clouds, and other distortions then atmospheric correction via dark pixel subtraction was applied. Finally, depth invariant indices were calculated for each location and associated parameters recorded. Findings showed how robust the resulting parameters (deep-water radiance, depth invariant constant, band radiance variance/covariance, and ratio of attenuation) were across all scenes. We then created false color composite images of the depth invariant indices for each location. We noted several artifacts within some sites in the form of patterns or striations that did not appear to be aligned with variations in subsurface ground cover types. Further research into depth surveys for these sites revealed depths consistent with one or more wavelengths fully attenuating. This result showed that our model framework is generalizing well but limited to the penetration depths due to wavelength attenuation. Finally, we compared the parameters associated with the depth invariant calculation which were consistent across most scenes and explained any outliers observed. We concluded that the depth invariant index framework can be deployed on a large scale for ground cover detection in shallow waters (less than 16.8m or 5.2m for three DII measurements).

A FPGA-based architecture for real-time image matching

NASA Astrophysics Data System (ADS)

Wang, Jianhui; Zhong, Sheng; Xu, Wenhui; Zhang, Weijun; Cao, Zhiguo

2013-10-01

Image matching is a fundamental task in computer vision. It is used to establish correspondence between two images taken at different viewpoint or different time from the same scene. However, its large computational complexity has been a challenge to most embedded systems. This paper proposes a single FPGA-based image matching system, which consists of SIFT feature detection, BRIEF descriptor extraction and BRIEF matching. It optimizes the FPGA architecture for the SIFT feature detection to reduce the FPGA resources utilization. Moreover, we implement BRIEF description and matching on FPGA also. The proposed system can implement image matching at 30fps (frame per second) for 1280x720 images. Its processing speed can meet the demand of most real-life computer vision applications.

High-resolution three-dimensional imaging with compress sensing

NASA Astrophysics Data System (ADS)

Wang, Jingyi; Ke, Jun

2016-10-01

LIDAR three-dimensional imaging technology have been used in many fields, such as military detection. However, LIDAR require extremely fast data acquisition speed. This makes the manufacture of detector array for LIDAR system is very difficult. To solve this problem, we consider using compress sensing which can greatly decrease the data acquisition and relax the requirement of a detection device. To use the compressive sensing idea, a spatial light modulator will be used to modulate the pulsed light source. Then a photodetector is used to receive the reflected light. A convex optimization problem is solved to reconstruct the 2D depth map of the object. To improve the resolution in transversal direction, we use multiframe image restoration technology. For each 2D piecewise-planar scene, we move the SLM half-pixel each time. Then the position where the modulated light illuminates will changed accordingly. We repeat moving the SLM to four different directions. Then we can get four low-resolution depth maps with different details of the same plane scene. If we use all of the measurements obtained by the subpixel movements, we can reconstruct a high-resolution depth map of the sense. A linear minimum-mean-square error algorithm is used for the reconstruction. By combining compress sensing and multiframe image restoration technology, we reduce the burden on data analyze and improve the efficiency of detection. More importantly, we obtain high-resolution depth maps of a 3D scene.

Large Area Crop Inventory Experiment (LACIE). Detection of episodic phenomena on LANDSAT imagery. [Kansas

NASA Technical Reports Server (NTRS)

Chesnutwood, C. M. (Principal Investigator)

1976-01-01

The author has identified the following significant results. Episodic phenomena such as rainfall shortly before data pass, thin translucent clouds, cloud shadows, and aircraft condensation trails and their shadows are responsible for changes in the spectral reflectivities of some surfaces. These changes are readily detected on LANDSAT full-frame imagery. Histograms of selected areas in Kansas show a distinct decrease in mean radiance values, but also, an increase in scene contrast, in areas where recent rains had occurred. Histograms from a few individual fields indicate that the mean radiance values for winter wheat followed a different trend after a rainfall than alfalfa or grasses.

How do visual and postural cues combine for self-tilt perception during slow pitch rotations?

PubMed

Scotto Di Cesare, C; Buloup, F; Mestre, D R; Bringoux, L

2014-11-01

Self-orientation perception relies on the integration of multiple sensory inputs which convey spatially-related visual and postural cues. In the present study, an experimental set-up was used to tilt the body and/or the visual scene to investigate how these postural and visual cues are integrated for self-tilt perception (the subjective sensation of being tilted). Participants were required to repeatedly rate a confidence level for self-tilt perception during slow (0.05°·s(-1)) body and/or visual scene pitch tilts up to 19° relative to vertical. Concurrently, subjects also had to perform arm reaching movements toward a body-fixed target at certain specific angles of tilt. While performance of a concurrent motor task did not influence the main perceptual task, self-tilt detection did vary according to the visuo-postural stimuli. Slow forward or backward tilts of the visual scene alone did not induce a marked sensation of self-tilt contrary to actual body tilt. However, combined body and visual scene tilt influenced self-tilt perception more strongly, although this effect was dependent on the direction of visual scene tilt: only a forward visual scene tilt combined with a forward body tilt facilitated self-tilt detection. In such a case, visual scene tilt did not seem to induce vection but rather may have produced a deviation of the perceived orientation of the longitudinal body axis in the forward direction, which may have lowered the self-tilt detection threshold during actual forward body tilt. Copyright © 2014 Elsevier B.V. All rights reserved.

Scene recognition following locomotion around a scene.

PubMed

Motes, Michael A; Finlay, Cory A; Kozhevnikov, Maria

2006-01-01

Effects of locomotion on scene-recognition reaction time (RT) and accuracy were studied. In experiment 1, observers memorized an 11-object scene and made scene-recognition judgments on subsequently presented scenes from the encoded view or different views (ie scenes were rotated or observers moved around the scene, both from 40 degrees to 360 degrees). In experiment 2, observers viewed different 5-object scenes on each trial and made scene-recognition judgments from the encoded view or after moving around the scene, from 36 degrees to 180 degrees. Across experiments, scene-recognition RT increased (in experiment 2 accuracy decreased) with angular distance between encoded and judged views, regardless of how the viewpoint changes occurred. The findings raise questions about conditions in which locomotion produces spatially updated representations of scenes.

Conscious visual memory with minimal attention.

PubMed

Pinto, Yair; Vandenbroucke, Annelinde R; Otten, Marte; Sligte, Ilja G; Seth, Anil K; Lamme, Victor A F

2017-02-01

Is conscious visual perception limited to the locations that a person attends? The remarkable phenomenon of change blindness, which shows that people miss nearly all unattended changes in a visual scene, suggests the answer is yes. However, change blindness is found after visual interference (a mask or a new scene), so that subjects have to rely on working memory (WM), which has limited capacity, to detect the change. Before such interference, however, a much larger capacity store, called fragile memory (FM), which is easily overwritten by newly presented visual information, is present. Whether these different stores depend equally on spatial attention is central to the debate on the role of attention in conscious vision. In 2 experiments, we found that minimizing spatial attention almost entirely erases visual WM, as expected. Critically, FM remains largely intact. Moreover, minimally attended FM responses yield accurate metacognition, suggesting that conscious memory persists with limited spatial attention. Together, our findings help resolve the fundamental issue of how attention affects perception: Both visual consciousness and memory can be supported by only minimal attention. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Image and Processing Models for Satellite Detection in Images Acquired by Space-based Surveillance-of-Space Sensors

DTIC Science & Technology

2010-09-01

external sources ‘L1’ like zodiacal light (or diffuse nebula ) or stray light ‘L2’ and these components change with the telescope pointing. Bk (T,t...Astronomical scene background (zodiacal light, diffuse nebulae , etc.). L2(P A(tk), t): Image background component caused by stray light. MS

Risk and safety perception on urban and rural roads: Effects of environmental features, driver age and risk sensitivity.

PubMed

Cox, Jolene A; Beanland, Vanessa; Filtness, Ashleigh J

2017-10-03

The ability to detect changing visual information is a vital component of safe driving. In addition to detecting changing visual information, drivers must also interpret its relevance to safety. Environmental changes considered to have high safety relevance will likely demand greater attention and more timely responses than those considered to have lower safety relevance. The aim of this study was to explore factors that are likely to influence perceptions of risk and safety regarding changing visual information in the driving environment. Factors explored were the environment in which the change occurs (i.e., urban vs. rural), the type of object that changes, and the driver's age, experience, and risk sensitivity. Sixty-three licensed drivers aged 18-70 years completed a hazard rating task, which required them to rate the perceived hazardousness of changing specific elements within urban and rural driving environments. Three attributes of potential hazards were systematically manipulated: the environment (urban, rural); the type of object changed (road sign, car, motorcycle, pedestrian, traffic light, animal, tree); and its inherent safety risk (low risk, high risk). Inherent safety risk was manipulated by either varying the object's placement, on/near or away from the road, or altering an infrastructure element that would require a change to driver behavior. Participants also completed two driving-related risk perception tasks, rating their relative crash risk and perceived risk of aberrant driving behaviors. Driver age was not significantly associated with hazard ratings, but individual differences in perceived risk of aberrant driving behaviors predicted hazard ratings, suggesting that general driving-related risk sensitivity plays a strong role in safety perception. In both urban and rural scenes, there were significant associations between hazard ratings and inherent safety risk, with low-risk changes perceived as consistently less hazardous than high-risk impact changes; however, the effect was larger for urban environments. There were also effects of object type, with certain objects rated as consistently more safety relevant. In urban scenes, changes involving pedestrians were rated significantly more hazardous than all other objects, and in rural scenes, changes involving animals were rated as significantly more hazardous. Notably, hazard ratings were found to be higher in urban compared with rural driving environments, even when changes were matched between environments. This study demonstrates that drivers perceive rural roads as less risky than urban roads, even when similar scenarios occur in both environments. Age did not affect hazard ratings. Instead, the findings suggest that the assessment of risk posed by hazards is influenced more by individual differences in risk sensitivity. This highlights the need for driver education to account for appraisal of hazards' risk and relevance, in addition to hazard detection, when considering factors that promote road safety.

Parallel detection of violations of color constancy

PubMed Central

Foster, David H.; Nascimento, Sérgio M. C.; Amano, Kinjiro; Arend, Larry; Linnell, Karina J.; Nieves, Juan Luis; Plet, Sabrina; Foster, Jeffrey S.

2001-01-01

The perceived colors of reflecting surfaces generally remain stable despite changes in the spectrum of the illuminating light. This color constancy can be measured operationally by asking observers to distinguish illuminant changes on a scene from changes in the reflecting properties of the surfaces comprising it. It is shown here that during fast illuminant changes, simultaneous changes in spectral reflectance of one or more surfaces in an array of other surfaces can be readily detected almost independent of the numbers of surfaces, suggesting a preattentive, spatially parallel process. This process, which is perfect over a spatial window delimited by the anatomical fovea, may form an early input to a multistage analysis of surface color, providing the visual system with information about a rapidly changing world in advance of the generation of a more elaborate and stable perceptual representation. PMID:11438751

Iconic memory requires attention

PubMed Central

Persuh, Marjan; Genzer, Boris; Melara, Robert D.

2012-01-01

Two experiments investigated whether attention plays a role in iconic memory, employing either a change detection paradigm (Experiment 1) or a partial-report paradigm (Experiment 2). In each experiment, attention was taxed during initial display presentation, focusing the manipulation on consolidation of information into iconic memory, prior to transfer into working memory. Observers were able to maintain high levels of performance (accuracy of change detection or categorization) even when concurrently performing an easy visual search task (low load). However, when the concurrent search was made difficult (high load), observers' performance dropped to almost chance levels, while search accuracy held at single-task levels. The effects of attentional load remained the same across paradigms. The results suggest that, without attention, participants consolidate in iconic memory only gross representations of the visual scene, information too impoverished for successful detection of perceptual change or categorization of features. PMID:22586389

Iconic memory requires attention.

PubMed

Persuh, Marjan; Genzer, Boris; Melara, Robert D

2012-01-01

Two experiments investigated whether attention plays a role in iconic memory, employing either a change detection paradigm (Experiment 1) or a partial-report paradigm (Experiment 2). In each experiment, attention was taxed during initial display presentation, focusing the manipulation on consolidation of information into iconic memory, prior to transfer into working memory. Observers were able to maintain high levels of performance (accuracy of change detection or categorization) even when concurrently performing an easy visual search task (low load). However, when the concurrent search was made difficult (high load), observers' performance dropped to almost chance levels, while search accuracy held at single-task levels. The effects of attentional load remained the same across paradigms. The results suggest that, without attention, participants consolidate in iconic memory only gross representations of the visual scene, information too impoverished for successful detection of perceptual change or categorization of features.

Experimental application of simulation tools for evaluating UAV video change detection

NASA Astrophysics Data System (ADS)

Saur, Günter; Bartelsen, Jan

2015-10-01

Change detection is one of the most important tasks when unmanned aerial vehicles (UAV) are used for video reconnaissance and surveillance. In this paper, we address changes on short time scale, i.e. the observations are taken within time distances of a few hours. Each observation is a short video sequence corresponding to the near-nadir overflight of the UAV above the interesting area and the relevant changes are e.g. recently added or removed objects. The change detection algorithm has to distinguish between relevant and non-relevant changes. Examples for non-relevant changes are versatile objects like trees and compression or transmission artifacts. To enable the usage of an automatic change detection within an interactive workflow of an UAV video exploitation system, an evaluation and assessment procedure has to be performed. Large video data sets which contain many relevant objects with varying scene background and altering influence parameters (e.g. image quality, sensor and flight parameters) including image metadata and ground truth data are necessary for a comprehensive evaluation. Since the acquisition of real video data is limited by cost and time constraints, from our point of view, the generation of synthetic data by simulation tools has to be considered. In this paper the processing chain of Saur et al. (2014) [1] and the interactive workflow for video change detection is described. We have selected the commercial simulation environment Virtual Battle Space 3 (VBS3) to generate synthetic data. For an experimental setup, an example scenario "road monitoring" has been defined and several video clips have been produced with varying flight and sensor parameters and varying objects in the scene. Image registration and change mask extraction, both components of the processing chain, are applied to corresponding frames of different video clips. For the selected examples, the images could be registered, the modelled changes could be extracted and the artifacts of the image rendering considered as noise (slight differences of heading angles, disparity of vegetation, 3D parallax) could be suppressed. We conclude that these image data could be considered to be realistic enough to serve as evaluation data for the selected processing components. Future work will extend the evaluation to other influence parameters and may include the human operator for mission planning and sensor control.

Enhanced change detection performance reveals improved strategy use in avid action video game players.

PubMed

Clark, Kait; Fleck, Mathias S; Mitroff, Stephen R

2011-01-01

Recent research has shown that avid action video game players (VGPs) outperform non-video game players (NVGPs) on a variety of attentional and perceptual tasks. However, it remains unknown exactly why and how such differences arise; while some prior research has demonstrated that VGPs' improvements stem from enhanced basic perceptual processes, other work indicates that they can stem from enhanced attentional control. The current experiment used a change-detection task to explore whether top-down strategies can contribute to VGPs' improved abilities. Participants viewed alternating presentations of an image and a modified version of the image and were tasked with detecting and localizing the changed element. Consistent with prior claims of enhanced perceptual abilities, VGPs were able to detect the changes while requiring less exposure to the change than NVGPs. Further analyses revealed this improved change detection performance may result from altered strategy use; VGPs employed broader search patterns when scanning scenes for potential changes. These results complement prior demonstrations of VGPs' enhanced bottom-up perceptual benefits by providing new evidence of VGPs' potentially enhanced top-down strategic benefits. Copyright © 2010 Elsevier B.V. All rights reserved.

Neural-net-based image matching

NASA Astrophysics Data System (ADS)

Jerebko, Anna K.; Barabanov, Nikita E.; Luciv, Vadim R.; Allinson, Nigel M.

2000-04-01

The paper describes a neural-based method for matching spatially distorted image sets. The matching of partially overlapping images is important in many applications-- integrating information from images formed from different spectral ranges, detecting changes in a scene and identifying objects of differing orientations and sizes. Our approach consists of extracting contour features from both images, describing the contour curves as sets of line segments, comparing these sets, determining the corresponding curves and their common reference points, calculating the image-to-image co-ordinate transformation parameters on the basis of the most successful variant of the derived curve relationships. The main steps are performed by custom neural networks. The algorithms describe in this paper have been successfully tested on a large set of images of the same terrain taken in different spectral ranges, at different seasons and rotated by various angles. In general, this experimental verification indicates that the proposed method for image fusion allows the robust detection of similar objects in noisy, distorted scenes where traditional approaches often fail.

Eye movements and attention in reading, scene perception, and visual search.

PubMed

Rayner, Keith

2009-08-01

Eye movements are now widely used to investigate cognitive processes during reading, scene perception, and visual search. In this article, research on the following topics is reviewed with respect to reading: (a) the perceptual span (or span of effective vision), (b) preview benefit, (c) eye movement control, and (d) models of eye movements. Related issues with respect to eye movements during scene perception and visual search are also reviewed. It is argued that research on eye movements during reading has been somewhat advanced over research on eye movements in scene perception and visual search and that some of the paradigms developed to study reading should be more widely adopted in the study of scene perception and visual search. Research dealing with "real-world" tasks and research utilizing the visual-world paradigm are also briefly discussed.

Updating the 2001 National Land Cover Database Impervious Surface Products to 2006 using Landsat imagery change detection methods

USGS Publications Warehouse

Xian, George; Homer, Collin G.

2010-01-01

A prototype method was developed to update the U.S. Geological Survey (USGS) National Land Cover Database (NLCD) 2001 to a nominal date of 2006. NLCD 2001 is widely used as a baseline for national land cover and impervious cover conditions. To enable the updating of this database in an optimal manner, methods are designed to be accomplished by individual Landsat scene. Using conservative change thresholds based on land cover classes, areas of change and no-change were segregated from change vectors calculated from normalized Landsat scenes from 2001 and 2006. By sampling from NLCD 2001 impervious surface in unchanged areas, impervious surface predictions were estimated for changed areas within an urban extent defined by a companion land cover classification. Methods were developed and tested for national application across six study sites containing a variety of urban impervious surface. Results show the vast majority of impervious surface change associated with urban development was captured, with overall RMSE from 6.86 to 13.12% for these areas. Changes of urban development density were also evaluated by characterizing the categories of change by percentile for impervious surface. This prototype method provides a relatively low cost, flexible approach to generate updated impervious surface using NLCD 2001 as the baseline.

Iterative nonlinear joint transform correlation for the detection of objects in cluttered scenes

NASA Astrophysics Data System (ADS)

Haist, Tobias; Tiziani, Hans J.

1999-03-01

An iterative correlation technique with digital image processing in the feedback loop for the detection of small objects in cluttered scenes is proposed. A scanning aperture is combined with the method in order to improve the immunity against noise and clutter. Multiple reference objects or different views of one object are processed in parallel. We demonstrate the method by detecting a noisy and distorted face in a crowd with a nonlinear joint transform correlator.

The Perception of Concurrent Sound Objects in Harmonic Complexes Impairs Gap Detection

ERIC Educational Resources Information Center

Leung, Ada W. S.; Jolicoeur, Pierre; Vachon, Francois; Alain, Claude

2011-01-01

Since the introduction of the concept of auditory scene analysis, there has been a paucity of work focusing on the theoretical explanation of how attention is allocated within a complex auditory scene. Here we examined signal detection in situations that promote either the fusion of tonal elements into a single sound object or the segregation of a…

An analysis of new techniqes for radiometric correction of LANDSAT-4 Thematic Mapper images. [Terrebonne Bay, Louisiana and Grand Bahamas scenes

NASA Technical Reports Server (NTRS)

Kogut, J.; Larduinat, E.; Fitzgerald, M.

1983-01-01

The utility of methods for generating TM RLUTS which can improve the quality of the resultant images was investigated. The TM-CCT-ADDS tape was changed to account for a different collection window for the calibration data. Several scenes of Terrebonne Bay, Louisiana and the Grand Bahamas were analyzed to evaluate the radiometric corrections operationally applied to the image data and to investigate several techniques for reducing striping in the images. Printer plots for the TM shutter data were produced and detector statistics were compiled and plotted. These statistics included various combinations of the average shutter counts for each scan before and after DC restore for forward and reverse scans. Results show that striping is caused by the detectors becoming saturated when they view a bright cloud and depress the DC restore level.

Landscape preference assessment of Louisiana river landscapes: a methodological study

Treesearch

Michael S. Lee

1979-01-01

The study pertains to the development of an assessment system for the analysis of visual preference attributed to Louisiana river landscapes. The assessment system was utilized in the evaluation of 20 Louisiana river scenes. Individuals were tested for their free choice preference for the same scenes. A statistical analysis was conducted to examine the relationship...

Reconstructing turbidity in a glacially influenced lake using the Landsat TM and ETM+ surface reflectance climate data record archive, Lake Clark, Alaska

USGS Publications Warehouse

Baughman, Carson; Jones, Benjamin M.; Bartz, Krista K.; Young, Daniel B.; Zimmerman, Christian E.

2015-01-01

Lake Clark is an important nursery lake for sockeye salmon (Oncorhynchus nerka) in the headwaters of Bristol Bay, Alaska, the most productive wild salmon fishery in the world. Reductions in water clarity within Alaska lake systems as a result of increased glacial runoff have been shown to reduce salmon production via reduced abundance of zooplankton and macroinvertebrates. In this study, we reconstruct long-term, lake-wide water clarity for Lake Clark using the Landsat TM and ETM+ surface reflectance products (1985–2014) and in situwater clarity data collected between 2009 and 2013. Analysis of a Landsat scene acquired in 2009, coincident with in situ measurements in the lake, and uncertainty analysis with four scenes acquired within two weeks of field data collection showed that Band 3 surface reflectance was the best indicator of turbidity (r2 = 0.55,RMSE << 0.01). We then processed 151 (98 partial- and 53 whole-lake) Landsat scenes using this relation and detected no significant long-term trend in mean turbidity for Lake Clark between 1991 and 2014. We did, however, detect interannual variation that exhibited a non-significant (r2 = 0.20) but positive correlation (r = 0.20) with regional mean summer air temperature and found the month of May exhibited a significant positive trend (r2 = 0.68, p = 0.02) in turbidity between 2000 and 2014. This study demonstrates the utility of hindcasting turbidity in a glacially influenced lake using the Landsat surface reflectance products. It may also help land and resource managers reconstruct turbidity records for lakes that lack in situ monitoring, and may be useful in predicting future water clarity conditions based on projected climate scenarios.

A Method of Sharing Tacit Knowledge by a Bulletin Board Link to Video Scene and an Evaluation in the Field of Nursing Skill

NASA Astrophysics Data System (ADS)

Shimada, Satoshi; Azuma, Shouzou; Teranaka, Sayaka; Kojima, Akira; Majima, Yukie; Maekawa, Yasuko

We developed the system that knowledge could be discovered and shared cooperatively in the organization based on the SECI model of knowledge management. This system realized three processes by the following method. (1)A video that expressed skill is segmented into a number of scenes according to its contents. Tacit knowledge is shared in each scene. (2)Tacit knowledge is extracted by bulletin board linked to each scene. (3)Knowledge is acquired by repeatedly viewing the video scene with the comment that shows the technical content to be practiced. We conducted experiments that the system was used by nurses working for general hospitals. Experimental results show that the nursing practical knack is able to be collected by utilizing bulletin board linked to video scene. Results of this study confirmed the possibility of expressing the tacit knowledge of nurses' empirical nursing skills sensitively with a clue of video images.

A new method for text detection and recognition in indoor scene for assisting blind people

NASA Astrophysics Data System (ADS)

Jabnoun, Hanen; Benzarti, Faouzi; Amiri, Hamid

2017-03-01

Developing assisting system of handicapped persons become a challenging ask in research projects. Recently, a variety of tools are designed to help visually impaired or blind people object as a visual substitution system. The majority of these tools are based on the conversion of input information into auditory or tactile sensory information. Furthermore, object recognition and text retrieval are exploited in the visual substitution systems. Text detection and recognition provides the description of the surrounding environments, so that the blind person can readily recognize the scene. In this work, we aim to introduce a method for detecting and recognizing text in indoor scene. The process consists on the detection of the regions of interest that should contain the text using the connected component. Then, the text detection is provided by employing the images correlation. This component of an assistive blind person should be simple, so that the users are able to obtain the most informative feedback within the shortest time.

Attentional Modulation of Change Detection ERP Components by Peripheral Retro-Cueing

PubMed Central

Pazo-Álvarez, Paula; Roca-Fernández, Adriana; Gutiérrez-Domínguez, Francisco-Javier; Amenedo, Elena

2017-01-01

Change detection is essential for visual perception and performance in our environment. However, observers often miss changes that should be easily noticed. A failure in any of the processes involved in conscious detection (encoding the pre-change display, maintenance of that information within working memory, and comparison of the pre and post change displays) can lead to change blindness. Given that unnoticed visual changes in a scene can be easily detected once attention is drawn to them, it has been suggested that attention plays an important role on visual awareness. In the present study, we used behavioral and electrophysiological (ERPs) measures to study whether the manipulation of retrospective spatial attention affects performance and modulates brain activity related to the awareness of a change. To that end, exogenous peripheral cues were presented during the delay period (retro-cues) between the first and the second array using a one-shot change detection task. Awareness of a change was associated with a posterior negative amplitude shift around 228–292 ms (“Visual Awareness Negativity”), which was independent of retrospective spatial attention, as it was elicited to both validly and invalidly cued change trials. Change detection was also associated with a larger positive deflection around 420–580 ms (“Late Positivity”), but only when the peripheral retro-cues correctly predicted the change. Present results confirm that the early and late ERP components related to change detection can be functionally dissociated through manipulations of exogenous retro-cueing using a change blindness paradigm. PMID:28270759

Emotional facial expressions evoke faster orienting responses, but weaker emotional responses at neural and behavioural levels compared to scenes: A simultaneous EEG and facial EMG study.

PubMed

Mavratzakis, Aimee; Herbert, Cornelia; Walla, Peter

2016-01-01

In the current study, electroencephalography (EEG) was recorded simultaneously with facial electromyography (fEMG) to determine whether emotional faces and emotional scenes are processed differently at the neural level. In addition, it was investigated whether these differences can be observed at the behavioural level via spontaneous facial muscle activity. Emotional content of the stimuli did not affect early P1 activity. Emotional faces elicited enhanced amplitudes of the face-sensitive N170 component, while its counterpart, the scene-related N100, was not sensitive to emotional content of scenes. At 220-280ms, the early posterior negativity (EPN) was enhanced only slightly for fearful as compared to neutral or happy faces. However, its amplitudes were significantly enhanced during processing of scenes with positive content, particularly over the right hemisphere. Scenes of positive content also elicited enhanced spontaneous zygomatic activity from 500-750ms onwards, while happy faces elicited no such changes. Contrastingly, both fearful faces and negative scenes elicited enhanced spontaneous corrugator activity at 500-750ms after stimulus onset. However, relative to baseline EMG changes occurred earlier for faces (250ms) than for scenes (500ms) whereas for scenes activity changes were more pronounced over the whole viewing period. Taking into account all effects, the data suggests that emotional facial expressions evoke faster attentional orienting, but weaker affective neural activity and emotional behavioural responses compared to emotional scenes. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Unsupervised Multi-Scale Change Detection from SAR Imagery for Monitoring Natural and Anthropogenic Disasters

NASA Astrophysics Data System (ADS)

Ajadi, Olaniyi A.

Radar remote sensing can play a critical role in operational monitoring of natural and anthropogenic disasters. Despite its all-weather capabilities, and its high performance in mapping, and monitoring of change, the application of radar remote sensing in operational monitoring activities has been limited. This has largely been due to: (1) the historically high costs associated with obtaining radar data; (2) slow data processing, and delivery procedures; and (3) the limited temporal sampling that was provided by spaceborne radar-based satellites. Recent advances in the capabilities of spaceborne Synthetic Aperture Radar (SAR) sensors have developed an environment that now allows for SAR to make significant contributions to disaster monitoring. New SAR processing strategies that can take full advantage of these new sensor capabilities are currently being developed. Hence, with this PhD dissertation, I aim to: (i) investigate unsupervised change detection techniques that can reliably extract signatures from time series of SAR images, and provide the necessary flexibility for application to a variety of natural, and anthropogenic hazard situations; (ii) investigate effective methods to reduce the effects of speckle and other noise on change detection performance; (iii) automate change detection algorithms using probabilistic Bayesian inferencing; and (iv) ensure that the developed technology is applicable to current, and future SAR sensors to maximize temporal sampling of a hazardous event. This is achieved by developing new algorithms that rely on image amplitude information only, the sole image parameter that is available for every single SAR acquisition.. The motivation and implementation of the change detection concept are described in detail in Chapter 3. In the same chapter, I demonstrated the technique's performance using synthetic data as well as a real-data application to map wildfire progression. I applied Radiometric Terrain Correction (RTC) to the data to increase the sampling frequency, while the developed multiscale-driven approach reliably identified changes embedded in largely stationary background scenes. With this technique, I was able to identify the extent of burn scars with high accuracy. I further applied the application of the change detection technology to oil spill mapping. The analysis highlights that the approach described in Chapter 3 can be applied to this drastically different change detection problem with only little modification. While the core of the change detection technique remained unchanged, I made modifications to the pre-processing step to enable change detection from scenes of continuously varying background. I introduced the Lipschitz regularity (LR) transformation as a technique to normalize the typically dynamic ocean surface, facilitating high performance oil spill detection independent of environmental conditions during image acquisition. For instance, I showed that LR processing reduces the sensitivity of change detection performance to variations in surface winds, which is a known limitation in oil spill detection from SAR. Finally, I applied the change detection technique to aufeis flood mapping along the Sagavanirktok River. Due to the complex nature of aufeis flooded areas, I substituted the resolution-preserving speckle filter used in Chapter 3 with curvelet filters. In addition to validating the performance of the change detection results, I also provide evidence of the wealth of information that can be extracted about aufeis flooding events once a time series of change detection information was extracted from SAR imagery. A summary of the developed change detection techniques is conducted and suggested future work is presented in Chapter 6.

Orthorectified High Resolution Multispectral Imagery for Application to Change Detection and Analysis

NASA Technical Reports Server (NTRS)

Benkelman, Cody A.

1997-01-01

The project team has outlined several technical objectives which will allow the companies to improve on their current capabilities. These include modifications to the imaging system, enabling it to operate more cost effectively and with greater ease of use, automation of the post-processing software to mosaic and orthorectify the image scenes collected, and the addition of radiometric calibration to greatly aid in the ability to perform accurate change detection. Business objectives include fine tuning of the market plan plus specification of future product requirements, expansion of sales activities (including identification of necessary additional resources required to meet stated revenue objectives), development of a product distribution plan, and implementation of a world wide sales effort.

CHAMP: a locally adaptive unmixing-based hyperspectral anomaly detection algorithm

NASA Astrophysics Data System (ADS)

Crist, Eric P.; Thelen, Brian J.; Carrara, David A.

1998-10-01

Anomaly detection offers a means by which to identify potentially important objects in a scene without prior knowledge of their spectral signatures. As such, this approach is less sensitive to variations in target class composition, atmospheric and illumination conditions, and sensor gain settings than would be a spectral matched filter or similar algorithm. The best existing anomaly detectors generally fall into one of two categories: those based on local Gaussian statistics, and those based on linear mixing moles. Unmixing-based approaches better represent the real distribution of data in a scene, but are typically derived and applied on a global or scene-wide basis. Locally adaptive approaches allow detection of more subtle anomalies by accommodating the spatial non-homogeneity of background classes in a typical scene, but provide a poorer representation of the true underlying background distribution. The CHAMP algorithm combines the best attributes of both approaches, applying a linear-mixing model approach in a spatially adaptive manner. The algorithm itself, and teste results on simulated and actual hyperspectral image data, are presented in this paper.

Discriminating between camouflaged targets by their time of detection by a human-based observer assessment method

NASA Astrophysics Data System (ADS)

Selj, G. K.; Søderblom, M.

2015-10-01

Detection of a camouflaged object in natural sceneries requires the target to be distinguishable from its local background. The development of any new camouflage pattern therefore has to rely on a well-founded test methodology - which has to be correlated with the final purpose of the pattern - as well as an evaluation procedure, containing the optimal criteria for i) discriminating between the targets and then eventually ii) for a final rank of the targets. In this study we present results from a recent camouflage assessment trial where human observers were used in a search by photo methodology to assess generic test camouflage patterns. We conducted a study to investigate possible improvements in camouflage patterns for battle dress uniforms. The aim was to do a comparative study of potential, and generic patterns intended for use in arid areas (sparsely vegetated, semi desert). We developed a test methodology that was intended to be simple, reliable and realistic with respect to the operational benefit of camouflage. Therefore we chose to conduct a human based observer trial founded on imagery of realistic targets in natural backgrounds. Inspired by a recent and similar trial in the UK, we developed new and purpose-based software to be able to conduct the observer trial. Our preferred assessment methodology - the observer trial - was based on target recordings in 12 different, but operational relevant scenes, collected in a dry and sparsely vegetated area (Rhodes). The scenes were chosen with the intention to span as broadly as possible. The targets were human-shaped mannequins and were situated identically in each of the scenes to allow for a relative comparison of camouflage effectiveness in each scene. Test of significance, among the targets' performance, was carried out by non-parametric tests as the corresponding time of detection distributions in overall were found to be difficult to parameterize. From the trial, containing 12 different scenes from sparsely vegetated areas we collected detection time's distributions for 6 generic targets through visual search by 148 observers. We found that the different targets performed differently, given by their corresponding time of detection distributions, within a single scene. Furthermore, we gained an overall ranking over all the 12 scenes by performing a weighted sum over all scenes, intended to keep as much of the vital information on the targets' signature effectiveness as possible. Our results show that it was possible to measure the targets performance relatively to another also when summing over all scenes. We also compared our ranking based on our preferred criterion (detection time) with a secondary (probability of detection) to assess the sensitivity of a final ranking based upon the test set-up and evaluation criterion. We found our observer-based approach to be well suited regarding its ability to discriminate between similar targets and to assign numeric values to the observed differences in performance. We believe our approach will be well suited as a tool whenever different aspects of camouflage are to be evaluated and understood further.

Automated UAV-based mapping for airborne reconnaissance and video exploitation

NASA Astrophysics Data System (ADS)

Se, Stephen; Firoozfam, Pezhman; Goldstein, Norman; Wu, Linda; Dutkiewicz, Melanie; Pace, Paul; Naud, J. L. Pierre

2009-05-01

Airborne surveillance and reconnaissance are essential for successful military missions. Such capabilities are critical for force protection, situational awareness, mission planning, damage assessment and others. UAVs gather huge amount of video data but it is extremely labour-intensive for operators to analyse hours and hours of received data. At MDA, we have developed a suite of tools towards automated video exploitation including calibration, visualization, change detection and 3D reconstruction. The on-going work is to improve the robustness of these tools and automate the process as much as possible. Our calibration tool extracts and matches tie-points in the video frames incrementally to recover the camera calibration and poses, which are then refined by bundle adjustment. Our visualization tool stabilizes the video, expands its field-of-view and creates a geo-referenced mosaic from the video frames. It is important to identify anomalies in a scene, which may include detecting any improvised explosive devices (IED). However, it is tedious and difficult to compare video clips to look for differences manually. Our change detection tool allows the user to load two video clips taken from two passes at different times and flags any changes between them. 3D models are useful for situational awareness, as it is easier to understand the scene by visualizing it in 3D. Our 3D reconstruction tool creates calibrated photo-realistic 3D models from video clips taken from different viewpoints, using both semi-automated and automated approaches. The resulting 3D models also allow distance measurements and line-of- sight analysis.

Change Detection Analysis of Costal Habitat Using Remote Sensing Technologies in the Western Arabian Gulf (Saudi Arabian Coast) over a Thirty-Year Period.

NASA Astrophysics Data System (ADS)

El-Askary, H. M.; Idris, N.; Johnson, S. H.; Qurban, M. A. B.

2014-12-01

Many factors can severely affect the growth and abundance of the marine ecosystems. For example, due to anthropogenic and natural forces, benthic habitats including but not limited to mangroves, sea grass, salt marshes, macro algae, and coral reefs have been experiencing high levels of declination. Furthermore, aerosols and their propellants are suspected contributors to marine habitat degradation. Although several studies reveal that the Arabian Gulf habitats have suffered deleterious impacts after the Gulf War and the following six month off-shore oil spill, limited research exists to track the changes in benthic habitats over the past three decades using remote sensing. Document changes in costal habitats over the past thirty years were better observed with the use of multispectral remote sensors such as Landsat-5, Landsat-7, and Landsat8 (OLI). Change detection analysis was performed on the three Landsat images (Landsat-5 for the 1987 image, Landsat-7 for the 2000, and Landsat-8 for the 2013 image). The images were then modified, masked off from open water and land. An unsupervised classification was performed which cluster similar classes together. The supervised classification displayed the seven following classes: coral reefs, macro algae, sea grass, salt marshes, mangroves, water, and land. Compared to 1987 image to 2000 scene, there was a noticeable increase in the extensiveness of salt marsh and macro algae habitats. However, a significant decrease in salt marsh habitats were apparent in the 2013 scene.

Fast Edge Detection and Segmentation of Terrestrial Laser Scans Through Normal Variation Analysis

NASA Astrophysics Data System (ADS)

Che, E.; Olsen, M. J.

2017-09-01

Terrestrial Laser Scanning (TLS) utilizes light detection and ranging (lidar) to effectively and efficiently acquire point cloud data for a wide variety of applications. Segmentation is a common procedure of post-processing to group the point cloud into a number of clusters to simplify the data for the sequential modelling and analysis needed for most applications. This paper presents a novel method to rapidly segment TLS data based on edge detection and region growing. First, by computing the projected incidence angles and performing the normal variation analysis, the silhouette edges and intersection edges are separated from the smooth surfaces. Then a modified region growing algorithm groups the points lying on the same smooth surface. The proposed method efficiently exploits the gridded scan pattern utilized during acquisition of TLS data from most sensors and takes advantage of parallel programming to process approximately 1 million points per second. Moreover, the proposed segmentation does not require estimation of the normal at each point, which limits the errors in normal estimation propagating to segmentation. Both an indoor and outdoor scene are used for an experiment to demonstrate and discuss the effectiveness and robustness of the proposed segmentation method.

Automated content and quality assessment of full-motion-video for the generation of meta data

NASA Astrophysics Data System (ADS)

Harguess, Josh

2015-05-01

Virtually all of the video data (and full-motion-video (FMV)) that is currently collected and stored in support of missions has been corrupted to various extents by image acquisition and compression artifacts. Additionally, video collected by wide-area motion imagery (WAMI) surveillance systems and unmanned aerial vehicles (UAVs) and similar sources is often of low quality or in other ways corrupted so that it is not worth storing or analyzing. In order to make progress in the problem of automatic video analysis, the first problem that should be solved is deciding whether the content of the video is even worth analyzing to begin with. We present a work in progress to address three types of scenes which are typically found in real-world data stored in support of Department of Defense (DoD) missions: no or very little motion in the scene, large occlusions in the scene, and fast camera motion. Each of these produce video that is generally not usable to an analyst or automated algorithm for mission support and therefore should be removed or flagged to the user as such. We utilize recent computer vision advances in motion detection and optical flow to automatically assess FMV for the identification and generation of meta-data (or tagging) of video segments which exhibit unwanted scenarios as described above. Results are shown on representative real-world video data.

Spatial and temporal variability of hyperspectral signatures of terrain

NASA Astrophysics Data System (ADS)

Jones, K. F.; Perovich, D. K.; Koenig, G. G.

2008-04-01

Electromagnetic signatures of terrain exhibit significant spatial heterogeneity on a range of scales as well as considerable temporal variability. A statistical characterization of the spatial heterogeneity and spatial scaling algorithms of terrain electromagnetic signatures are required to extrapolate measurements to larger scales. Basic terrain elements including bare soil, grass, deciduous, and coniferous trees were studied in a quasi-laboratory setting using instrumented test sites in Hanover, NH and Yuma, AZ. Observations were made using a visible and near infrared spectroradiometer (350 - 2500 nm) and hyperspectral camera (400 - 1100 nm). Results are reported illustrating: i) several difference scenes; ii) a terrain scene time series sampled over an annual cycle; and iii) the detection of artifacts in scenes. A principal component analysis indicated that the first three principal components typically explained between 90 and 99% of the variance of the 30 to 40-channel hyperspectral images. Higher order principal components of hyperspectral images are useful for detecting artifacts in scenes.

How temporal cues can aid colour constancy

PubMed Central

Foster, David H.; Amano, Kinjiro; Nascimento, Sérgio M. C.

2007-01-01

Colour constancy assessed by asymmetric simultaneous colour matching usually reveals limited levels of performance in the unadapted eye. Yet observers can readily discriminate illuminant changes on a scene from changes in the spectral reflectances of the surfaces making up the scene. This ability is probably based on judgements of relational colour constancy, in turn based on the physical stability of spatial ratios of cone excitations under illuminant changes. Evidence is presented suggesting that the ability to detect violations in relational colour constancy depends on temporal transient cues. Because colour constancy and relational colour constancy are closely connected, it should be possible to improve estimates of colour constancy by introducing similar transient cues into the matching task. To test this hypothesis, an experiment was performed in which observers made surface-colour matches between patterns presented in the same position in an alternating sequence with period 2 s or, as a control, presented simultaneously, side-by-side. The degree of constancy was significantly higher for sequential presentation, reaching 87% for matches averaged over 20 observers. Temporal cues may offer a useful source of information for making colour-constancy judgements. PMID:17515948

Characterization techniques for incorporating backgrounds into DIRSIG

NASA Astrophysics Data System (ADS)

Brown, Scott D.; Schott, John R.

2000-07-01

The appearance of operation hyperspectral imaging spectrometers in both solar and thermal regions has lead to the development of a variety of spectral detection algorithms. The development and testing of these algorithms requires well characterized field collection campaigns that can be time and cost prohibitive. Radiometrically robust synthetic image generation (SIG) environments that can generate appropriate images under a variety of atmospheric conditions and with a variety of sensors offers an excellent supplement to reduce the scope of the expensive field collections. In addition, SIG image products provide the algorithm developer with per-pixel truth, allowing for improved characterization of the algorithm performance. To meet the needs of the algorithm development community, the image modeling community needs to supply synthetic image products that contain all the spatial and spectral variability present in real world scenes, and that provide the large area coverage typically acquired with actual sensors. This places a heavy burden on synthetic scene builders to construct well characterized scenes that span large areas. Several SIG models have demonstrated the ability to accurately model targets (vehicles, buildings, etc.) Using well constructed target geometry (from CAD packages) and robust thermal and radiometry models. However, background objects (vegetation, infrastructure, etc.) dominate the percentage of real world scene pixels and utilizing target building techniques is time and resource prohibitive. This paper discusses new methods that have been integrated into the Digital Imaging and Remote Sensing Image Generation (DIRSIG) model to characterize backgrounds. The new suite of scene construct types allows the user to incorporate both terrain and surface properties to obtain wide area coverage. The terrain can be incorporated using a triangular irregular network (TIN) derived from elevation data or digital elevation model (DEM) data from actual sensors, temperature maps, spectral reflectance cubes (possible derived from actual sensors), and/or material and mixture maps. Descriptions and examples of each new technique are presented as well as hybrid methods to demonstrate target embedding in real world imagery.

A scheme for racquet sports video analysis with the combination of audio-visual information

NASA Astrophysics Data System (ADS)

Xing, Liyuan; Ye, Qixiang; Zhang, Weigang; Huang, Qingming; Yu, Hua

2005-07-01

As a very important category in sports video, racquet sports video, e.g. table tennis, tennis and badminton, has been paid little attention in the past years. Considering the characteristics of this kind of sports video, we propose a new scheme for structure indexing and highlight generating based on the combination of audio and visual information. Firstly, a supervised classification method is employed to detect important audio symbols including impact (ball hit), audience cheers, commentator speech, etc. Meanwhile an unsupervised algorithm is proposed to group video shots into various clusters. Then, by taking advantage of temporal relationship between audio and visual signals, we can specify the scene clusters with semantic labels including rally scenes and break scenes. Thirdly, a refinement procedure is developed to reduce false rally scenes by further audio analysis. Finally, an exciting model is proposed to rank the detected rally scenes from which many exciting video clips such as game (match) points can be correctly retrieved. Experiments on two types of representative racquet sports video, table tennis video and tennis video, demonstrate encouraging results.

Domain Adaptation for Pedestrian Detection Based on Prediction Consistency

PubMed Central

Huan-ling, Tang; Zhi-yong, An

2014-01-01

Pedestrian detection is an active area of research in computer vision. It remains a quite challenging problem in many applications where many factors cause a mismatch between source dataset used to train the pedestrian detector and samples in the target scene. In this paper, we propose a novel domain adaptation model for merging plentiful source domain samples with scared target domain samples to create a scene-specific pedestrian detector that performs as well as rich target domain simples are present. Our approach combines the boosting-based learning algorithm with an entropy-based transferability, which is derived from the prediction consistency with the source classifications, to selectively choose the samples showing positive transferability in source domains to the target domain. Experimental results show that our approach can improve the detection rate, especially with the insufficient labeled data in target scene. PMID:25013850

Change detection on UGV patrols with respect to a reference tour using VIS imagery

NASA Astrophysics Data System (ADS)

Müller, Thomas

2015-05-01

Autonomous driving robots (UGVs, Unmanned Ground Vehicles) equipped with visual-optical (VIS) cameras offer a high potential to automatically detect suspicious occurrences and dangerous or threatening situations on patrol. In order to explore this potential, the scene of interest is recorded first on a reference tour representing the 'everything okay' situation. On further patrols changes are detected with respect to the reference in a two step processing scheme. In the first step, an image retrieval is done to find the reference images that are closest to the current camera image on patrol. This is done efficiently based on precalculated image-to-image registrations of the reference by optimizing image overlap in a local reference search (after a global search when that is needed). In the second step, a robust spatio-temporal change detection is performed that widely compensates 3-D parallax according to variations of the camera position. Various results document the performance of the presented approach.

Active microwave measurements of sea ice under fall conditions: The RADARSAT/FIREX fall experiment. [in the Canadian Arctic

NASA Technical Reports Server (NTRS)

Onstott, R. G.; Kim, Y. S.; Moore, R. K.

1984-01-01

A series of measurements of the active microwave properties of sea ice under fall growing conditions was conducted. Ice in the inland waters of Mould Bay, Crozier Channel, and intrepid inlet and ice in the Arctic Ocean near Hardinge Bay was investigated. Active microwave data were acquired using a helicopter borne scatterometer. Results show that multiyear ice frozen in grey or first year ice is easily detected under cold fall conditions. Multiyear ice returns were dynamic due to response to two of its scene constituents. Floe boundaries between thick and thin ice are well defined. Multiyear pressure ridge returns are similar in level to background ice returns. Backscatter from homogeneous first year ice is seen to be primarily due to surface scattering. Operation at 9.6 GHz is more sensitive to the detailed changes in scene roughness, while operation at 5.6 GHz seems to track roughness changes less ably.

ViCoMo: visual context modeling for scene understanding in video surveillance

NASA Astrophysics Data System (ADS)

Creusen, Ivo M.; Javanbakhti, Solmaz; Loomans, Marijn J. H.; Hazelhoff, Lykele B.; Roubtsova, Nadejda; Zinger, Svitlana; de With, Peter H. N.

2013-10-01

The use of contextual information can significantly aid scene understanding of surveillance video. Just detecting people and tracking them does not provide sufficient information to detect situations that require operator attention. We propose a proof-of-concept system that uses several sources of contextual information to improve scene understanding in surveillance video. The focus is on two scenarios that represent common video surveillance situations, parking lot surveillance and crowd monitoring. In the first scenario, a pan-tilt-zoom (PTZ) camera tracking system is developed for parking lot surveillance. Context is provided by the traffic sign recognition system to localize regular and handicapped parking spot signs as well as license plates. The PTZ algorithm has the ability to selectively detect and track persons based on scene context. In the second scenario, a group analysis algorithm is introduced to detect groups of people. Contextual information is provided by traffic sign recognition and region labeling algorithms and exploited for behavior understanding. In both scenarios, decision engines are used to interpret and classify the output of the subsystems and if necessary raise operator alerts. We show that using context information enables the automated analysis of complicated scenarios that were previously not possible using conventional moving object classification techniques.

The effects of scene content parameters, compression, and frame rate on the performance of analytics systems

NASA Astrophysics Data System (ADS)

Tsifouti, A.; Triantaphillidou, S.; Larabi, M. C.; Doré, G.; Bilissi, E.; Psarrou, A.

2015-01-01

In this investigation we study the effects of compression and frame rate reduction on the performance of four video analytics (VA) systems utilizing a low complexity scenario, such as the Sterile Zone (SZ). Additionally, we identify the most influential scene parameters affecting the performance of these systems. The SZ scenario is a scene consisting of a fence, not to be trespassed, and an area with grass. The VA system needs to alarm when there is an intruder (attack) entering the scene. The work includes testing of the systems with uncompressed and compressed (using H.264/MPEG-4 AVC at 25 and 5 frames per second) footage, consisting of quantified scene parameters. The scene parameters include descriptions of scene contrast, camera to subject distance, and attack portrayal. Additional footage, including only distractions (no attacks) is also investigated. Results have shown that every system has performed differently for each compression/frame rate level, whilst overall, compression has not adversely affected the performance of the systems. Frame rate reduction has decreased performance and scene parameters have influenced the behavior of the systems differently. Most false alarms were triggered with a distraction clip, including abrupt shadows through the fence. Findings could contribute to the improvement of VA systems.

Flood Extent Mapping for Namibia Using Change Detection and Thresholding with SAR

NASA Technical Reports Server (NTRS)

Long, Stephanie; Fatoyinbo, Temilola E.; Policelli, Frederick

2014-01-01

A new method for flood detection change detection and thresholding (CDAT) was used with synthetic aperture radar (SAR) imagery to delineate the extent of flooding for the Chobe floodplain in the Caprivi region of Namibia. This region experiences annual seasonal flooding and has seen a recent renewal of severe flooding after a long dry period in the 1990s. Flooding in this area has caused loss of life and livelihoods for the surrounding communities and has caught the attention of disaster relief agencies. There is a need for flood extent mapping techniques that can be used to process images quickly, providing near real-time flooding information to relief agencies. ENVISAT/ASAR and Radarsat-2 images were acquired for several flooding seasons from February 2008 to March 2013. The CDAT method was used to determine flooding from these images and includes the use of image subtraction, decision based classification with threshold values, and segmentation of SAR images. The total extent of flooding determined for 2009, 2011 and 2012 was about 542 km2, 720 km2, and 673 km2 respectively. Pixels determined to be flooded in vegetation were typically <0.5 % of the entire scene, with the exception of 2009 where the detection of flooding in vegetation was much greater (almost one third of the total flooded area). The time to maximum flooding for the 2013 flood season was determined to be about 27 days. Landsat water classification was used to compare the results from the new CDAT with SAR method; the results show good spatial agreement with Landsat scenes.

Object Scene Flow

NASA Astrophysics Data System (ADS)

Menze, Moritz; Heipke, Christian; Geiger, Andreas

2018-06-01

This work investigates the estimation of dense three-dimensional motion fields, commonly referred to as scene flow. While great progress has been made in recent years, large displacements and adverse imaging conditions as observed in natural outdoor environments are still very challenging for current approaches to reconstruction and motion estimation. In this paper, we propose a unified random field model which reasons jointly about 3D scene flow as well as the location, shape and motion of vehicles in the observed scene. We formulate the problem as the task of decomposing the scene into a small number of rigidly moving objects sharing the same motion parameters. Thus, our formulation effectively introduces long-range spatial dependencies which commonly employed local rigidity priors are lacking. Our inference algorithm then estimates the association of image segments and object hypotheses together with their three-dimensional shape and motion. We demonstrate the potential of the proposed approach by introducing a novel challenging scene flow benchmark which allows for a thorough comparison of the proposed scene flow approach with respect to various baseline models. In contrast to previous benchmarks, our evaluation is the first to provide stereo and optical flow ground truth for dynamic real-world urban scenes at large scale. Our experiments reveal that rigid motion segmentation can be utilized as an effective regularizer for the scene flow problem, improving upon existing two-frame scene flow methods. At the same time, our method yields plausible object segmentations without requiring an explicitly trained recognition model for a specific object class.

Anticipation in Real-World Scenes: The Role of Visual Context and Visual Memory.

PubMed

Coco, Moreno I; Keller, Frank; Malcolm, George L

2016-11-01

The human sentence processor is able to make rapid predictions about upcoming linguistic input. For example, upon hearing the verb eat, anticipatory eye-movements are launched toward edible objects in a visual scene (Altmann & Kamide, 1999). However, the cognitive mechanisms that underlie anticipation remain to be elucidated in ecologically valid contexts. Previous research has, in fact, mainly used clip-art scenes and object arrays, raising the possibility that anticipatory eye-movements are limited to displays containing a small number of objects in a visually impoverished context. In Experiment 1, we confirm that anticipation effects occur in real-world scenes and investigate the mechanisms that underlie such anticipation. In particular, we demonstrate that real-world scenes provide contextual information that anticipation can draw on: When the target object is not present in the scene, participants infer and fixate regions that are contextually appropriate (e.g., a table upon hearing eat). Experiment 2 investigates whether such contextual inference requires the co-presence of the scene, or whether memory representations can be utilized instead. The same real-world scenes as in Experiment 1 are presented to participants, but the scene disappears before the sentence is heard. We find that anticipation occurs even when the screen is blank, including when contextual inference is required. We conclude that anticipatory language processing is able to draw upon global scene representations (such as scene type) to make contextual inferences. These findings are compatible with theories assuming contextual guidance, but posit a challenge for theories assuming object-based visual indices. Copyright © 2015 Cognitive Science Society, Inc.

Passive Fully Polarimetric W-Band Millimeter-Wave Imaging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bernacki, Bruce E.; Kelly, James F.; Sheen, David M.

2012-04-01

We present the theory, design, and experimental results obtained from a scanning passive W-band fully polarimetric imager. Passive millimeter-wave imaging offers persistent day/nighttime imaging and the ability to penetrate dust, clouds and other obscurants, including clothing and dry soil. The single-pixel scanning imager includes both far-field and near-field fore-optics for investigation of polarization phenomena. Using both fore-optics, a variety of scenes including natural and man-made objects was imaged and these results are presented showing the utility of polarimetric imaging for anomaly detection. Analysis includes conventional Stokes-parameter based approaches as well as multivariate image analysis methods.

A landsat data tiling and compositing approach optimized for change detection in the conterminous United States

USGS Publications Warehouse

Nelson, Kurtis; Steinwand, Daniel R.

2015-01-01

Annual disturbance maps are produced by the LANDFIRE program across the conterminous United States (CONUS). Existing LANDFIRE disturbance data from 1999 to 2010 are available and current efforts will produce disturbance data through 2012. A tiling and compositing approach was developed to produce bi-annual images optimized for change detection. A tiled grid of 10,000 × 10,000 30 m pixels was defined for CONUS and adjusted to consolidate smaller tiles along national borders, resulting in 98 non-overlapping tiles. Data from Landsat-5,-7, and -8 were re-projected to the tile extents, masked to remove clouds, shadows, water, and snow/ice, then composited using a cosine similarity approach. The resultant images were used in a change detection algorithm to determine areas of vegetation change. This approach enabled more efficient processing compared to using single Landsat scenes, by taking advantage of overlap between adjacent paths, and allowed an automated system to be developed for the entire process.

Spatial and temporal aspects of chromatic adaptation and their functional significance for colour constancy.

PubMed

Werner, Annette

2014-11-01

Illumination in natural scenes changes at multiple temporal and spatial scales: slow changes in global illumination occur in the course of a day, and we encounter fast and localised illumination changes when visually exploring the non-uniform light field of three-dimensional scenes; in addition, very long-term chromatic variations may come from the environment, like for example seasonal changes. In this context, I consider the temporal and spatial properties of chromatic adaptation and discuss their functional significance for colour constancy in three-dimensional scenes. A process of fast spatial tuning in chromatic adaptation is proposed as a possible sensory mechanism for linking colour constancy to the spatial structure of a scene. The observed middlewavelength selectivity of this process is particularly suitable for adaptation to the mean chromaticity and the compensation of interreflections in natural scenes. Two types of sensory colour constancy are distinguished, based on the functional differences of their temporal and spatial scales: a slow type, operating at a global scale for the compensation of the ambient illumination; and a fast colour constancy, which is locally restricted and well suited to compensate region-specific variations in the light field of three dimensional scenes. Copyright © 2014 Elsevier B.V. All rights reserved.

The Low Backscattering Objects Classification in Polsar Image Based on Bag of Words Model Using Support Vector Machine

NASA Astrophysics Data System (ADS)

Yang, L.; Shi, L.; Li, P.; Yang, J.; Zhao, L.; Zhao, B.

2018-04-01

Due to the forward scattering and block of radar signal, the water, bare soil, shadow, named low backscattering objects (LBOs), often present low backscattering intensity in polarimetric synthetic aperture radar (PolSAR) image. Because the LBOs rise similar backscattering intensity and polarimetric responses, the spectral-based classifiers are inefficient to deal with LBO classification, such as Wishart method. Although some polarimetric features had been exploited to relieve the confusion phenomenon, the backscattering features are still found unstable when the system noise floor varies in the range direction. This paper will introduce a simple but effective scene classification method based on Bag of Words (BoW) model using Support Vector Machine (SVM) to discriminate the LBOs, without relying on any polarimetric features. In the proposed approach, square windows are firstly opened around the LBOs adaptively to determine the scene images, and then the Scale-Invariant Feature Transform (SIFT) points are detected in training and test scenes. The several SIFT features detected are clustered using K-means to obtain certain cluster centers as the visual word lists and scene images are represented using word frequency. At last, the SVM is selected for training and predicting new scenes as some kind of LBOs. The proposed method is executed over two AIRSAR data sets at C band and L band, including water, bare soil and shadow scenes. The experimental results illustrate the effectiveness of the scene method in distinguishing LBOs.

Texture classification using autoregressive filtering

NASA Technical Reports Server (NTRS)

Lawton, W. M.; Lee, M.

1984-01-01

A general theory of image texture models is proposed and its applicability to the problem of scene segmentation using texture classification is discussed. An algorithm, based on half-plane autoregressive filtering, which optimally utilizes second order statistics to discriminate between texture classes represented by arbitrary wide sense stationary random fields is described. Empirical results of applying this algorithm to natural and sysnthesized scenes are presented and future research is outlined.

Correlated Topic Vector for Scene Classification.

PubMed

Wei, Pengxu; Qin, Fei; Wan, Fang; Zhu, Yi; Jiao, Jianbin; Ye, Qixiang

2017-07-01

Scene images usually involve semantic correlations, particularly when considering large-scale image data sets. This paper proposes a novel generative image representation, correlated topic vector, to model such semantic correlations. Oriented from the correlated topic model, correlated topic vector intends to naturally utilize the correlations among topics, which are seldom considered in the conventional feature encoding, e.g., Fisher vector, but do exist in scene images. It is expected that the involvement of correlations can increase the discriminative capability of the learned generative model and consequently improve the recognition accuracy. Incorporated with the Fisher kernel method, correlated topic vector inherits the advantages of Fisher vector. The contributions to the topics of visual words have been further employed by incorporating the Fisher kernel framework to indicate the differences among scenes. Combined with the deep convolutional neural network (CNN) features and Gibbs sampling solution, correlated topic vector shows great potential when processing large-scale and complex scene image data sets. Experiments on two scene image data sets demonstrate that correlated topic vector improves significantly the deep CNN features, and outperforms existing Fisher kernel-based features.

Integration of heterogeneous features for remote sensing scene classification

NASA Astrophysics Data System (ADS)

Wang, Xin; Xiong, Xingnan; Ning, Chen; Shi, Aiye; Lv, Guofang

2018-01-01

Scene classification is one of the most important issues in remote sensing (RS) image processing. We find that features from different channels (shape, spectral, texture, etc.), levels (low-level and middle-level), or perspectives (local and global) could provide various properties for RS images, and then propose a heterogeneous feature framework to extract and integrate heterogeneous features with different types for RS scene classification. The proposed method is composed of three modules (1) heterogeneous features extraction, where three heterogeneous feature types, called DS-SURF-LLC, mean-Std-LLC, and MS-CLBP, are calculated, (2) heterogeneous features fusion, where the multiple kernel learning (MKL) is utilized to integrate the heterogeneous features, and (3) an MKL support vector machine classifier for RS scene classification. The proposed method is extensively evaluated on three challenging benchmark datasets (a 6-class dataset, a 12-class dataset, and a 21-class dataset), and the experimental results show that the proposed method leads to good classification performance. It produces good informative features to describe the RS image scenes. Moreover, the integration of heterogeneous features outperforms some state-of-the-art features on RS scene classification tasks.

Sky Detection in Hazy Image.

PubMed

Song, Yingchao; Luo, Haibo; Ma, Junkai; Hui, Bin; Chang, Zheng

2018-04-01

Sky detection plays an essential role in various computer vision applications. Most existing sky detection approaches, being trained on ideal dataset, may lose efficacy when facing unfavorable conditions like the effects of weather and lighting conditions. In this paper, a novel algorithm for sky detection in hazy images is proposed from the perspective of probing the density of haze. We address the problem by an image segmentation and a region-level classification. To characterize the sky of hazy scenes, we unprecedentedly introduce several haze-relevant features that reflect the perceptual hazy density and the scene depth. Based on these features, the sky is separated by two imbalance SVM classifiers and a similarity measurement. Moreover, a sky dataset (named HazySky) with 500 annotated hazy images is built for model training and performance evaluation. To evaluate the performance of our method, we conducted extensive experiments both on our HazySky dataset and the SkyFinder dataset. The results demonstrate that our method performs better on the detection accuracy than previous methods, not only under hazy scenes, but also under other weather conditions.

Adherent Raindrop Modeling, Detectionand Removal in Video.

PubMed

You, Shaodi; Tan, Robby T; Kawakami, Rei; Mukaigawa, Yasuhiro; Ikeuchi, Katsushi

2016-09-01

Raindrops adhered to a windscreen or window glass can significantly degrade the visibility of a scene. Modeling, detecting and removing raindrops will, therefore, benefit many computer vision applications, particularly outdoor surveillance systems and intelligent vehicle systems. In this paper, a method that automatically detects and removes adherent raindrops is introduced. The core idea is to exploit the local spatio-temporal derivatives of raindrops. To accomplish the idea, we first model adherent raindrops using law of physics, and detect raindrops based on these models in combination with motion and intensity temporal derivatives of the input video. Having detected the raindrops, we remove them and restore the images based on an analysis that some areas of raindrops completely occludes the scene, and some other areas occlude only partially. For partially occluding areas, we restore them by retrieving as much as possible information of the scene, namely, by solving a blending function on the detected partially occluding areas using the temporal intensity derivative. For completely occluding areas, we recover them by using a video completion technique. Experimental results using various real videos show the effectiveness of our method.

Sky Detection in Hazy Image

PubMed Central

Song, Yingchao; Luo, Haibo; Ma, Junkai; Hui, Bin; Chang, Zheng

2018-01-01

Sky detection plays an essential role in various computer vision applications. Most existing sky detection approaches, being trained on ideal dataset, may lose efficacy when facing unfavorable conditions like the effects of weather and lighting conditions. In this paper, a novel algorithm for sky detection in hazy images is proposed from the perspective of probing the density of haze. We address the problem by an image segmentation and a region-level classification. To characterize the sky of hazy scenes, we unprecedentedly introduce several haze-relevant features that reflect the perceptual hazy density and the scene depth. Based on these features, the sky is separated by two imbalance SVM classifiers and a similarity measurement. Moreover, a sky dataset (named HazySky) with 500 annotated hazy images is built for model training and performance evaluation. To evaluate the performance of our method, we conducted extensive experiments both on our HazySky dataset and the SkyFinder dataset. The results demonstrate that our method performs better on the detection accuracy than previous methods, not only under hazy scenes, but also under other weather conditions. PMID:29614778

Color constancy in natural scenes explained by global image statistics

PubMed Central

Foster, David H.; Amano, Kinjiro; Nascimento, Sérgio M. C.

2007-01-01

To what extent do observers' judgments of surface color with natural scenes depend on global image statistics? To address this question, a psychophysical experiment was performed in which images of natural scenes under two successive daylights were presented on a computer-controlled high-resolution color monitor. Observers reported whether there was a change in reflectance of a test surface in the scene. The scenes were obtained with a hyperspectral imaging system and included variously trees, shrubs, grasses, ferns, flowers, rocks, and buildings. Discrimination performance, quantified on a scale of 0 to 1 with a color-constancy index, varied from 0.69 to 0.97 over 21 scenes and two illuminant changes, from a correlated color temperature of 25,000 K to 6700 K and from 4000 K to 6700 K. The best account of these effects was provided by receptor-based rather than colorimetric properties of the images. Thus, in a linear regression, 43% of the variance in constancy index was explained by the log of the mean relative deviation in spatial cone-excitation ratios evaluated globally across the two images of a scene. A further 20% was explained by including the mean chroma of the first image and its difference from that of the second image and a further 7% by the mean difference in hue. Together, all four global color properties accounted for 70% of the variance and provided a good fit to the effects of scene and of illuminant change on color constancy, and, additionally, of changing test-surface position. By contrast, a spatial-frequency analysis of the images showed that the gradient of the luminance amplitude spectrum accounted for only 5% of the variance. PMID:16961965

Color constancy in natural scenes explained by global image statistics.

PubMed

Foster, David H; Amano, Kinjiro; Nascimento, Sérgio M C

2006-01-01

To what extent do observers' judgments of surface color with natural scenes depend on global image statistics? To address this question, a psychophysical experiment was performed in which images of natural scenes under two successive daylights were presented on a computer-controlled high-resolution color monitor. Observers reported whether there was a change in reflectance of a test surface in the scene. The scenes were obtained with a hyperspectral imaging system and included variously trees, shrubs, grasses, ferns, flowers, rocks, and buildings. Discrimination performance, quantified on a scale of 0 to 1 with a color-constancy index, varied from 0.69 to 0.97 over 21 scenes and two illuminant changes, from a correlated color temperature of 25,000 K to 6700 K and from 4000 K to 6700 K. The best account of these effects was provided by receptor-based rather than colorimetric properties of the images. Thus, in a linear regression, 43% of the variance in constancy index was explained by the log of the mean relative deviation in spatial cone-excitation ratios evaluated globally across the two images of a scene. A further 20% was explained by including the mean chroma of the first image and its difference from that of the second image and a further 7% by the mean difference in hue. Together, all four global color properties accounted for 70% of the variance and provided a good fit to the effects of scene and of illuminant change on color constancy, and, additionally, of changing test-surface position. By contrast, a spatial-frequency analysis of the images showed that the gradient of the luminance amplitude spectrum accounted for only 5% of the variance.

A simulation study of scene confusion factors in sensing soil moisture from orbital radar

NASA Technical Reports Server (NTRS)

Ulaby, F. T. (Principal Investigator); Dobson, M. C.; Moezzi, S.; Roth, F. T.

1983-01-01

Simulated C-band radar imagery for a 124-km by 108-km test site in eastern Kansas is used to classify soil moisture. Simulated radar resolutions are 100 m by 100 m, 1 km by 1km, and 3 km by 3 km. Distributions of actual near-surface soil moisture are established daily for a 23-day accounting period using a water budget model. Within the 23-day period, three orbital radar overpasses are simulated roughly corresponding to generally moist, wet, and dry soil moisture conditions. The radar simulations are performed by a target/sensor interaction model dependent upon a terrain model, land-use classification, and near-surface soil moisture distribution. The accuracy of soil-moisture classification is evaluated for each single-date radar observation and also for multi-date detection of relative soil moisture change. In general, the results for single-date moisture detection show that 70% to 90% of cropland can be correctly classified to within +/- 20% of the true percent of field capacity. For a given radar resolution, the expected classification accuracy is shown to be dependent upon both the general soil moisture condition and also the geographical distribution of land-use and topographic relief. An analysis of cropland, urban, pasture/rangeland, and woodland subregions within the test site indicates that multi-temporal detection of relative soil moisture change is least sensitive to classification error resulting from scene complexity and topographic effects.

Beyond the cockpit: The visual world as a flight instrument

NASA Technical Reports Server (NTRS)

Johnson, W. W.; Kaiser, M. K.; Foyle, D. C.

1992-01-01

The use of cockpit instruments to guide flight control is not always an option (e.g., low level rotorcraft flight). Under such circumstances the pilot must use out-the-window information for control and navigation. Thus it is important to determine the basis of visually guided flight for several reasons: (1) to guide the design and construction of the visual displays used in training simulators; (2) to allow modeling of visibility restrictions brought about by weather, cockpit constraints, or distortions introduced by sensor systems; and (3) to aid in the development of displays that augment the cockpit window scene and are compatible with the pilot's visual extraction of information from the visual scene. The authors are actively pursuing these questions. We have on-going studies using both low-cost, lower fidelity flight simulators, and state-of-the-art helicopter simulation research facilities. Research results will be presented on: (1) the important visual scene information used in altitude and speed control; (2) the utility of monocular, stereo, and hyperstereo cues for the control of flight; (3) perceptual effects due to the differences between normal unaided daylight vision, and that made available by various night vision devices (e.g., light intensifying goggles and infra-red sensor displays); and (4) the utility of advanced contact displays in which instrument information is made part of the visual scene, as on a 'scene linked' head-up display (e.g., displaying altimeter information on a virtual billboard located on the ground).

[Asymmetric effects of addition versus deletion on change detection task: the role of feeling of something strange].

PubMed

Uchino, Yashio; Hakoda, Yuji; Shibata, Mariko

2005-06-01

Two experiments were conducted to examine the asymmetric effect of alterations (i.e., addition versus deletion) on recognition memory. In Experiment 1, a scale for measuring the FSS (Feeling of Something Strange) was developed (n=50) using added or deleted pictures from previous research (e.g., Uchino, Hakoda, & Yamada, 2000). Result showed that altered pictures were evaluated by "pleasant" and "odd" factors. In Experiment 2, 80 participants observed 20 pictures, and then they answered whether each test picture was altered or not. Test pictures varied in significance of the objects added or deleted on a scene. Additions were detected more easily than deletions only when added object was unexpected or unusual, while deleted object was essential to a scene (TD: typicality-disrupted condition). Then, 60 participants rated the FSS scale for test pictures. Ratings of odd factor for added pictures were higher than deleted pictures presented in the TD condition. These results suggest that superiority of addition over deletion might be due to their different effect on FSS.

Impact of age-related macular degeneration on object searches in realistic panoramic scenes.

PubMed

Thibaut, Miguel; Tran, Thi-Ha-Chau; Szaffarczyk, Sebastien; Boucart, Muriel

2018-05-01

This study investigated whether realistic immersive conditions with dynamic indoor scenes presented on a large, hemispheric panoramic screen covering 180° of the visual field improved the visual search abilities of participants with age-related macular degeneration (AMD). Twenty-one participants with AMD, 16 age-matched controls and 16 young observers were included. Realistic indoor scenes were presented on a panoramic five metre diameter screen. Twelve different objects were used as targets. The participants were asked to search for a target object, shown on paper before each trial, within a room composed of various objects. A joystick was used for navigation within the scene views. A target object was present in 24 trials and absent in 24 trials. The percentage of correct detection of the target, the percentage of false alarms (that is, the detection of the target when it was absent), the number of scene views explored and the search time were measured. The search time was slower for participants with AMD than for the age-matched controls, who in turn were slower than the young participants. The participants with AMD were able to accomplish the task with a performance of 75 per cent correct detections. This was slightly lower than older controls (79.2 per cent) while young controls were at ceiling (91.7 per cent). Errors were mainly due to false alarms resulting from confusion between the target object and another object present in the scene in the target-absent trials. The outcomes of the present study indicate that, under realistic conditions, although slower than age-matched, normally sighted controls, participants with AMD were able to accomplish visual searches of objects with high accuracy. © 2017 Optometry Australia.

Scalable Track Detection in SAR CCD Images

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chow, James G; Quach, Tu-Thach

Existing methods to detect vehicle tracks in coherent change detection images, a product of combining two synthetic aperture radar images ta ken at different times of the same scene, rely on simple, fast models to label track pixels. These models, however, are often too simple to capture natural track features such as continuity and parallelism. We present a simple convolutional network architecture consisting of a series of 3-by-3 convolutions to detect tracks. The network is trained end-to-end to learn natural track features entirely from data. The network is computationally efficient and improves the F-score on a standard dataset to 0.988,more » up fr om 0.907 obtained by the current state-of-the-art method.« less

Simulating Optical Correlation on a Digital Image Processing

NASA Astrophysics Data System (ADS)

Denning, Bryan

1998-04-01

Optical Correlation is a useful tool for recognizing objects in video scenes. In this paper, we explore the characteristics of a composite filter known as the equal correlation peak synthetic discriminant function (ECP SDF). Although the ECP SDF is commonly used in coherent optical correlation systems, the authors simulated the operation of a correlator using an EPIX frame grabber/image processor board to complete this work. Issues pertaining to simulating correlation using an EPIX board will be discussed. Additionally, the ability of the ECP SDF to detect objects that have been subjected to inplane rotation and small scale changes will be addressed by correlating filters against true-class objects placed randomly within a scene. To test the robustness of the filters, the results of correlating the filter against false-class objects that closely resemble the true class will also be presented.

[Forensic aspects of gunshot suicides in Germany].

PubMed

Kunz, Sebastian Niko; Meyer, Harald J; Kraus, Sybille

2013-12-01

Suicidal gunshot wounds are a common appearance in forensic casework. The main task of the coroner lies in the detection of typical pathomorphological correlates, thus differentiating between homicide, suicide and accident. Apart from characteristic bloodstain patterns on the gun and shooting hand, the localisation of the entrance wound and the position of the weapon, additional details such as family background or medical history are important aspects of forensic investigation. An uncommon choice of weaponry and its unusual morphological manifestation often complicate the examination and reconstruction of such cases. Furthermore, due to social stigmatisation, the possibility of secondary changes by relatives at the crime scene should be considered. In addition to autopsy findings, a careful crime scene investigation and bloodstain pattern analysis, a ballistic reconstruction can be an essential tool to gain knowledge of the shooting distance and position of the gun.

A fast automatic target detection method for detecting ships in infrared scenes

NASA Astrophysics Data System (ADS)

Özertem, Kemal Arda

2016-05-01

Automatic target detection in infrared scenes is a vital task for many application areas like defense, security and border surveillance. For anti-ship missiles, having a fast and robust ship detection algorithm is crucial for overall system performance. In this paper, a straight-forward yet effective ship detection method for infrared scenes is introduced. First, morphological grayscale reconstruction is applied to the input image, followed by an automatic thresholding onto the suppressed image. For the segmentation step, connected component analysis is employed to obtain target candidate regions. At this point, it can be realized that the detection is defenseless to outliers like small objects with relatively high intensity values or the clouds. To deal with this drawback, a post-processing stage is introduced. For the post-processing stage, two different methods are used. First, noisy detection results are rejected with respect to target size. Second, the waterline is detected by using Hough transform and the detection results that are located above the waterline with a small margin are rejected. After post-processing stage, there are still undesired holes remaining, which cause to detect one object as multi objects or not to detect an object as a whole. To improve the detection performance, another automatic thresholding is implemented only to target candidate regions. Finally, two detection results are fused and post-processing stage is repeated to obtain final detection result. The performance of overall methodology is tested with real world infrared test data.

Fusion of monocular cues to detect man-made structures in aerial imagery

NASA Technical Reports Server (NTRS)

Shufelt, Jefferey; Mckeown, David M.

1991-01-01

The extraction of buildings from aerial imagery is a complex problem for automated computer vision. It requires locating regions in a scene that possess properties distinguishing them as man-made objects as opposed to naturally occurring terrain features. It is reasonable to assume that no single detection method can correctly delineate or verify buildings in every scene. A cooperative-methods paradigm is useful in approaching the building extraction problem. Using this paradigm, each extraction technique provides information which can be added or assimilated into an overall interpretation of the scene. Thus, the main objective is to explore the development of computer vision system that integrates the results of various scene analysis techniques into an accurate and robust interpretation of the underlying three dimensional scene. The problem of building hypothesis fusion in aerial imagery is discussed. Building extraction techniques are briefly surveyed, including four building extraction, verification, and clustering systems. A method for fusing the symbolic data generated by these systems is described, and applied to monocular image and stereo image data sets. Evaluation methods for the fusion results are described, and the fusion results are analyzed using these methods.

The role of cognitive switching in head-up displays. [to determine pilot ability to accurately extract information from either of two sources

NASA Technical Reports Server (NTRS)

Fischer, E.

1979-01-01

The pilot's ability to accurately extract information from either one or both of two superimposed sources of information was determined. Static, aerial, color 35 mm slides of external runway environments and slides of corresponding static head-up display (HUD) symbology were used as the sources. A three channel tachistoscope was utilized to show either the HUD alone, the scene alone, or the two slides superimposed. Cognitive performance of the pilots was assessed by determining the percentage of correct answers given to two HUD related questions, two scene related questions, or one HUD and one scene related question.

Research on hyperspectral dynamic scene and image sequence simulation

NASA Astrophysics Data System (ADS)

Sun, Dandan; Liu, Fang; Gao, Jiaobo; Sun, Kefeng; Hu, Yu; Li, Yu; Xie, Junhu; Zhang, Lei

2016-10-01

This paper presents a simulation method of hyperspectral dynamic scene and image sequence for hyperspectral equipment evaluation and target detection algorithm. Because of high spectral resolution, strong band continuity, anti-interference and other advantages, in recent years, hyperspectral imaging technology has been rapidly developed and is widely used in many areas such as optoelectronic target detection, military defense and remote sensing systems. Digital imaging simulation, as a crucial part of hardware in loop simulation, can be applied to testing and evaluation hyperspectral imaging equipment with lower development cost and shorter development period. Meanwhile, visual simulation can produce a lot of original image data under various conditions for hyperspectral image feature extraction and classification algorithm. Based on radiation physic model and material characteristic parameters this paper proposes a generation method of digital scene. By building multiple sensor models under different bands and different bandwidths, hyperspectral scenes in visible, MWIR, LWIR band, with spectral resolution 0.01μm, 0.05μm and 0.1μm have been simulated in this paper. The final dynamic scenes have high real-time and realistic, with frequency up to 100 HZ. By means of saving all the scene gray data in the same viewpoint image sequence is obtained. The analysis results show whether in the infrared band or the visible band, the grayscale variations of simulated hyperspectral images are consistent with the theoretical analysis results.

Coherent Change Detection: Theoretical Description and Experimental Results

DTIC Science & Technology

2006-08-01

Elementary Linear Algebra With Applications. John Wiley and sons, 1987. 49. J. Lee, K. W. Hoppel, and A. R. Miller, “Intensity and phase statistics of...kx, ky, kz = 0). The nature of the image recovered by the PFA may be ascertained by considering a scene consisting of an elementary point scatter...registered image pair estimate any dominant relative linear phase term between the primary image and the resampled repeat pass image and remove this

Detecting multiple DNA human profile from a mosquito blood meal.

PubMed

Rabêlo, K C N; Albuquerque, C M R; Tavares, V B; Santos, S M; Souza, C A; Oliveira, T C; Moura, R R; Brandão, L A C; Crovella, S

2016-08-26

Criminal traces commonly found at crime scenes may present mixtures from two or more individuals. The scene of the crime is important for the collection of various types of traces in order to find the perpetrator of the crime. Thus, we propose that hematophagous mosquitoes found at crime scenes can be used to perform genetic testing of human blood and aid in suspect investigation. The aim of the study was to obtain a single Aedes aegypti mosquito profile from a human DNA mixture containing genetic materials of four individuals. We also determined the effect of blood acquisition time by setting time intervals of 24, 48, and 72 h after the blood meal. STR loci and amelogenin were analyzed, and the results showed that human DNA profiles could be obtained from hematophagous mosquitos at 24 h following the blood meal. It is possible that hematophagous mosquitoes can be used as biological remains at the scene of the crime, and can be used to detect human DNA profiles of up to four individuals.

Fire flame detection based on GICA and target tracking

NASA Astrophysics Data System (ADS)

Rong, Jianzhong; Zhou, Dechuang; Yao, Wei; Gao, Wei; Chen, Juan; Wang, Jian

2013-04-01

To improve the video fire detection rate, a robust fire detection algorithm based on the color, motion and pattern characteristics of fire targets was proposed, which proved a satisfactory fire detection rate for different fire scenes. In this fire detection algorithm: (a) a rule-based generic color model was developed based on analysis on a large quantity of flame pixels; (b) from the traditional GICA (Geometrical Independent Component Analysis) model, a Cumulative Geometrical Independent Component Analysis (C-GICA) model was developed for motion detection without static background and (c) a BP neural network fire recognition model based on multi-features of the fire pattern was developed. Fire detection tests on benchmark fire video clips of different scenes have shown the robustness, accuracy and fast-response of the algorithm.

An improved non-uniformity correction algorithm and its hardware implementation on FPGA

NASA Astrophysics Data System (ADS)

Rong, Shenghui; Zhou, Huixin; Wen, Zhigang; Qin, Hanlin; Qian, Kun; Cheng, Kuanhong

2017-09-01

The Non-uniformity of Infrared Focal Plane Arrays (IRFPA) severely degrades the infrared image quality. An effective non-uniformity correction (NUC) algorithm is necessary for an IRFPA imaging and application system. However traditional scene-based NUC algorithm suffers the image blurring and artificial ghosting. In addition, few effective hardware platforms have been proposed to implement corresponding NUC algorithms. Thus, this paper proposed an improved neural-network based NUC algorithm by the guided image filter and the projection-based motion detection algorithm. First, the guided image filter is utilized to achieve the accurate desired image to decrease the artificial ghosting. Then a projection-based moving detection algorithm is utilized to determine whether the correction coefficients should be updated or not. In this way the problem of image blurring can be overcome. At last, an FPGA-based hardware design is introduced to realize the proposed NUC algorithm. A real and a simulated infrared image sequences are utilized to verify the performance of the proposed algorithm. Experimental results indicated that the proposed NUC algorithm can effectively eliminate the fix pattern noise with less image blurring and artificial ghosting. The proposed hardware design takes less logic elements in FPGA and spends less clock cycles to process one frame of image.

Characteristics of color memory for natural scenes

NASA Astrophysics Data System (ADS)

Amano, Kinjiro; Uchikawa, Keiji; Kuriki, Ichiro

2002-08-01

To study the characteristics of color memory for natural images, a memory-identification task was performed with differing color contrasts; three of the contrasts were defined by chromatic and luminance components of the image, and the others were defined with respect to the categorical colors. After observing a series of pictures successively, subjects identified the pictures using a confidence rating. Detection of increased contrasts tended to be harder than detection of decreased contrasts, suggesting that the chromaticness of pictures is enhanced in memory. Detecting changes within each color category was more difficult than across the categories. A multiple mechanism that processes color differences and categorical colors is briefly considered. 2002 Optical Society of America

Quantum correlation enhanced super-resolution localization microscopy enabled by a fibre bundle camera

PubMed Central

Israel, Yonatan; Tenne, Ron; Oron, Dan; Silberberg, Yaron

2017-01-01

Despite advances in low-light-level detection, single-photon methods such as photon correlation have rarely been used in the context of imaging. The few demonstrations, for example of subdiffraction-limited imaging utilizing quantum statistics of photons, have remained in the realm of proof-of-principle demonstrations. This is primarily due to a combination of low values of fill factors, quantum efficiencies, frame rates and signal-to-noise characteristic of most available single-photon sensitive imaging detectors. Here we describe an imaging device based on a fibre bundle coupled to single-photon avalanche detectors that combines a large fill factor, a high quantum efficiency, a low noise and scalable architecture. Our device enables localization-based super-resolution microscopy in a non-sparse non-stationary scene, utilizing information on the number of active emitters, as gathered from non-classical photon statistics. PMID:28287167

Blur Detection is Unaffected by Cognitive Load.

PubMed

Loschky, Lester C; Ringer, Ryan V; Johnson, Aaron P; Larson, Adam M; Neider, Mark; Kramer, Arthur F

2014-03-01

Blur detection is affected by retinal eccentricity, but is it also affected by attentional resources? Research showing effects of selective attention on acuity and contrast sensitivity suggests that allocating attention should increase blur detection. However, research showing that blur affects selection of saccade targets suggests that blur detection may be pre-attentive. To investigate this question, we carried out experiments in which viewers detected blur in real-world scenes under varying levels of cognitive load manipulated by the N -back task. We used adaptive threshold estimation to measure blur detection thresholds at 0°, 3°, 6°, and 9° eccentricity. Participants carried out blur detection as a single task, a single task with to-be-ignored letters, or an N-back task with four levels of cognitive load (0, 1, 2, or 3-back). In Experiment 1, blur was presented gaze-contingently for occasional single eye fixations while participants viewed scenes in preparation for an easy picture recognition memory task, and the N -back stimuli were presented auditorily. The results for three participants showed a large effect of retinal eccentricity on blur thresholds, significant effects of N -back level on N -back performance, scene recognition memory, and gaze dispersion, but no effect of N -back level on blur thresholds. In Experiment 2, we replicated Experiment 1 but presented the images tachistoscopically for 200 ms (half with, half without blur), to determine whether gaze-contingent blur presentation in Experiment 1 had produced attentional capture by blur onset during a fixation, thus eliminating any effect of cognitive load on blur detection. The results with three new participants replicated those of Experiment 1, indicating that the use of gaze-contingent blur presentation could not explain the lack of effect of cognitive load on blur detection. Thus, apparently blur detection in real-world scene images is unaffected by attentional resources, as manipulated by the cognitive load produced by the N -back task.

The effects of visual scenes on roll and pitch thresholds in pilots versus nonpilots.

PubMed

Otakeno, Shinji; Matthews, Roger S J; Folio, Les; Previc, Fred H; Lessard, Charles S

2002-02-01

Previous studies have indicated that, compared with nonpilots, pilots rely more on vision than "seat-of-the-pants" sensations when presented with visual-vestibular conflict. The objective of this study was to evaluate whether pilots and nonpilots differ in their thresholds for tilt perception while viewing visual scenes depicting simulated flight. This study was conducted in the Advanced Spatial Disorientation Demonstrator (ASDD) at Brooks AFB, TX. There were 14 subjects (7 pilots and 7 nonpilots) who recorded tilt detection thresholds in pitch and roll while exposed to sub-threshold movement in each axis. During each test run, subjects were presented with computer-generated visual scenes depicting accelerating forward flight by day or night, and a blank (control) condition. The only significant effect detected by an analysis of variance (ANOVA) was that all subjects were more sensitive to tilt in roll than in pitch [F (2,24) = 18.96, p < 0.001]. Overall, pilots had marginally higher tilt detection thresholds compared with nonpilots (p = 0.055), but the type of visual scene had no significant effect on thresholds. In this study, pilots did not demonstrate greater visual dominance over vestibular and proprioceptive cues than nonpilots, but appeared to have higher pitch and roll thresholds overall. The finding of significantly lower detection thresholds in the roll axis vs. the pitch axis was an incidental finding for both subject groups.

Radiometrically accurate scene-based nonuniformity correction for array sensors.

PubMed

Ratliff, Bradley M; Hayat, Majeed M; Tyo, J Scott

2003-10-01

A novel radiometrically accurate scene-based nonuniformity correction (NUC) algorithm is described. The technique combines absolute calibration with a recently reported algebraic scene-based NUC algorithm. The technique is based on the following principle: First, detectors that are along the perimeter of the focal-plane array are absolutely calibrated; then the calibration is transported to the remaining uncalibrated interior detectors through the application of the algebraic scene-based algorithm, which utilizes pairs of image frames exhibiting arbitrary global motion. The key advantage of this technique is that it can obtain radiometric accuracy during NUC without disrupting camera operation. Accurate estimates of the bias nonuniformity can be achieved with relatively few frames, which can be fewer than ten frame pairs. Advantages of this technique are discussed, and a thorough performance analysis is presented with use of simulated and real infrared imagery.

Virtual environments for scene of crime reconstruction and analysis

NASA Astrophysics Data System (ADS)

Howard, Toby L. J.; Murta, Alan D.; Gibson, Simon

2000-02-01

This paper describes research conducted in collaboration with Greater Manchester Police (UK), to evalute the utility of Virtual Environments for scene of crime analysis, forensic investigation, and law enforcement briefing and training. We present an illustrated case study of the construction of a high-fidelity virtual environment, intended to match a particular real-life crime scene as closely as possible. We describe and evaluate the combination of several approaches including: the use of the Manchester Scene Description Language for constructing complex geometrical models; the application of a radiosity rendering algorithm with several novel features based on human perceptual consideration; texture extraction from forensic photography; and experiments with interactive walkthroughs and large-screen stereoscopic display of the virtual environment implemented using the MAVERIK system. We also discuss the potential applications of Virtual Environment techniques in the Law Enforcement and Forensic communities.

Bag of Lines (BoL) for Improved Aerial Scene Representation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sridharan, Harini; Cheriyadat, Anil M.

2014-09-22

Feature representation is a key step in automated visual content interpretation. In this letter, we present a robust feature representation technique, referred to as bag of lines (BoL), for high-resolution aerial scenes. The proposed technique involves extracting and compactly representing low-level line primitives from the scene. The compact scene representation is generated by counting the different types of lines representing various linear structures in the scene. Through extensive experiments, we show that the proposed scene representation is invariant to scale changes and scene conditions and can discriminate urban scene categories accurately. We compare the BoL representation with the popular scalemore » invariant feature transform (SIFT) and Gabor wavelets for their classification and clustering performance on an aerial scene database consisting of images acquired by sensors with different spatial resolutions. The proposed BoL representation outperforms the SIFT- and Gabor-based representations.« less

Updating representations of learned scenes.

PubMed

Finlay, Cory A; Motes, Michael A; Kozhevnikov, Maria

2007-05-01

Two experiments were designed to compare scene recognition reaction time (RT) and accuracy patterns following observer versus scene movement. In Experiment 1, participants memorized a scene from a single perspective. Then, either the scene was rotated or the participants moved (0 degrees -360 degrees in 36 degrees increments) around the scene, and participants judged whether the objects' positions had changed. Regardless of whether the scene was rotated or the observer moved, RT increased with greater angular distance between judged and encoded views. In Experiment 2, we varied the delay (0, 6, or 12 s) between scene encoding and locomotion. Regardless of the delay, however, accuracy decreased and RT increased with angular distance. Thus, our data show that observer movement does not necessarily update representations of spatial layouts and raise questions about the effects of duration limitations and encoding points of view on the automatic spatial updating of representations of scenes.

Modeling global scene factors in attention

NASA Astrophysics Data System (ADS)

Torralba, Antonio

2003-07-01

Models of visual attention have focused predominantly on bottom-up approaches that ignored structured contextual and scene information. I propose a model of contextual cueing for attention guidance based on the global scene configuration. It is shown that the statistics of low-level features across the whole image can be used to prime the presence or absence of objects in the scene and to predict their location, scale, and appearance before exploring the image. In this scheme, visual context information can become available early in the visual processing chain, which allows modulation of the saliency of image regions and provides an efficient shortcut for object detection and recognition. 2003 Optical Society of America

AgRISTARS. Supporting research: Algorithms for scene modelling

NASA Technical Reports Server (NTRS)

Rassbach, M. E. (Principal Investigator)

1982-01-01

The requirements for a comprehensive analysis of LANDSAT or other visual data scenes are defined. The development of a general model of a scene and a computer algorithm for finding the particular model for a given scene is discussed. The modelling system includes a boundary analysis subsystem, which detects all the boundaries and lines in the image and builds a boundary graph; a continuous variation analysis subsystem, which finds gradual variations not well approximated by a boundary structure; and a miscellaneous features analysis, which includes texture, line parallelism, etc. The noise reduction capabilities of this method and its use in image rectification and registration are discussed.

Pattern-histogram-based temporal change detection using personal chest radiographs

NASA Astrophysics Data System (ADS)

Ugurlu, Yucel; Obi, Takashi; Hasegawa, Akira; Yamaguchi, Masahiro; Ohyama, Nagaaki

1999-05-01

An accurate and reliable detection of temporal changes from a pair of images has considerable interest in the medical science. Traditional registration and subtraction techniques can be applied to extract temporal differences when,the object is rigid or corresponding points are obvious. However, in radiological imaging, loss of the depth information, the elasticity of object, the absence of clearly defined landmarks and three-dimensional positioning differences constraint the performance of conventional registration techniques. In this paper, we propose a new method in order to detect interval changes accurately without using an image registration technique. The method is based on construction of so-called pattern histogram and comparison procedure. The pattern histogram is a graphic representation of the frequency counts of all allowable patterns in the multi-dimensional pattern vector space. K-means algorithm is employed to partition pattern vector space successively. Any differences in the pattern histograms imply that different patterns are involved in the scenes. In our experiment, a pair of chest radiographs of pneumoconiosis is employed and the changing histogram bins are visualized on both of the images. We found that the method can be used as an alternative way of temporal change detection, particularly when the precise image registration is not available.

Detection of exudates in fundus imagery using a constant false-alarm rate (CFAR) detector

NASA Astrophysics Data System (ADS)

Khanna, Manish; Kapoor, Elina

2014-05-01

Diabetic retinopathy is the leading cause of blindness in adults in the United States. The presence of exudates in fundus imagery is the early sign of diabetic retinopathy so detection of these lesions is essential in preventing further ocular damage. In this paper we present a novel technique to automatically detect exudates in fundus imagery that is robust against spatial and temporal variations of background noise. The detection threshold is adjusted dynamically, based on the local noise statics around the pixel under test in order to maintain a pre-determined, constant false alarm rate (CFAR). The CFAR detector is often used to detect bright targets in radar imagery where the background clutter can vary considerably from scene to scene and with angle to the scene. Similarly, the CFAR detector addresses the challenge of detecting exudate lesions in RGB and multispectral fundus imagery where the background clutter often exhibits variations in brightness and texture. These variations present a challenge to common, global thresholding detection algorithms and other methods. Performance of the CFAR algorithm is tested against a publicly available, annotated, diabetic retinopathy database and preliminary testing suggests that performance of the CFAR detector proves to be superior to techniques such as Otsu thresholding.

HDR imaging and color constancy: two sides of the same coin?

NASA Astrophysics Data System (ADS)

McCann, John J.

2011-01-01

At first, we think that High Dynamic Range (HDR) imaging is a technique for improved recordings of scene radiances. Many of us think that human color constancy is a variation of a camera's automatic white balance algorithm. However, on closer inspection, glare limits the range of light we can detect in cameras and on retinas. All scene regions below middle gray are influenced, more or less, by the glare from the bright scene segments. Instead of accurate radiance reproduction, HDR imaging works well because it preserves the details in the scene's spatial contrast. Similarly, on closer inspection, human color constancy depends on spatial comparisons that synthesize appearances from all the scene segments. Can spatial image processing play similar principle roles in both HDR imaging and color constancy?

Synthetic aperture design for increased SAR image rate

DOEpatents

Bielek, Timothy P [Albuquerque, NM; Thompson, Douglas G [Albuqerque, NM; Walker, Bruce C [Albuquerque, NM

2009-03-03

High resolution SAR images of a target scene at near video rates can be produced by using overlapped, but nevertheless, full-size synthetic apertures. The SAR images, which respectively correspond to the apertures, can be analyzed in sequence to permit detection of movement in the target scene.

Using auditory pre-information to solve the cocktail-party problem: electrophysiological evidence for age-specific differences.

PubMed

Getzmann, Stephan; Lewald, Jörg; Falkenstein, Michael

2014-01-01

Speech understanding in complex and dynamic listening environments requires (a) auditory scene analysis, namely auditory object formation and segregation, and (b) allocation of the attentional focus to the talker of interest. There is evidence that pre-information is actively used to facilitate these two aspects of the so-called "cocktail-party" problem. Here, a simulated multi-talker scenario was combined with electroencephalography to study scene analysis and allocation of attention in young and middle-aged adults. Sequences of short words (combinations of brief company names and stock-price values) from four talkers at different locations were simultaneously presented, and the detection of target names and the discrimination between critical target values were assessed. Immediately prior to speech sequences, auditory pre-information was provided via cues that either prepared auditory scene analysis or attentional focusing, or non-specific pre-information was given. While performance was generally better in younger than older participants, both age groups benefited from auditory pre-information. The analysis of the cue-related event-related potentials revealed age-specific differences in the use of pre-cues: Younger adults showed a pronounced N2 component, suggesting early inhibition of concurrent speech stimuli; older adults exhibited a stronger late P3 component, suggesting increased resource allocation to process the pre-information. In sum, the results argue for an age-specific utilization of auditory pre-information to improve listening in complex dynamic auditory environments.

Using auditory pre-information to solve the cocktail-party problem: electrophysiological evidence for age-specific differences

PubMed Central

Getzmann, Stephan; Lewald, Jörg; Falkenstein, Michael

2014-01-01

Speech understanding in complex and dynamic listening environments requires (a) auditory scene analysis, namely auditory object formation and segregation, and (b) allocation of the attentional focus to the talker of interest. There is evidence that pre-information is actively used to facilitate these two aspects of the so-called “cocktail-party” problem. Here, a simulated multi-talker scenario was combined with electroencephalography to study scene analysis and allocation of attention in young and middle-aged adults. Sequences of short words (combinations of brief company names and stock-price values) from four talkers at different locations were simultaneously presented, and the detection of target names and the discrimination between critical target values were assessed. Immediately prior to speech sequences, auditory pre-information was provided via cues that either prepared auditory scene analysis or attentional focusing, or non-specific pre-information was given. While performance was generally better in younger than older participants, both age groups benefited from auditory pre-information. The analysis of the cue-related event-related potentials revealed age-specific differences in the use of pre-cues: Younger adults showed a pronounced N2 component, suggesting early inhibition of concurrent speech stimuli; older adults exhibited a stronger late P3 component, suggesting increased resource allocation to process the pre-information. In sum, the results argue for an age-specific utilization of auditory pre-information to improve listening in complex dynamic auditory environments. PMID:25540608

Tracker Toolkit

NASA Technical Reports Server (NTRS)

Lewis, Steven J.; Palacios, David M.

2013-01-01

This software can track multiple moving objects within a video stream simultaneously, use visual features to aid in the tracking, and initiate tracks based on object detection in a subregion. A simple programmatic interface allows plugging into larger image chain modeling suites. It extracts unique visual features for aid in tracking and later analysis, and includes sub-functionality for extracting visual features about an object identified within an image frame. Tracker Toolkit utilizes a feature extraction algorithm to tag each object with metadata features about its size, shape, color, and movement. Its functionality is independent of the scale of objects within a scene. The only assumption made on the tracked objects is that they move. There are no constraints on size within the scene, shape, or type of movement. The Tracker Toolkit is also capable of following an arbitrary number of objects in the same scene, identifying and propagating the track of each object from frame to frame. Target objects may be specified for tracking beforehand, or may be dynamically discovered within a tripwire region. Initialization of the Tracker Toolkit algorithm includes two steps: Initializing the data structures for tracked target objects, including targets preselected for tracking; and initializing the tripwire region. If no tripwire region is desired, this step is skipped. The tripwire region is an area within the frames that is always checked for new objects, and all new objects discovered within the region will be tracked until lost (by leaving the frame, stopping, or blending in to the background).

Dynamics of scene representations in the human brain revealed by magnetoencephalography and deep neural networks

PubMed Central

Cichy, Radoslaw Martin; Khosla, Aditya; Pantazis, Dimitrios; Oliva, Aude

2017-01-01

Human scene recognition is a rapid multistep process evolving over time from single scene image to spatial layout processing. We used multivariate pattern analyses on magnetoencephalography (MEG) data to unravel the time course of this cortical process. Following an early signal for lower-level visual analysis of single scenes at ~100 ms, we found a marker of real-world scene size, i.e. spatial layout processing, at ~250 ms indexing neural representations robust to changes in unrelated scene properties and viewing conditions. For a quantitative model of how scene size representations may arise in the brain, we compared MEG data to a deep neural network model trained on scene classification. Representations of scene size emerged intrinsically in the model, and resolved emerging neural scene size representation. Together our data provide a first description of an electrophysiological signal for layout processing in humans, and suggest that deep neural networks are a promising framework to investigate how spatial layout representations emerge in the human brain. PMID:27039703

Detecting and collecting traces of semen and blood from outdoor crime scenes using crime scene dogs and presumptive tests.

PubMed

Skalleberg, A G; Bouzga, M M

2016-07-01

In 2009, the Norwegian police academy educated their first crime scene dogs, trained to locate traces of seminal fluid and blood in outdoor and indoor crime scenes. The Department of Forensic Biology was invited to take part in this project to educate the police in specimen collection and presumptive testing. We performed tests where seminal fluid was deposited on different outdoor surfaces from between one hour to six days, and blood on coniferous ground from between one hour to two days. For both body fluids the tests were performed with three different volumes. The crime scene dogs located the stains, and acid phosphatase/tetrabasebariumperoxide was used as presumptive tests before collection for microscopy and DNA analysis. For seminal fluid the dogs were able to locate all stains for up to two days and only the largest volume after four days. The presumptive tests confirmed the dog's detection. By microscopy we were able to detect spermatozoa for the smallest volumes up to 32h, and for the largest volume up to 4 days, and the DNA results are in correlation to these findings. For blood all the stains were detected by the dogs, except the smallest volume of blood after 32h. The presumptive tests confirmed the dog's detection. We were able to get DNA results for most stains in the timeframe 1-48h with the two largest volumes. The smallest volume shows diversities between the parallels, with no DNA results after 24h. These experiments show that it is critical that body fluids are collected within a timeframe to be able to get a good DNA result, preferably within the first 24-48h. Other parameters that should be taken into account are the weather conditions, type of surfaces and specimen collection. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Standoff alpha radiation detection for hot cell imaging and crime scene investigation

NASA Astrophysics Data System (ADS)

Kerst, Thomas; Sand, Johan; Ihantola, Sakari; Peräjärvi, Kari; Nicholl, Adrian; Hrnecek, Erich; Toivonen, Harri; Toivonen, Juha

2018-02-01

This paper presents the remote detection of alpha contamination in a nuclear facility. Alpha-active material in a shielded nuclear radiation containment chamber has been localized by optical means. Furthermore, sources of radiation danger have been identified in a staged crime scene setting. For this purpose, an electron-multiplying charge-coupled device camera was used to capture photons generated by alpha-induced air scintillation (radioluminescence). The detected radioluminescence was superimposed with a regular photograph to reveal the origin of the light and thereby the alpha radioactive material. The experimental results show that standoff detection of alpha contamination is a viable tool in radiation threat detection. Furthermore, the radioluminescence spectrum in the air is spectrally analyzed. Possibilities of camera-based alpha threat detection under various background lighting conditions are discussed.

Standoff alpha radiation detection for hot cell imaging and crime scene investigation

NASA Astrophysics Data System (ADS)

Kerst, Thomas; Sand, Johan; Ihantola, Sakari; Peräjärvi, Kari; Nicholl, Adrian; Hrnecek, Erich; Toivonen, Harri; Toivonen, Juha

2018-06-01

This paper presents the remote detection of alpha contamination in a nuclear facility. Alpha-active material in a shielded nuclear radiation containment chamber has been localized by optical means. Furthermore, sources of radiation danger have been identified in a staged crime scene setting. For this purpose, an electron-multiplying charge-coupled device camera was used to capture photons generated by alpha-induced air scintillation (radioluminescence). The detected radioluminescence was superimposed with a regular photograph to reveal the origin of the light and thereby the alpha radioactive material. The experimental results show that standoff detection of alpha contamination is a viable tool in radiation threat detection. Furthermore, the radioluminescence spectrum in the air is spectrally analyzed. Possibilities of camera-based alpha threat detection under various background lighting conditions are discussed.

Rank preserving sparse learning for Kinect based scene classification.

PubMed

Tao, Dapeng; Jin, Lianwen; Yang, Zhao; Li, Xuelong

2013-10-01

With the rapid development of the RGB-D sensors and the promptly growing population of the low-cost Microsoft Kinect sensor, scene classification, which is a hard, yet important, problem in computer vision, has gained a resurgence of interest recently. That is because the depth of information provided by the Kinect sensor opens an effective and innovative way for scene classification. In this paper, we propose a new scheme for scene classification, which applies locality-constrained linear coding (LLC) to local SIFT features for representing the RGB-D samples and classifies scenes through the cooperation between a new rank preserving sparse learning (RPSL) based dimension reduction and a simple classification method. RPSL considers four aspects: 1) it preserves the rank order information of the within-class samples in a local patch; 2) it maximizes the margin between the between-class samples on the local patch; 3) the L1-norm penalty is introduced to obtain the parsimony property; and 4) it models the classification error minimization by utilizing the least-squares error minimization. Experiments are conducted on the NYU Depth V1 dataset and demonstrate the robustness and effectiveness of RPSL for scene classification.

Rotation-invariant features for multi-oriented text detection in natural images.

PubMed

Yao, Cong; Zhang, Xin; Bai, Xiang; Liu, Wenyu; Ma, Yi; Tu, Zhuowen

2013-01-01

Texts in natural scenes carry rich semantic information, which can be used to assist a wide range of applications, such as object recognition, image/video retrieval, mapping/navigation, and human computer interaction. However, most existing systems are designed to detect and recognize horizontal (or near-horizontal) texts. Due to the increasing popularity of mobile-computing devices and applications, detecting texts of varying orientations from natural images under less controlled conditions has become an important but challenging task. In this paper, we propose a new algorithm to detect texts of varying orientations. Our algorithm is based on a two-level classification scheme and two sets of features specially designed for capturing the intrinsic characteristics of texts. To better evaluate the proposed method and compare it with the competing algorithms, we generate a comprehensive dataset with various types of texts in diverse real-world scenes. We also propose a new evaluation protocol, which is more suitable for benchmarking algorithms for detecting texts in varying orientations. Experiments on benchmark datasets demonstrate that our system compares favorably with the state-of-the-art algorithms when handling horizontal texts and achieves significantly enhanced performance on variant texts in complex natural scenes.

Satellite inventory of Minnesota forest resources

NASA Technical Reports Server (NTRS)

Bauer, Marvin E.; Burk, Thomas E.; Ek, Alan R.; Coppin, Pol R.; Lime, Stephen D.; Walsh, Terese A.; Walters, David K.; Befort, William; Heinzen, David F.

1993-01-01

The methods and results of using Landsat Thematic Mapper (TM) data to classify and estimate the acreage of forest covertypes in northeastern Minnesota are described. Portions of six TM scenes covering five counties with a total area of 14,679 square miles were classified into six forest and five nonforest classes. The approach involved the integration of cluster sampling, image processing, and estimation. Using cluster sampling, 343 plots, each 88 acres in size, were photo interpreted and field mapped as a source of reference data for classifier training and calibration of the TM data classifications. Classification accuracies of up to 75 percent were achieved; most misclassification was between similar or related classes. An inverse method of calibration, based on the error rates obtained from the classifications of the cluster plots, was used to adjust the classification class proportions for classification errors. The resulting area estimates for total forest land in the five-county area were within 3 percent of the estimate made independently by the USDA Forest Service. Area estimates for conifer and hardwood forest types were within 0.8 and 6.0 percent respectively, of the Forest Service estimates. A trial of a second method of estimating the same classes as the Forest Service resulted in standard errors of 0.002 to 0.015. A study of the use of multidate TM data for change detection showed that forest canopy depletion, canopy increment, and no change could be identified with greater than 90 percent accuracy. The project results have been the basis for the Minnesota Department of Natural Resources and the Forest Service to define and begin to implement an annual system of forest inventory which utilizes Landsat TM data to detect changes in forest cover.

Electrophysiological revelations of trial history effects in a color oddball search task.

PubMed

Shin, Eunsam; Chong, Sang Chul

2016-12-01

In visual oddball search tasks, viewing a no-target scene (i.e., no-target selection trial) leads to the facilitation or delay of the search time for a target in a subsequent trial. Presumably, this selection failure leads to biasing attentional set and prioritizing stimulus features unseen in the no-target scene. We observed attention-related ERP components and tracked the course of attentional biasing as a function of trial history. Participants were instructed to identify color oddballs (i.e., targets) shown in varied trial sequences. The number of no-target scenes preceding a target scene was increased from zero to two to reinforce attentional biasing, and colors presented in two successive no-target scenes were repeated or changed to systematically bias attention to specific colors. For the no-target scenes, the presentation of a second no-target scene resulted in an early selection of, and sustained attention to, the changed colors (mirrored in the frontal selection positivity, the anterior N2, and the P3b). For the target scenes, the N2pc indicated an earlier allocation of attention to the targets with unseen or remotely seen colors. Inhibitory control of attention, shown in the anterior N2, was greatest when the target scene was followed by repeated no-target scenes with repeated colors. Finally, search times and the P3b were influenced by both color previewing and its history. The current results demonstrate that attentional biasing can occur on a trial-by-trial basis and be influenced by both feature previewing and its history. © 2016 Society for Psychophysiological Research.

Applications of a morphological scene change detection (MSCD) for visual leak and failure identification in process and chemical engineering

NASA Astrophysics Data System (ADS)

Tickle, Andrew J.; Harvey, Paul K.; Smith, Jeremy S.

2010-10-01

Morphological Scene Change Detection (MSCD) is a process typically tasked at detecting relevant changes in a guarded environment for security applications. This can be implemented on a Field Programmable Gate Array (FPGA) by a combination of binary differences based around exclusive-OR (XOR) gates, mathematical morphology and a crucial threshold setting. The additional ability to set up the system in virtually any location due to the FPGA makes it ideal for insertion into an autonomous mobile robot for patrol duties. However, security is not the only potential of this robust algorithm. This paper details how such a system can be used for the detection of leaks in piping for use in the process and chemical industries and could be deployed as stated in the above manner. The test substance in this work was water, which was pumped either as a liquid or as low pressure steam through a simple pipe configuration with holes at set points to simulate the leaks. These holes were situated randomly at either the center of a pipe (in order to simulate an impact to it) or at a joint or corner (to simulate a failed weld). Imagery of the resultant leaks, which were visualised as drips or the accumulation of steam, which where analysed using MATLAB to determine their pixel volume in order to calibrate the trigger for the MSCD. The triggering mechanism is adaptive to make it possible in theory for the type of leak to be determined by the number of pixels in the threshold of the image and a numerical output signal to state which of the leak situations is being observed. The system was designed using the DSP Builder package from Altera so that its graphical nature is easily comprehensible to the non-embedded system designer. Furthermore, all the data from the DSP Builder simulation underwent verification against MATLAB comparisons using the image processing toolbox in order to validate the results.

Blindness to a simultaneous change of all elements in a scene, unless there is a change in summary statistics.

PubMed

Saiki, Jun; Holcombe, Alex O

2012-03-06

Sudden change of every object in a display is typically conspicuous. We find however that in the presence of a secondary task, with a display of moving dots, it can be difficult to detect a sudden change in color of all the dots. A field of 200 dots, half red and half green, half moving rightward and half moving leftward, gave the appearance of two surfaces. When all 200 dots simultaneously switched color between red and green, performance in detecting the switch was very poor. A key display characteristic was that the color proportions on each surface (summary statistics) were not affected by the color switch. When the color switch is accompanied by a change in these summary statistics, people perform well in detecting the switch, suggesting that the secondary task does not disrupt the availability of this statistical information. These findings suggest that when the change is missed, the old and new colors were represented, but the color-location pattern (binding of colors to locations) was not represented or not compared. Even after extended viewing, changes to the individual color-location pattern are not available, suggesting that the feeling of seeing these details is misleading.

Hierarchy-associated semantic-rule inference framework for classifying indoor scenes

NASA Astrophysics Data System (ADS)

Yu, Dan; Liu, Peng; Ye, Zhipeng; Tang, Xianglong; Zhao, Wei

2016-03-01

Typically, the initial task of classifying indoor scenes is challenging, because the spatial layout and decoration of a scene can vary considerably. Recent efforts at classifying object relationships commonly depend on the results of scene annotation and predefined rules, making classification inflexible. Furthermore, annotation results are easily affected by external factors. Inspired by human cognition, a scene-classification framework was proposed using the empirically based annotation (EBA) and a match-over rule-based (MRB) inference system. The semantic hierarchy of images is exploited by EBA to construct rules empirically for MRB classification. The problem of scene classification is divided into low-level annotation and high-level inference from a macro perspective. Low-level annotation involves detecting the semantic hierarchy and annotating the scene with a deformable-parts model and a bag-of-visual-words model. In high-level inference, hierarchical rules are extracted to train the decision tree for classification. The categories of testing samples are generated from the parts to the whole. Compared with traditional classification strategies, the proposed semantic hierarchy and corresponding rules reduce the effect of a variable background and improve the classification performance. The proposed framework was evaluated on a popular indoor scene dataset, and the experimental results demonstrate its effectiveness.

Multi-temporal change image inference towards false alarms reduction for an operational photogrammetric rockfall detection system

NASA Astrophysics Data System (ADS)

Partsinevelos, Panagiotis; Kallimani, Christina; Tripolitsiotis, Achilleas

2015-06-01

Rockfall incidents affect civil security and hamper the sustainable growth of hard to access mountainous areas due to casualties, injuries and infrastructure loss. Rockfall occurrences cannot be easily prevented, whereas previous studies for rockfall multiple sensor early detection systems have focused on large scale incidents. However, even a single rock may cause the loss of a human life along transportation routes thus, it is highly important to establish methods for the early detection of small-scale rockfall incidents. Terrestrial photogrammetric techniques are prone to a series of errors leading to false alarm incidents, including vegetation, wind, and non relevant change in the scene under consideration. In this study, photogrammetric monitoring of rockfall prone slopes is established and the resulting multi-temporal change imagery is processed in order to minimize false alarm incidents. Integration of remote sensing imagery analysis techniques is hereby applied to enhance early detection of a rockfall. Experimental data demonstrated that an operational system able to identify a 10-cm rock movement within a 10% false alarm rate is technically feasible.

Investigation of Cloud Properties and Atmospheric Profiles with MODIS

NASA Technical Reports Server (NTRS)

Menzel, Paul; Ackerman, Steve; Moeller, Chris; Gumley, Liam; Strabala, Kathy; Frey, Richard; Prins, Elaine; LaPorte, Dan; Wolf, Walter

1997-01-01

The WINter Cloud Experiment (WINCE) was directed and supported by personnel from the University of Wisconsin in January and February. Data sets of good quality were collected by the MODIS Airborne Simulator (MAS) and other instruments on the NASA ER2; they will be used to develop and validate cloud detection and cloud property retrievals over winter scenes (especially over snow). Software development focused on utilities needed for all of the UW product executables; preparations for Version 2 software deliveries were almost completed. A significant effort was made, in cooperation with SBRS and MCST, in characterizing and understanding MODIS PFM thermal infrared performance; crosstalk in the longwave infrared channels continues to get considerable attention.

Using VIS/NIR and IR spectral cameras for detecting and separating crime scene details

NASA Astrophysics Data System (ADS)

Kuula, Jaana; Pölönen, Ilkka; Puupponen, Hannu-Heikki; Selander, Tuomas; Reinikainen, Tapani; Kalenius, Tapani; Saari, Heikki

2012-06-01

Detecting invisible details and separating mixed evidence is critical for forensic inspection. If this can be done reliably and fast at the crime scene, irrelevant objects do not require further examination at the laboratory. This will speed up the inspection process and release resources for other critical tasks. This article reports on tests which have been carried out at the University of Jyväskylä in Finland together with the Central Finland Police Department and the National Bureau of Investigation for detecting and separating forensic details with hyperspectral technology. In the tests evidence was sought after at an assumed violent burglary scene with the use of VTT's 500-900 nm wavelength VNIR camera, Specim's 400- 1000 nm VNIR camera, and Specim's 1000-2500 nm SWIR camera. The tested details were dried blood on a ceramic plate, a stain of four types of mixed and absorbed blood, and blood which had been washed off a table. Other examined details included untreated latent fingerprints, gunshot residue, primer residue, and layered paint on small pieces of wood. All cameras could detect visible details and separate mixed paint. The SWIR camera could also separate four types of human and animal blood which were mixed in the same stain and absorbed into a fabric. None of the cameras could however detect primer residue, untreated latent fingerprints, or blood that had been washed off. The results are encouraging and indicate the need for further studies. The results also emphasize the importance of creating optimal imaging conditions into the crime scene for each kind of subjects and backgrounds.

Image processing system and method for recognizing and removing shadows from the image of a monitored scene

DOEpatents

Osbourn, Gordon C.

1996-01-01

The shadow contrast sensitivity of the human vision system is simulated by configuring information obtained from an image sensor so that the information may be evaluated with multiple pixel widths in order to produce a machine vision system able to distinguish between shadow edges and abrupt object edges. A second difference of the image intensity for each line of the image is developed and this second difference is used to screen out high frequency noise contributions from the final edge detection signals. These edge detection signals are constructed from first differences of the image intensity where the screening conditions are satisfied. The positional coincidence of oppositely signed maxima in the first difference signal taken from the right and the second difference signal taken from the left is used to detect the presence of an object edge. Alternatively, the effective number of responding operators (ENRO) may be utilized to determine the presence of object edges.

Forensic science information needs of patrol officers: The perceptions of the patrol officers, their supervisors and administrators, detectives, and crime scene technicians

NASA Astrophysics Data System (ADS)

Aydogdu, Eyup

Thanks to the rapid developments in science and technology in recent decades, especially in the past two decades, forensic sciences have been making invaluable contributions to criminal justice systems. With scientific evaluation of physical evidence, policing has become more effective in fighting crime and criminals. On the other hand, law enforcement personnel have made mistakes during the detection, protection, collection, and evaluation of physical evidence. Law enforcement personnel, especially patrol officers, have been criticized for ignoring or overlooking physical evidence at crime scenes. This study, conducted in a large American police department, was aimed to determine the perceptions of patrol officers, their supervisors and administrators, detectives, and crime scene technicians about the forensic science needs of patrol officers. The results showed no statistically significant difference among the perceptions of the said groups. More than half of the respondents perceived that 14 out of 16 areas of knowledge were important for patrol officers to have: crime scene documentation, evidence collection, interviewing techniques, firearm evidence, latent and fingerprint evidence, blood evidence, death investigation information, DNA evidence, document evidence, electronically recorded evidence, trace evidence, biological fluid evidence, arson and explosive evidence, and impression evidence. Less than half of the respondents perceived forensic entomology and plant evidence as important for patrol officers.

Landsat-7 long-term acquisition plan radiometry - evolution over time

USGS Publications Warehouse

Markham, Brian L; Goward, Samuel; Arvidson, Terry; Barsi, Julia A.; Scaramuzza, Pat

2006-01-01

The Landsat-7 Enhanced Thematic Mapper Plus instrument has two selectable gains for each spectral band. In the acquisition plan, the gains were initially set to maximize the entropy in each scene. One unintended consequence of this strategy was that, at times, dense vegetation saturated band 4 and deserts saturated all bands. A revised strategy, based on a land-cover classification and sun angle thresholds, reduced saturation, but resulted in gain changes occurring within the same scene on multiple overpasses. As the gain changes cause some loss of data and difficulties for some ground processing systems, a procedure was devised to shift the gain changes to the nearest predicted cloudy scenes. The results are still not totally satisfactory as gain changes still impact some scenes and saturation still occurs, particularly in ephemerally snow-covered regions. A primary conclusion of our experience with variable gain on Landsat-7 is that such an approach should not be employed on future global monitoring missions.

A Two-Stream Deep Fusion Framework for High-Resolution Aerial Scene Classification

PubMed Central

Liu, Fuxian

2018-01-01

One of the challenging problems in understanding high-resolution remote sensing images is aerial scene classification. A well-designed feature representation method and classifier can improve classification accuracy. In this paper, we construct a new two-stream deep architecture for aerial scene classification. First, we use two pretrained convolutional neural networks (CNNs) as feature extractor to learn deep features from the original aerial image and the processed aerial image through saliency detection, respectively. Second, two feature fusion strategies are adopted to fuse the two different types of deep convolutional features extracted by the original RGB stream and the saliency stream. Finally, we use the extreme learning machine (ELM) classifier for final classification with the fused features. The effectiveness of the proposed architecture is tested on four challenging datasets: UC-Merced dataset with 21 scene categories, WHU-RS dataset with 19 scene categories, AID dataset with 30 scene categories, and NWPU-RESISC45 dataset with 45 challenging scene categories. The experimental results demonstrate that our architecture gets a significant classification accuracy improvement over all state-of-the-art references. PMID:29581722

A Two-Stream Deep Fusion Framework for High-Resolution Aerial Scene Classification.

PubMed

Yu, Yunlong; Liu, Fuxian

2018-01-01

One of the challenging problems in understanding high-resolution remote sensing images is aerial scene classification. A well-designed feature representation method and classifier can improve classification accuracy. In this paper, we construct a new two-stream deep architecture for aerial scene classification. First, we use two pretrained convolutional neural networks (CNNs) as feature extractor to learn deep features from the original aerial image and the processed aerial image through saliency detection, respectively. Second, two feature fusion strategies are adopted to fuse the two different types of deep convolutional features extracted by the original RGB stream and the saliency stream. Finally, we use the extreme learning machine (ELM) classifier for final classification with the fused features. The effectiveness of the proposed architecture is tested on four challenging datasets: UC-Merced dataset with 21 scene categories, WHU-RS dataset with 19 scene categories, AID dataset with 30 scene categories, and NWPU-RESISC45 dataset with 45 challenging scene categories. The experimental results demonstrate that our architecture gets a significant classification accuracy improvement over all state-of-the-art references.

Generative Learning during Visual Search for Scene Changes: Enhancing Free Recall of Individuals with and without Mental Retardation

ERIC Educational Resources Information Center

Carlin, Michael T.; Soraci, Sal A.; Strawbridge, Christina P.

2005-01-01

Memory for scene changes that were identified immediately (passive encoding) or following systematic and effortful search (generative encoding) was compared across groups differing in age and intelligence. In the context of flicker methodology, generative search for the changing object involved selection and rejection of multiple potential…

Age-related macular degeneration changes the processing of visual scenes in the brain.

PubMed

Ramanoël, Stephen; Chokron, Sylvie; Hera, Ruxandra; Kauffmann, Louise; Chiquet, Christophe; Krainik, Alexandre; Peyrin, Carole

2018-01-01

In age-related macular degeneration (AMD), the processing of fine details in a visual scene, based on a high spatial frequency processing, is impaired, while the processing of global shapes, based on a low spatial frequency processing, is relatively well preserved. The present fMRI study aimed to investigate the residual abilities and functional brain changes of spatial frequency processing in visual scenes in AMD patients. AMD patients and normally sighted elderly participants performed a categorization task using large black and white photographs of scenes (indoors vs. outdoors) filtered in low and high spatial frequencies, and nonfiltered. The study also explored the effect of luminance contrast on the processing of high spatial frequencies. The contrast across scenes was either unmodified or equalized using a root-mean-square contrast normalization in order to increase contrast in high-pass filtered scenes. Performance was lower for high-pass filtered scenes than for low-pass and nonfiltered scenes, for both AMD patients and controls. The deficit for processing high spatial frequencies was more pronounced in AMD patients than in controls and was associated with lower activity for patients than controls not only in the occipital areas dedicated to central and peripheral visual fields but also in a distant cerebral region specialized for scene perception, the parahippocampal place area. Increasing the contrast improved the processing of high spatial frequency content and spurred activation of the occipital cortex for AMD patients. These findings may lead to new perspectives for rehabilitation procedures for AMD patients.

Deciding what is possible and impossible following hippocampal damage in humans.

PubMed

McCormick, Cornelia; Rosenthal, Clive R; Miller, Thomas D; Maguire, Eleanor A

2017-03-01

There is currently much debate about whether the precise role of the hippocampus in scene processing is predominantly constructive, perceptual, or mnemonic. Here, we developed a novel experimental paradigm designed to control for general perceptual and mnemonic demands, thus enabling us to specifically vary the requirement for constructive processing. We tested the ability of patients with selective bilateral hippocampal damage and matched control participants to detect either semantic (e.g., an elephant with butterflies for ears) or constructive (e.g., an endless staircase) violations in realistic images of scenes. Thus, scenes could be semantically or constructively 'possible' or 'impossible'. Importantly, general perceptual and memory requirements were similar for both types of scene. We found that the patients performed comparably to control participants when deciding whether scenes were semantically possible or impossible, but were selectively impaired at judging if scenes were constructively possible or impossible. Post-task debriefing indicated that control participants constructed flexible mental representations of the scenes in order to make constructive judgements, whereas the patients were more constrained and typically focused on specific fragments of the scenes, with little indication of having constructed internal scene models. These results suggest that one contribution the hippocampus makes to scene processing is to construct internal representations of spatially coherent scenes, which may be vital for modelling the world during both perception and memory recall. © 2016 The Authors. Hippocampus Published by Wiley Periodicals, Inc. © 2016 The Authors. Hippocampus Published by Wiley Periodicals, Inc.

MTF analysis of LANDSAT-4 Thematic Mapper

NASA Technical Reports Server (NTRS)

Schowengerdt, R.

1983-01-01

The spatial radiance distribution of a ground target must be known to a resolution at least four to five times greater than that of the system under test when measuring a satellite sensor's modulation transfer function. Calibration of the target requires either the use of man-made special purpose targets with known properties, e.g., a small reflective mirror or a dark-light linear pattern such as line or edge, or use of relatively high resolution underflight imagery to calibrate an arbitrary ground scene. Both approaches are to be used in addition a technique that utilizes an analytical model for the scene spatial frequency power spectrum is being investigated as an alternative to calibration of the scene.

MTF Analysis of LANDSAT-4 Thematic Mapper

NASA Technical Reports Server (NTRS)

Schowengerdt, R.

1985-01-01

The spatial radiance distribution of a ground target must be known to a resolution at least four to five times greater than that of the system under test when measuring a satellite sensor's modulation transfer function. Calibration of the target requires either the use of man-made special purpose targets with known properties, e.g., a small reflective mirror or a dark-light linear pattern such as line or edge, or use of relatively high resolution underflight imagery to calibrate an arbitrary ground scene. Both approaches are to be used, in addition a technique that utilizes an analytical model of the scene spatial frequency power spectrum is being investigated as an alternative to calibration of the scene.

Scheme for Terminal Guidance Utilizing Acousto-Optic Correlator.

DTIC Science & Technology

longitudinally extending acousto - optic device as index of refraction variation pattern signals. Real time signals corresponding to the scene actually being viewed...by the vehicle are propagated across the stored signals, and the results of an acousto - optic correlation are utilized to determine X and Y error

Intercomparison of Satellite-Derived Snow-Cover Maps

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Tait, Andrew B.; Foster, James L.; Chang, Alfred T. C.; Allen, Milan

1999-01-01

In anticipation of the launch of the Earth Observing System (EOS) Terra, and the PM-1 spacecraft in 1999 and 2000, respectively, efforts are ongoing to determine errors of satellite-derived snow-cover maps. EOS Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Microwave Scanning Radiometer-E (AMSR-E) snow-cover products will be produced. For this study we compare snow maps covering the same study area acquired from different sensors using different snow- mapping algorithms. Four locations are studied: 1) southern Saskatchewan; 2) a part of New England (New Hampshire, Vermont and Massachusetts) and eastern New York; 3) central Idaho and western Montana; and 4) parts of North and South Dakota. Snow maps were produced using a prototype MODIS snow-mapping algorithm used on Landsat Thematic Mapper (TM) scenes of each study area at 30-m and when the TM data were degraded to 1 -km resolution. National Operational Hydrologic Remote Sensing Center (NOHRSC) 1 -km resolution snow maps were also used, as were snow maps derived from 1/2 deg. x 1/2 deg. resolution Special Sensor Microwave Imager (SSM/1) data. A land-cover map derived from the International Geosphere-Biosphere Program (IGBP) land-cover map of North America was also registered to the scenes. The TM, NOHRSC and SSM/I snow maps, and land-cover maps were compared digitally. In most cases, TM-derived maps show less snow cover than the NOHRSC and SSM/I maps because areas of incomplete snow cover in forests (e.g., tree canopies, branches and trunks) are seen in the TM data, but not in the coarser-resolution maps. The snow maps generally agree with respect to the spatial variability of the snow cover. The 30-m resolution TM data provide the most accurate snow maps, and are thus used as the baseline for comparison with the other maps. Comparisons show that the percent change in amount of snow cover relative to the 3 0-m resolution TM maps is lowest using the TM I -km resolution maps, ranging from 0 to 40%. The highest percent change (less than 100%) is found in the New England study area, probably due to the presence of patchy snow cover. A scene with patchy snow cover is more difficult to map accurately than is a scene with a well-defined snowline such as is found on the North and South Dakota scene where the percent change ranged from 0 to 40%. There are also some important differences in the amount of snow mapped using the two different SSM/I algorithms because they utilize different channels.

Face recognition for criminal identification: An implementation of principal component analysis for face recognition

NASA Astrophysics Data System (ADS)

Abdullah, Nurul Azma; Saidi, Md. Jamri; Rahman, Nurul Hidayah Ab; Wen, Chuah Chai; Hamid, Isredza Rahmi A.

2017-10-01

In practice, identification of criminal in Malaysia is done through thumbprint identification. However, this type of identification is constrained as most of criminal nowadays getting cleverer not to leave their thumbprint on the scene. With the advent of security technology, cameras especially CCTV have been installed in many public and private areas to provide surveillance activities. The footage of the CCTV can be used to identify suspects on scene. However, because of limited software developed to automatically detect the similarity between photo in the footage and recorded photo of criminals, the law enforce thumbprint identification. In this paper, an automated facial recognition system for criminal database was proposed using known Principal Component Analysis approach. This system will be able to detect face and recognize face automatically. This will help the law enforcements to detect or recognize suspect of the case if no thumbprint present on the scene. The results show that about 80% of input photo can be matched with the template data.

Hdr Imaging for Feature Detection on Detailed Architectural Scenes

NASA Astrophysics Data System (ADS)

Kontogianni, G.; Stathopoulou, E. K.; Georgopoulos, A.; Doulamis, A.

2015-02-01

3D reconstruction relies on accurate detection, extraction, description and matching of image features. This is even truer for complex architectural scenes that pose needs for 3D models of high quality, without any loss of detail in geometry or color. Illumination conditions influence the radiometric quality of images, as standard sensors cannot depict properly a wide range of intensities in the same scene. Indeed, overexposed or underexposed pixels cause irreplaceable information loss and degrade digital representation. Images taken under extreme lighting environments may be thus prohibitive for feature detection/extraction and consequently for matching and 3D reconstruction. High Dynamic Range (HDR) images could be helpful for these operators because they broaden the limits of illumination range that Standard or Low Dynamic Range (SDR/LDR) images can capture and increase in this way the amount of details contained in the image. Experimental results of this study prove this assumption as they examine state of the art feature detectors applied both on standard dynamic range and HDR images.

Multiple Vehicle Detection and Segmentation in Malaysia Traffic Flow

NASA Astrophysics Data System (ADS)

Fariz Hasan, Ahmad; Fikri Che Husin, Mohd; Affendi Rosli, Khairul; Norhafiz Hashim, Mohd; Faiz Zainal Abidin, Amar

2018-03-01

Vision based system are widely used in the field of Intelligent Transportation System (ITS) to extract a large amount of information to analyze traffic scenes. By rapid number of vehicles on the road as well as significant increase on cameras dictated the need for traffic surveillance systems. This system can take over the burden some task was performed by human operator in traffic monitoring centre. The main technique proposed by this paper is concentrated on developing a multiple vehicle detection and segmentation focusing on monitoring through Closed Circuit Television (CCTV) video. The system is able to automatically segment vehicle extracted from heavy traffic scene by optical flow estimation alongside with blob analysis technique in order to detect the moving vehicle. Prior to segmentation, blob analysis technique will compute the area of interest region corresponding to moving vehicle which will be used to create bounding box on that particular vehicle. Experimental validation on the proposed system was performed and the algorithm is demonstrated on various set of traffic scene.

Stereoscopic augmented reality with pseudo-realistic global illumination effects

NASA Astrophysics Data System (ADS)

de Sorbier, Francois; Saito, Hideo

2014-03-01

Recently, augmented reality has become very popular and has appeared in our daily life with gaming, guiding systems or mobile phone applications. However, inserting object in such a way their appearance seems natural is still an issue, especially in an unknown environment. This paper presents a framework that demonstrates the capabilities of Kinect for convincing augmented reality in an unknown environment. Rather than pre-computing a reconstruction of the scene like proposed by most of the previous method, we propose a dynamic capture of the scene that allows adapting to live changes of the environment. Our approach, based on the update of an environment map, can also detect the position of the light sources. Combining information from the environment map, the light sources and the camera tracking, we can display virtual objects using stereoscopic devices with global illumination effects such as diffuse and mirror reflections, refractions and shadows in real time.

Topography-Dependent Motion Compensation: Application to UAVSAR Data

NASA Technical Reports Server (NTRS)

Jones, Cathleen E.; Hensley, Scott; Michel, Thierry

2009-01-01

The UAVSAR L-band synthetic aperture radar system has been designed for repeat track interferometry in support of Earth science applications that require high-precision measurements of small surface deformations over timescales from hours to years. Conventional motion compensation algorithms, which are based upon assumptions of a narrow beam and flat terrain, yield unacceptably large errors in areas with even moderate topographic relief, i.e., in most areas of interest. This often limits the ability to achieve sub-centimeter surface change detection over significant portions of an acquired scene. To reduce this source of error in the interferometric phase, we have implemented an advanced motion compensation algorithm that corrects for the scene topography and radar beam width. Here we discuss the algorithm used, its implementation in the UAVSAR data processor, and the improvement in interferometric phase and correlation achieved in areas with significant topographic relief.

The Effects of Similarity on High-Level Visual Working Memory Processing.

PubMed

Yang, Li; Mo, Lei

2017-01-01

Similarity has been observed to have opposite effects on visual working memory (VWM) for complex images. How can these discrepant results be reconciled? To answer this question, we used a change-detection paradigm to test visual working memory performance for multiple real-world objects. We found that working memory for moderate similarity items was worse than that for either high or low similarity items. This pattern was unaffected by manipulations of stimulus type (faces vs. scenes), encoding duration (limited vs. self-paced), and presentation format (simultaneous vs. sequential). We also found that the similarity effects differed in strength in different categories (scenes vs. faces). These results suggest that complex real-world objects are represented using a centre-surround inhibition organization . These results support the category-specific cortical resource theory and further suggest that centre-surround inhibition organization may differ by category.

Research on hyperspectral dynamic scene and image sequence simulation

NASA Astrophysics Data System (ADS)

Sun, Dandan; Gao, Jiaobo; Sun, Kefeng; Hu, Yu; Li, Yu; Xie, Junhu; Zhang, Lei

2016-10-01

This paper presents a simulation method of hyper-spectral dynamic scene and image sequence for hyper-spectral equipment evaluation and target detection algorithm. Because of high spectral resolution, strong band continuity, anti-interference and other advantages, in recent years, hyper-spectral imaging technology has been rapidly developed and is widely used in many areas such as optoelectronic target detection, military defense and remote sensing systems. Digital imaging simulation, as a crucial part of hardware in loop simulation, can be applied to testing and evaluation hyper-spectral imaging equipment with lower development cost and shorter development period. Meanwhile, visual simulation can produce a lot of original image data under various conditions for hyper-spectral image feature extraction and classification algorithm. Based on radiation physic model and material characteristic parameters this paper proposes a generation method of digital scene. By building multiple sensor models under different bands and different bandwidths, hyper-spectral scenes in visible, MWIR, LWIR band, with spectral resolution 0.01μm, 0.05μm and 0.1μm have been simulated in this paper. The final dynamic scenes have high real-time and realistic, with frequency up to 100 HZ. By means of saving all the scene gray data in the same viewpoint image sequence is obtained. The analysis results show whether in the infrared band or the visible band, the grayscale variations of simulated hyper-spectral images are consistent with the theoretical analysis results.

Laser-based structural sensing and surface damage detection

NASA Astrophysics Data System (ADS)

Guldur, Burcu

Damage due to age or accumulated damage from hazards on existing structures poses a worldwide problem. In order to evaluate the current status of aging, deteriorating and damaged structures, it is vital to accurately assess the present conditions. It is possible to capture the in situ condition of structures by using laser scanners that create dense three-dimensional point clouds. This research investigates the use of high resolution three-dimensional terrestrial laser scanners with image capturing abilities as tools to capture geometric range data of complex scenes for structural engineering applications. Laser scanning technology is continuously improving, with commonly available scanners now capturing over 1,000,000 texture-mapped points per second with an accuracy of ~2 mm. However, automatically extracting meaningful information from point clouds remains a challenge, and the current state-of-the-art requires significant user interaction. The first objective of this research is to use widely accepted point cloud processing steps such as registration, feature extraction, segmentation, surface fitting and object detection to divide laser scanner data into meaningful object clusters and then apply several damage detection methods to these clusters. This required establishing a process for extracting important information from raw laser-scanned data sets such as the location, orientation and size of objects in a scanned region, and location of damaged regions on a structure. For this purpose, first a methodology for processing range data to identify objects in a scene is presented and then, once the objects from model library are correctly detected and fitted into the captured point cloud, these fitted objects are compared with the as-is point cloud of the investigated object to locate defects on the structure. The algorithms are demonstrated on synthetic scenes and validated on range data collected from test specimens and test-bed bridges. The second objective of this research is to combine useful information extracted from laser scanner data with color information, which provides information in the fourth dimension that enables detection of damage types such as cracks, corrosion, and related surface defects that are generally difficult to detect using only laser scanner data; moreover, the color information also helps to track volumetric changes on structures such as spalling. Although using images with varying resolution to detect cracks is an extensively researched topic, damage detection using laser scanners with and without color images is a new research area that holds many opportunities for enhancing the current practice of visual inspections. The aim is to combine the best features of laser scans and images to create an automatic and effective surface damage detection method, which will reduce the need for skilled labor during visual inspections and allow automatic documentation of related information. This work enables developing surface damage detection strategies that integrate existing condition rating criteria for a wide range damage types that are collected under three main categories: small deformations already existing on the structure (cracks); damage types that induce larger deformations, but where the initial topology of the structure has not changed appreciably (e.g., bent members); and large deformations where localized changes in the topology of the structure have occurred (e.g., rupture, discontinuities and spalling). The effectiveness of the developed damage detection algorithms are validated by comparing the detection results with the measurements taken from test specimens and test-bed bridges.

Modern Approaches to the Computation of the Probability of Target Detection in Cluttered Environments

NASA Astrophysics Data System (ADS)

Meitzler, Thomas J.

The field of computer vision interacts with fields such as psychology, vision research, machine vision, psychophysics, mathematics, physics, and computer science. The focus of this thesis is new algorithms and methods for the computation of the probability of detection (Pd) of a target in a cluttered scene. The scene can be either a natural visual scene such as one sees with the naked eye (visual), or, a scene displayed on a monitor with the help of infrared sensors. The relative clutter and the temperature difference between the target and background (DeltaT) are defined and then used to calculate a relative signal -to-clutter ratio (SCR) from which the Pd is calculated for a target in a cluttered scene. It is shown how this definition can include many previous definitions of clutter and (DeltaT). Next, fuzzy and neural -fuzzy techniques are used to calculate the Pd and it is shown how these methods can give results that have a good correlation with experiment. The experimental design for actually measuring the Pd of a target by observers is described. Finally, wavelets are applied to the calculation of clutter and it is shown how this new definition of clutter based on wavelets can be used to compute the Pd of a target.

Inattentional blindness and augmented-vision displays: Effects of cartoon-like filtering and attended scene

PubMed Central

Apfelbaum, Henry L.; Apfelbaum, Doris H.; Woods, Russell L.; Peli, Eli

2007-01-01

Augmented-vision devices that we are developing to aid people with low vision (impaired vision) employ vision multiplexing – the simultaneous presentation of two different views to one or both eyes. This approach enables compensation for vision deficits without depriving the wearers of their normal views of the scene. Ideally, wearers would make use of the simultaneous views to alert them to potential mobility hazards, without a need to divide attention consciously. Inattentional blindness, the frequent inability to notice otherwise-obvious events in one scene while paying attention to another, overlapping, scene, works against that sort of augmentation, so we are investigating ways to mitigate it. In this study we filtered the augmented view, creating cartoon-like representations, to make it easier to detect significant features in that view and to minimise interference with the normal view. We reproduced a classic inattentional blindness experiment to evaluate the effect, and found that, surprisingly, edge filtering had no detectable effect – positive or negative – on the noticing of unexpected events in the unattended scene. We then modified the experiment to determine if the inattentional blindness was due to the confusion of overlaid views or simply a matter of attention, and found the latter to be the case. PMID:18426419

Detecting text in natural scenes with multi-level MSER and SWT

NASA Astrophysics Data System (ADS)

Lu, Tongwei; Liu, Renjun

2018-04-01

The detection of the characters in the natural scene is susceptible to factors such as complex background, variable viewing angle and diverse forms of language, which leads to poor detection results. Aiming at these problems, a new text detection method was proposed, which consisted of two main stages, candidate region extraction and text region detection. At first stage, the method used multiple scale transformations of original image and multiple thresholds of maximally stable extremal regions (MSER) to detect the text regions which could detect character regions comprehensively. At second stage, obtained SWT maps by using the stroke width transform (SWT) algorithm to compute the candidate regions, then using cascaded classifiers to propose non-text regions. The proposed method was evaluated on the standard benchmark datasets of ICDAR2011 and the datasets that we made our own data sets. The experiment results showed that the proposed method have greatly improved that compared to other text detection methods.

-The Influence of Scene Context on Parafoveal Processing of Objects.

PubMed

Castelhano, Monica S; Pereira, Effie J

2017-04-21

Many studies in reading have shown the enhancing effect of context on the processing of a word before it is directly fixated (parafoveal processing of words; Balota et al., 1985; Balota & Rayner, 1983; Ehrlich & Rayner, 1981). Here, we examined whether scene context influences the parafoveal processing of objects and enhances the extraction of object information. Using a modified boundary paradigm (Rayner, 1975), the Dot-Boundary paradigm, participants fixated on a suddenly-onsetting cue before the preview object would onset 4° away. The preview object could be identical to the target, visually similar, visually dissimilar, or a control (black rectangle). The preview changed to the target object once a saccade toward the object was made. Critically, the objects were presented on either a consistent or an inconsistent scene background. Results revealed that there was a greater processing benefit for consistent than inconsistent scene backgrounds and that identical and visually similar previews produced greater processing benefits than other previews. In the second experiment, we added an additional context condition in which the target location was inconsistent, but the scene semantics remained consistent. We found that changing the location of the target object disrupted the processing benefit derived from the consistent context. Most importantly, across both experiments, the effect of preview was not enhanced by scene context. Thus, preview information and scene context appear to independently boost the parafoveal processing of objects without any interaction from object-scene congruency.

Cat and mouse search: the influence of scene and object analysis on eye movements when targets change locations during search.

PubMed

Hillstrom, Anne P; Segabinazi, Joice D; Godwin, Hayward J; Liversedge, Simon P; Benson, Valerie

2017-02-19

We explored the influence of early scene analysis and visible object characteristics on eye movements when searching for objects in photographs of scenes. On each trial, participants were shown sequentially either a scene preview or a uniform grey screen (250 ms), a visual mask, the name of the target and the scene, now including the target at a likely location. During the participant's first saccade during search, the target location was changed to: (i) a different likely location, (ii) an unlikely but possible location or (iii) a very implausible location. The results showed that the first saccade landed more often on the likely location in which the target re-appeared than on unlikely or implausible locations, and overall the first saccade landed nearer the first target location with a preview than without. Hence, rapid scene analysis influenced initial eye movement planning, but availability of the target rapidly modified that plan. After the target moved, it was found more quickly when it appeared in a likely location than when it appeared in an unlikely or implausible location. The findings show that both scene gist and object properties are extracted rapidly, and are used in conjunction to guide saccadic eye movements during visual search.This article is part of the themed issue 'Auditory and visual scene analysis'. © 2017 The Author(s).

[Asymmetric confusability effects in recognition memory of line drawings].

PubMed

Uchino, Y; Hakoda, Y; Yamada, N

2000-06-01

Experiment 1 and 2 examined the effect of addition or deletion changes in a picture recognition test. Addition and deletion applied to original pictures were referred to deviation change, and addition to deleted pictures or deletion from added pictures was referred to restoration change. In Experiment 1 (n = 40), elaborative detailed information contained in line drawings of scenes was changed whereas one of major features in a single object was changed in Experiment 2 (n = 36). In the test phase, participants indicated whether each test picture was changed or not from the picture they had seen in the study phase. Deviation change had a greater effect on detection performance than restoration only in Experiment 2. Additions were easily detected than deletions only in deviation change in Experiment 2. In Experiment 3, 51 participants rated impression of added or deleted pictures used in Experiment 2. Impression of added pictures was significantly different from that of deleted in 3 factors. These results suggest that superiority of additions over deletions might be due to their different impression change.

Monitoring Coral Growth - the Dichotomy Between Underwater Photogrammetry and Geodetic Control Network

NASA Astrophysics Data System (ADS)

Neyer, F.; Nocerino, E.; Gruen, A.

2018-05-01

Creating 3-dimensional (3D) models of underwater scenes has become a common approach for monitoring coral reef changes and its structural complexity. Also in underwater archeology, 3D models are often created using underwater optical imagery. In this paper, we focus on the aspect of detecting small changes in the coral reef using a multi-temporal photogrammetric modelling approach, which requires a high quality control network. We show that the quality of a good geodetic network limits the direct change detection, i.e., without any further registration process. As the photogrammetric accuracy is expected to exceed the geodetic network accuracy by at least one order of magnitude, we suggest to do a fine registration based on a number of signalized points. This work is part of the Moorea Island Digital Ecosystem Avatar (IDEA) project that has been initiated in 2013 by a group of international researchers (https://mooreaidea.ethz.ch/).

Investigation of the effects of construction and stage filling of reservoirs on the environment and ecology: Preproject baseline. [Missouri

NASA Technical Reports Server (NTRS)

Riggins, R. E. (Principal Investigator); Anderson, J. R.

1977-01-01

The author has identified the following significant results: (1) LANDSAT imagery can be used effectively as a baseline for detection of environmental change, resulting from construction of a major inland reservoir. (2) Forest cover can be observed adequately on two-band composite enlargements at a scale of 1:130,000. (3) Forest cover delineated on LANDSAT enlargements compares accurately with ground truth at a scale of 1:250,000. (4) A dual image mapping technique superimposing winter, summer, and spring scenes using the zoom transfer scope facilitates the determination. (5) The same technique can be used to detect changes in the project area, resulting from construction activities. (6) High altitude aircraft imagery can also be used to interpret changes in land use and forest type. (7) Construction operations can be more clearly detailed on the air photos than on LANDSAT imagery.

Acquaintance Rape: Applying Crime Scene Analysis to the Prediction of Sexual Recidivism.

PubMed

Lehmann, Robert J B; Goodwill, Alasdair M; Hanson, R Karl; Dahle, Klaus-Peter

2016-10-01

The aim of the current study was to enhance the assessment and predictive accuracy of risk assessments for sexual offenders by utilizing detailed crime scene analysis (CSA). CSA was conducted on a sample of 247 male acquaintance rapists from Berlin (Germany) using a nonmetric, multidimensional scaling (MDS) Behavioral Thematic Analysis (BTA) approach. The age of the offenders at the time of the index offense ranged from 14 to 64 years (M = 32.3; SD = 11.4). The BTA procedure revealed three behavioral themes of hostility, criminality, and pseudo-intimacy, consistent with previous CSA research on stranger rape. The construct validity of the three themes was demonstrated through correlational analyses with known sexual offending measures and criminal histories. The themes of hostility and pseudo-intimacy were significant predictors of sexual recidivism. In addition, the pseudo-intimacy theme led to a significant increase in the incremental validity of the Static-99 actuarial risk assessment instrument for the prediction of sexual recidivism. The results indicate the potential utility and validity of crime scene behaviors in the applied risk assessment of sexual offenders. © The Author(s) 2015.

Dynamics of scene representations in the human brain revealed by magnetoencephalography and deep neural networks.

PubMed

Martin Cichy, Radoslaw; Khosla, Aditya; Pantazis, Dimitrios; Oliva, Aude

2017-06-01

Human scene recognition is a rapid multistep process evolving over time from single scene image to spatial layout processing. We used multivariate pattern analyses on magnetoencephalography (MEG) data to unravel the time course of this cortical process. Following an early signal for lower-level visual analysis of single scenes at ~100ms, we found a marker of real-world scene size, i.e. spatial layout processing, at ~250ms indexing neural representations robust to changes in unrelated scene properties and viewing conditions. For a quantitative model of how scene size representations may arise in the brain, we compared MEG data to a deep neural network model trained on scene classification. Representations of scene size emerged intrinsically in the model, and resolved emerging neural scene size representation. Together our data provide a first description of an electrophysiological signal for layout processing in humans, and suggest that deep neural networks are a promising framework to investigate how spatial layout representations emerge in the human brain. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Acceptability and perceived utility of drone technology among emergency medical service responders and incident commanders for mass casualty incident management.

PubMed

Hart, Alexander; Chai, Peter R; Griswold, Matthew K; Lai, Jeffrey T; Boyer, Edward W; Broach, John

2017-01-01

This study seeks to understand the acceptability and perceived utility of unmanned aerial vehicle (UAV) technology to Mass Casualty Incidents (MCI) scene management. Qualitative questionnaires regarding the ease of operation, perceived usefulness, and training time to operate UAVs were administered to Emergency Medical Technicians (n = 15). A Single Urban New England Academic Tertiary Care Medical Center. Front-line emergency medical service (EMS) providers and senior EMS personnel in Incident Commander roles. Data from this pilot study indicate that EMS responders are accepting to deploying and operating UAV technology in a disaster scenario. Additionally, they perceived UAV technology as easy to adopt yet impactful in improving MCI scene management.

A read-in IC for infrared scene projectors with voltage drop compensation for improved uniformity of emitter current

NASA Astrophysics Data System (ADS)

Cho, Min Ji; Shin, Uisub; Lee, Hee Chul

2017-05-01

This paper proposes a read-in integrated circuit (RIIC) for infrared scene projectors, which compensates for the voltage drops in ground lines in order to improve the uniformity of the emitter current. A current output digital-to-analog converter is utilized to convert digital scene data into scene data currents. The unit cells in the array receive the scene data current and convert it into data voltage, which simultaneously self-adjusts to account for the voltage drop in the ground line in order to generate the desired emitter current independently of variations in the ground voltage. A 32 × 32 RIIC unit cell array was designed and fabricated using a 0.18-μm CMOS process. The experimental results demonstrate that the proposed RIIC can output a maximum emitter current of 150 μA and compensate for a voltage drop in the ground line of up to 500 mV under a 3.3-V supply. The uniformity of the emitter current is significantly improved compared to that of a conventional RIIC.

Eye guidance during real-world scene search: The role color plays in central and peripheral vision.

PubMed

Nuthmann, Antje; Malcolm, George L

2016-01-01

The visual system utilizes environmental features to direct gaze efficiently when locating objects. While previous research has isolated various features' contributions to gaze guidance, these studies generally used sparse displays and did not investigate how features facilitated search as a function of their location on the visual field. The current study investigated how features across the visual field--particularly color--facilitate gaze guidance during real-world search. A gaze-contingent window followed participants' eye movements, restricting color information to specified regions. Scene images were presented in full color, with color in the periphery and gray in central vision or gray in the periphery and color in central vision, or in grayscale. Color conditions were crossed with a search cue manipulation, with the target cued either with a word label or an exact picture. Search times increased as color information in the scene decreased. A gaze-data based decomposition of search time revealed color-mediated effects on specific subprocesses of search. Color in peripheral vision facilitated target localization, whereas color in central vision facilitated target verification. Picture cues facilitated search, with the effects of cue specificity and scene color combining additively. When available, the visual system utilizes the environment's color information to facilitate different real-world visual search behaviors based on the location within the visual field.

Crime Scene Investigation.

ERIC Educational Resources Information Center

Harris, Barbara; Kohlmeier, Kris; Kiel, Robert D.

Casting students in grades 5 through 12 in the roles of reporters, lawyers, and detectives at the scene of a crime, this interdisciplinary activity involves participants in the intrigue and drama of crime investigation. Using a hands-on, step-by-step approach, students work in teams to investigate a crime and solve a mystery. Through role-playing…

What you see is what you expect: rapid scene understanding benefits from prior experience.

PubMed

Greene, Michelle R; Botros, Abraham P; Beck, Diane M; Fei-Fei, Li

2015-05-01

Although we are able to rapidly understand novel scene images, little is known about the mechanisms that support this ability. Theories of optimal coding assert that prior visual experience can be used to ease the computational burden of visual processing. A consequence of this idea is that more probable visual inputs should be facilitated relative to more unlikely stimuli. In three experiments, we compared the perceptions of highly improbable real-world scenes (e.g., an underwater press conference) with common images matched for visual and semantic features. Although the two groups of images could not be distinguished by their low-level visual features, we found profound deficits related to the improbable images: Observers wrote poorer descriptions of these images (Exp. 1), had difficulties classifying the images as unusual (Exp. 2), and even had lower sensitivity to detect these images in noise than to detect their more probable counterparts (Exp. 3). Taken together, these results place a limit on our abilities for rapid scene perception and suggest that perception is facilitated by prior visual experience.

Combined optimization of image-gathering and image-processing systems for scene feature detection

NASA Technical Reports Server (NTRS)

Halyo, Nesim; Arduini, Robert F.; Samms, Richard W.

1987-01-01

The relationship between the image gathering and image processing systems for minimum mean squared error estimation of scene characteristics is investigated. A stochastic optimization problem is formulated where the objective is to determine a spatial characteristic of the scene rather than a feature of the already blurred, sampled and noisy image data. An analytical solution for the optimal characteristic image processor is developed. The Wiener filter for the sampled image case is obtained as a special case, where the desired characteristic is scene restoration. Optimal edge detection is investigated using the Laplacian operator x G as the desired characteristic, where G is a two dimensional Gaussian distribution function. It is shown that the optimal edge detector compensates for the blurring introduced by the image gathering optics, and notably, that it is not circularly symmetric. The lack of circular symmetry is largely due to the geometric effects of the sampling lattice used in image acquisition. The optimal image gathering optical transfer function is also investigated and the results of a sensitivity analysis are shown.

Real-time detection of moving objects from moving vehicles using dense stereo and optical flow

NASA Technical Reports Server (NTRS)

Talukder, Ashit; Matthies, Larry

2004-01-01

Dynamic scene perception is very important for autonomous vehicles operating around other moving vehicles and humans. Most work on real-time object tracking from moving platforms has used sparse features or assumed flat scene structures. We have recently extended a real-time, dense stereo system to include realtime, dense optical flow, enabling more comprehensive dynamic scene analysis. We describe algorithms to robustly estimate 6-DOF robot egomotion in the presence of moving objects using dense flow and dense stereo. We then use dense stereo and egomotion estimates to identify & other moving objects while the robot itself is moving. We present results showing accurate egomotion estimation and detection of moving people and vehicles under general 6-DOF motion of the robot and independently moving objects. The system runs at 18.3 Hz on a 1.4 GHz Pentium M laptop, computing 160x120 disparity maps and optical flow fields, egomotion, and moving object segmentation. We believe this is a significant step toward general unconstrained dynamic scene analysis for mobile robots, as well as for improved position estimation where GPS is unavailable.

Real-time detection of moving objects from moving vehicles using dense stereo and optical flow

NASA Technical Reports Server (NTRS)

Talukder, Ashit; Matthies, Larry

2004-01-01

Dynamic scene perception is very important for autonomous vehicles operating around other moving vehicles and humans. Most work on real-time object tracking from moving platforms has used sparse features or assumed flat scene structures. We have recently extended a real-time, dense stereo system to include real-time, dense optical flow, enabling more comprehensive dynamic scene analysis. We describe algorithms to robustly estimate 6-DOF robot egomotion in the presence of moving objects using dense flow and dense stereo. We then use dense stereo and egomotion estimates to identity other moving objects while the robot itself is moving. We present results showing accurate egomotion estimation and detection of moving people and vehicles under general 6-DOF motion of the robot and independently moving objects. The system runs at 18.3 Hz on a 1.4 GHz Pentium M laptop, computing 160x120 disparity maps and optical flow fields, egomotion, and moving object segmentation. We believe this is a significant step toward general unconstrained dynamic scene analysis for mobile robots, as well as for improved position estimation where GPS is unavailable.

Real-time Detection of Moving Objects from Moving Vehicles Using Dense Stereo and Optical Flow

NASA Technical Reports Server (NTRS)

Talukder, Ashit; Matthies, Larry

2004-01-01

Dynamic scene perception is very important for autonomous vehicles operating around other moving vehicles and humans. Most work on real-time object tracking from moving platforms has used sparse features or assumed flat scene structures. We have recently extended a real-time. dense stereo system to include realtime. dense optical flow, enabling more comprehensive dynamic scene analysis. We describe algorithms to robustly estimate 6-DOF robot egomotion in the presence of moving objects using dense flow and dense stereo. We then use dense stereo and egomotion estimates to identify other moving objects while the robot itself is moving. We present results showing accurate egomotion estimation and detection of moving people and vehicles under general 6DOF motion of the robot and independently moving objects. The system runs at 18.3 Hz on a 1.4 GHz Pentium M laptop. computing 160x120 disparity maps and optical flow fields, egomotion, and moving object segmentation. We believe this is a significant step toward general unconstrained dynamic scene analysis for mobile robots, as well as for improved position estimation where GPS is unavailable.

Guaranteeing Failsafe Operation of Extended-Scene Shack-Hartmann Wavefront Sensor Algorithm

NASA Technical Reports Server (NTRS)

Sidick, Erikin

2009-01-01

A Shack-Hartmann sensor (SHS) is an optical instrument consisting of a lenslet array and a camera. It is widely used for wavefront sensing in optical testing and astronomical adaptive optics. The camera is placed at the focal point of the lenslet array and points at a star or any other point source. The image captured is an array of spot images. When the wavefront error at the lenslet array changes, the position of each spot measurably shifts from its original position. Determining the shifts of the spot images from their reference points shows the extent of the wavefront error. An adaptive cross-correlation (ACC) algorithm has been developed to use scenes as well as point sources for wavefront error detection. Qualifying an extended scene image is often not an easy task due to changing conditions in scene content, illumination level, background, Poisson noise, read-out noise, dark current, sampling format, and field of view. The proposed new technique based on ACC algorithm analyzes the effects of these conditions on the performance of the ACC algorithm and determines the viability of an extended scene image. If it is viable, then it can be used for error correction; if it is not, the image fails and will not be further processed. By potentially testing for a wide variety of conditions, the algorithm s accuracy can be virtually guaranteed. In a typical application, the ACC algorithm finds image shifts of more than 500 Shack-Hartmann camera sub-images relative to a reference sub -image or cell when performing one wavefront sensing iteration. In the proposed new technique, a pair of test and reference cells is selected from the same frame, preferably from two well-separated locations. The test cell is shifted by an integer number of pixels, say, for example, from m= -5 to 5 along the x-direction by choosing a different area on the same sub-image, and the shifts are estimated using the ACC algorithm. The same is done in the y-direction. If the resulting shift estimate errors are less than a pre-determined threshold (e.g., 0.03 pixel), the image is accepted. Otherwise, it is rejected.

Bloodstain detection and discrimination impacted by spectral shift when using an interference filter-based visible and near-infrared multispectral crime scene imaging system

NASA Astrophysics Data System (ADS)

Yang, Jie; Messinger, David W.; Dube, Roger R.

2018-03-01

Bloodstain detection and discrimination from nonblood substances on various substrates are critical in forensic science as bloodstains are a critical source for confirmatory DNA tests. Conventional bloodstain detection methods often involve time-consuming sample preparation, a chance of harm to investigators, the possibility of destruction of blood samples, and acquisition of too little data at crime scenes either in the field or in the laboratory. An imaging method has the advantages of being nondestructive, noncontact, real-time, and covering a large field-of-view. The abundant spectral information provided by multispectral imaging makes it a potential presumptive bloodstain detection and discrimination method. This article proposes an interference filter (IF) based area scanning three-spectral-band crime scene imaging system used for forensic bloodstain detection and discrimination. The impact of large angle of views on the spectral shift of calibrated IFs is determined, for both detecting and discriminating bloodstains from visually similar substances on multiple substrates. Spectral features in the visible and near-infrared portion employed by the relative band depth method are used. This study shows that 1 ml bloodstain on black felt, gray felt, red felt, white cotton, white polyester, and raw wood can be detected. Bloodstains on the above substrates can be discriminated from cola, coffee, ketchup, orange juice, red wine, and green tea.

Knowledge-Based Object Detection in Laser Scanning Point Clouds

NASA Astrophysics Data System (ADS)

Boochs, F.; Karmacharya, A.; Marbs, A.

2012-07-01

Object identification and object processing in 3D point clouds have always posed challenges in terms of effectiveness and efficiency. In practice, this process is highly dependent on human interpretation of the scene represented by the point cloud data, as well as the set of modeling tools available for use. Such modeling algorithms are data-driven and concentrate on specific features of the objects, being accessible to numerical models. We present an approach that brings the human expert knowledge about the scene, the objects inside, and their representation by the data and the behavior of algorithms to the machine. This "understanding" enables the machine to assist human interpretation of the scene inside the point cloud. Furthermore, it allows the machine to understand possibilities and limitations of algorithms and to take this into account within the processing chain. This not only assists the researchers in defining optimal processing steps, but also provides suggestions when certain changes or new details emerge from the point cloud. Our approach benefits from the advancement in knowledge technologies within the Semantic Web framework. This advancement has provided a strong base for applications based on knowledge management. In the article we will present and describe the knowledge technologies used for our approach such as Web Ontology Language (OWL), used for formulating the knowledge base and the Semantic Web Rule Language (SWRL) with 3D processing and topologic built-ins, aiming to combine geometrical analysis of 3D point clouds, and specialists' knowledge of the scene and algorithmic processing.

Achieving thermography with a thermal security camera using uncooled amorphous silicon microbolometer image sensors

NASA Astrophysics Data System (ADS)

Wang, Yu-Wei; Tesdahl, Curtis; Owens, Jim; Dorn, David

2012-06-01

Advancements in uncooled microbolometer technology over the last several years have opened up many commercial applications which had been previously cost prohibitive. Thermal technology is no longer limited to the military and government market segments. One type of thermal sensor with low NETD which is available in the commercial market segment is the uncooled amorphous silicon (α-Si) microbolometer image sensor. Typical thermal security cameras focus on providing the best image quality by auto tonemaping (contrast enhancing) the image, which provides the best contrast depending on the temperature range of the scene. While this may provide enough information to detect objects and activities, there are further benefits of being able to estimate the actual object temperatures in a scene. This thermographic ability can provide functionality beyond typical security cameras by being able to monitor processes. Example applications of thermography[2] with thermal camera include: monitoring electrical circuits, industrial machinery, building thermal leaks, oil/gas pipelines, power substations, etc...[3][5] This paper discusses the methodology of estimating object temperatures by characterizing/calibrating different components inside a thermal camera utilizing an uncooled amorphous silicon microbolometer image sensor. Plots of system performance across camera operating temperatures will be shown.

High-speed holographic correlation system by a time-division recording method for copyright content management on the internet

NASA Astrophysics Data System (ADS)

Watanabe, Eriko; Ikeda, Kanami; Kodate, Kashiko

2012-10-01

Using a holographic disc memory on which a huge amount of data can be stored, we constructed an ultra-high-speed, all-optical correlation system. In this method, multiplex recording is, however, restricted to "one page" on "one spot." In addition, signal information must be normalized as data of the same size, even if the object data size is smaller. Therefore, this system is difficult to apply to part of the object data scene (i.e., partial scene searching and template matching), while maintaining high accessibility and programmability. In this paper, we develop a holographic correlation system by a time division recording method that increases the number of multiplex recordings on the same spot. Assuming that a four-channel detector is utilized, 15 parallel correlations are achieved by a time-division recording method. Preliminary correlation experiments with the holographic optical disc setup are carried out by high correlation peaks at a rotational speed of 300 rpm. We also describe the combination of an optical correlation system for copyright content management that searches the Internet and detects illegal contents on video sharing websites.

The Performance Analysis Based on SAR Sample Covariance Matrix

PubMed Central

Erten, Esra

2012-01-01

Multi-channel systems appear in several fields of application in science. In the Synthetic Aperture Radar (SAR) context, multi-channel systems may refer to different domains, as multi-polarization, multi-interferometric or multi-temporal data, or even a combination of them. Due to the inherent speckle phenomenon present in SAR images, the statistical description of the data is almost mandatory for its utilization. The complex images acquired over natural media present in general zero-mean circular Gaussian characteristics. In this case, second order statistics as the multi-channel covariance matrix fully describe the data. For practical situations however, the covariance matrix has to be estimated using a limited number of samples, and this sample covariance matrix follow the complex Wishart distribution. In this context, the eigendecomposition of the multi-channel covariance matrix has been shown in different areas of high relevance regarding the physical properties of the imaged scene. Specifically, the maximum eigenvalue of the covariance matrix has been frequently used in different applications as target or change detection, estimation of the dominant scattering mechanism in polarimetric data, moving target indication, etc. In this paper, the statistical behavior of the maximum eigenvalue derived from the eigendecomposition of the sample multi-channel covariance matrix in terms of multi-channel SAR images is simplified for SAR community. Validation is performed against simulated data and examples of estimation and detection problems using the analytical expressions are as well given. PMID:22736976

Optic Flow Dominates Visual Scene Polarity in Causing Adaptive Modification of Locomotor Trajectory

NASA Technical Reports Server (NTRS)

Nomura, Y.; Mulavara, A. P.; Richards, J. T.; Brady, R.; Bloomberg, Jacob J.

2005-01-01

Locomotion and posture are influenced and controlled by vestibular, visual and somatosensory information. Optic flow and scene polarity are two characteristics of a visual scene that have been identified as being critical in how they affect perceived body orientation and self-motion. The goal of this study was to determine the role of optic flow and visual scene polarity on adaptive modification in locomotor trajectory. Two computer-generated virtual reality scenes were shown to subjects during 20 minutes of treadmill walking. One scene was a highly polarized scene while the other was composed of objects displayed in a non-polarized fashion. Both virtual scenes depicted constant rate self-motion equivalent to walking counterclockwise around the perimeter of a room. Subjects performed Stepping Tests blindfolded before and after scene exposure to assess adaptive changes in locomotor trajectory. Subjects showed a significant difference in heading direction, between pre and post adaptation stepping tests, when exposed to either scene during treadmill walking. However, there was no significant difference in the subjects heading direction between the two visual scene polarity conditions. Therefore, it was inferred from these data that optic flow has a greater role than visual polarity in influencing adaptive locomotor function.

Ice Sheet Change Detection by Satellite Image Differencing

NASA Technical Reports Server (NTRS)

Bindschadler, Robert A.; Scambos, Ted A.; Choi, Hyeungu; Haran, Terry M.

2010-01-01

Differencing of digital satellite image pairs highlights subtle changes in near-identical scenes of Earth surfaces. Using the mathematical relationships relevant to photoclinometry, we examine the effectiveness of this method for the study of localized ice sheet surface topography changes using numerical experiments. We then test these results by differencing images of several regions in West Antarctica, including some where changes have previously been identified in altimeter profiles. The technique works well with coregistered images having low noise, high radiometric sensitivity, and near-identical solar illumination geometry. Clouds and frosts detract from resolving surface features. The ETM(plus) sensor on Landsat-7, ALI sensor on EO-1, and MODIS sensor on the Aqua and Terra satellite platforms all have potential for detecting localized topographic changes such as shifting dunes, surface inflation and deflation features associated with sub-glacial lake fill-drain events, or grounding line changes. Availability and frequency of MODIS images favor this sensor for wide application, and using it, we demonstrate both qualitative identification of changes in topography and quantitative mapping of slope and elevation changes.

Texture metric that predicts target detection performance

NASA Astrophysics Data System (ADS)

Culpepper, Joanne B.

2015-12-01

Two texture metrics based on gray level co-occurrence error (GLCE) are used to predict probability of detection and mean search time. The two texture metrics are local clutter metrics and are based on the statistics of GLCE probability distributions. The degree of correlation between various clutter metrics and the target detection performance of the nine military vehicles in complex natural scenes found in the Search_2 dataset are presented. Comparison is also made between four other common clutter metrics found in the literature: root sum of squares, Doyle, statistical variance, and target structure similarity. The experimental results show that the GLCE energy metric is a better predictor of target detection performance when searching for targets in natural scenes than the other clutter metrics studied.

A hybrid approach for text detection in natural scenes

NASA Astrophysics Data System (ADS)

Wang, Runmin; Sang, Nong; Wang, Ruolin; Kuang, Xiaoqin

2013-10-01

In this paper, a hybrid approach is proposed to detect texts in natural scenes. It is performed by the following steps: Firstly, the edge map and the text saliency region are obtained. Secondly, the text candidate regions are detected by connected components (CC) based method and are identified by an off-line trained HOG classifier. And then, the remaining CCs are grouped into text lines with some heuristic strategies to make up for the false negatives. Finally, the text lines are broken into separate words. The performance of the proposed approach is evaluated on the location detection database of ICDAR 2003 robust reading competition. Experimental results demonstrate the validity of our approach and are competitive with other state-of-the-art algorithms.

Initial progress in the recording of crime scene simulations using 3D laser structured light imagery techniques for law enforcement and forensic applications

NASA Astrophysics Data System (ADS)

Altschuler, Bruce R.; Monson, Keith L.

1998-03-01

Representation of crime scenes as virtual reality 3D computer displays promises to become a useful and important tool for law enforcement evaluation and analysis, forensic identification and pathological study and archival presentation during court proceedings. Use of these methods for assessment of evidentiary materials demands complete accuracy of reproduction of the original scene, both in data collection and in its eventual virtual reality representation. The recording of spatially accurate information as soon as possible after first arrival of law enforcement personnel is advantageous for unstable or hazardous crime scenes and reduces the possibility that either inadvertent measurement error or deliberate falsification may occur or be alleged concerning processing of a scene. Detailed measurements and multimedia archiving of critical surface topographical details in a calibrated, uniform, consistent and standardized quantitative 3D coordinate method are needed. These methods would afford professional personnel in initial contact with a crime scene the means for remote, non-contacting, immediate, thorough and unequivocal documentation of the contents of the scene. Measurements of the relative and absolute global positions of object sand victims, and their dispositions within the scene before their relocation and detailed examination, could be made. Resolution must be sufficient to map both small and large objects. Equipment must be able to map regions at varied resolution as collected from different perspectives. Progress is presented in devising methods for collecting and archiving 3D spatial numerical data from crime scenes, sufficient for law enforcement needs, by remote laser structured light and video imagery. Two types of simulation studies were done. One study evaluated the potential of 3D topographic mapping and 3D telepresence using a robotic platform for explosive ordnance disassembly. The second study involved using the laser mapping system on a fixed optical bench with simulated crime scene models of the people and furniture to assess feasibility, requirements and utility of such a system for crime scene documentation and analysis.

On-Board Cryospheric Change Detection By The Autonomous Sciencecraft Experiment

NASA Astrophysics Data System (ADS)

Doggett, T.; Greeley, R.; Castano, R.; Cichy, B.; Chien, S.; Davies, A.; Baker, V.; Dohm, J.; Ip, F.

2004-12-01

The Autonomous Sciencecraft Experiment (ASE) is operating on-board Earth Observing - 1 (EO-1) with the Hyperion hyper-spectral visible/near-IR spectrometer. ASE science activities include autonomous monitoring of cryopsheric changes, triggering the collection of additional data when change is detected and filtering of null data such as no change or cloud cover. This would have application to the study of cryospheres on Earth, Mars and the icy moons of the outer solar system. A cryosphere classification algorithm, in combination with a previously developed cloud algorithm [1] has been tested on-board ten times from March through August 2004. The cloud algorithm correctly screened out three scenes with total cloud cover, while the cryosphere algorithm detected alpine snow cover in the Rocky Mountains, lake thaw near Madison, Wisconsin, and the presence and subsequent break-up of sea ice in the Barrow Strait of the Canadian Arctic. Hyperion has 220 bands ranging from 400 to 2400 nm, with a spatial resolution of 30 m/pixel and a spectral resolution of 10 nm. Limited on-board memory and processing speed imposed the constraint that only partially processed Level 0.5 data with dark image subtraction and gain factors applied, but not full radiometric calibration. In addition, a maximum of 12 bands could be used for any stacked sequence of algorithms run for a scene on-board. The cryosphere algorithm was developed to classify snow, water, ice and land, using six Hyperion bands at 427, 559, 661, 864, 1245 and 1649 nm. Of these, only 427 nm does overlap with the cloud algorithm. The cloud algorithm was developed with Level 1 data, which introduces complications because of the incomplete calibration of SWIR in Level 0.5 data, including a high level of noise in the 1377 nm band used by the cloud algorithm. Development of a more robust cryosphere classifier, including cloud classification specifically adapted to Level 0.5, is in progress for deployment on EO-1 as part of continued ASE operations. [1] Griffin, M.K. et al., Cloud Cover Detection Algorithm For EO-1 Hyperion Imagery, SPIE 17, 2003.

Visual pop-out in barn owls: Human-like behavior in the avian brain.

PubMed

Orlowski, Julius; Beissel, Christian; Rohn, Friederike; Adato, Yair; Wagner, Hermann; Ben-Shahar, Ohad

2015-01-01

Visual pop-out is a phenomenon by which the latency to detect a target in a scene is independent of the number of other elements, the distractors. Pop-out is an effective visual-search guidance that occurs typically when the target is distinct in one feature from the distractors, thus facilitating fast detection of predators or prey. However, apart from studies on primates, pop-out has been examined in few species and demonstrated thus far in rats, archer fish, and pigeons only. To fill this gap, here we study pop-out in barn owls. These birds are a unique model system for such exploration because their lack of eye movements dictates visual behavior dominated by head movements. Head saccades and interspersed fixation periods can therefore be tracked and analyzed with a head-mounted wireless microcamera--the OwlCam. Using this methodology we confronted two owls with scenes containing search arrays of one target among varying numbers (15-63) of similar looking distractors. We tested targets distinct either by orientation (Experiment 1) or luminance contrast (Experiment 2). Search time and the number of saccades until the target was fixated remained largely independent of the number of distractors in both experiments. This suggests that barn owls can exhibit pop-out during visual search, thus expanding the group of species and brain structures that can cope with this fundamental visual behavior. The utility of our automatic analysis method is further discussed for other species and scientific questions.

Using articulated scene models for dynamic 3d scene analysis in vista spaces

NASA Astrophysics Data System (ADS)

Beuter, Niklas; Swadzba, Agnes; Kummert, Franz; Wachsmuth, Sven

2010-09-01

In this paper we describe an efficient but detailed new approach to analyze complex dynamic scenes directly in 3D. The arising information is important for mobile robots to solve tasks in the area of household robotics. In our work a mobile robot builds an articulated scene model by observing the environment in the visual field or rather in the so-called vista space. The articulated scene model consists of essential knowledge about the static background, about autonomously moving entities like humans or robots and finally, in contrast to existing approaches, information about articulated parts. These parts describe movable objects like chairs, doors or other tangible entities, which could be moved by an agent. The combination of the static scene, the self-moving entities and the movable objects in one articulated scene model enhances the calculation of each single part. The reconstruction process for parts of the static scene benefits from removal of the dynamic parts and in turn, the moving parts can be extracted more easily through the knowledge about the background. In our experiments we show, that the system delivers simultaneously an accurate static background model, moving persons and movable objects. This information of the articulated scene model enables a mobile robot to detect and keep track of interaction partners, to navigate safely through the environment and finally, to strengthen the interaction with the user through the knowledge about the 3D articulated objects and 3D scene analysis. [Figure not available: see fulltext.

Scene perception in posterior cortical atrophy: categorization, description and fixation patterns.

PubMed

Shakespeare, Timothy J; Yong, Keir X X; Frost, Chris; Kim, Lois G; Warrington, Elizabeth K; Crutch, Sebastian J

2013-01-01

Partial or complete Balint's syndrome is a core feature of the clinico-radiological syndrome of posterior cortical atrophy (PCA), in which individuals experience a progressive deterioration of cortical vision. Although multi-object arrays are frequently used to detect simultanagnosia in the clinical assessment and diagnosis of PCA, to date there have been no group studies of scene perception in patients with the syndrome. The current study involved three linked experiments conducted in PCA patients and healthy controls. Experiment 1 evaluated the accuracy and latency of complex scene perception relative to individual faces and objects (color and grayscale) using a categorization paradigm. PCA patients were both less accurate (faces < scenes < objects) and slower (scenes < objects < faces) than controls on all categories, with performance strongly associated with their level of basic visual processing impairment; patients also showed a small advantage for color over grayscale stimuli. Experiment 2 involved free description of real world scenes. PCA patients generated fewer features and more misperceptions than controls, though perceptual errors were always consistent with the patient's global understanding of the scene (whether correct or not). Experiment 3 used eye tracking measures to compare patient and control eye movements over initial and subsequent fixations of scenes. Patients' fixation patterns were significantly different to those of young and age-matched controls, with comparable group differences for both initial and subsequent fixations. Overall, these findings describe the variability in everyday scene perception exhibited by individuals with PCA, and indicate the importance of exposure duration in the perception of complex scenes.

The visual light field in real scenes

PubMed Central

Xia, Ling; Pont, Sylvia C.; Heynderickx, Ingrid

2014-01-01

Human observers' ability to infer the light field in empty space is known as the “visual light field.” While most relevant studies were performed using images on computer screens, we investigate the visual light field in a real scene by using a novel experimental setup. A “probe” and a scene were mixed optically using a semitransparent mirror. Twenty participants were asked to judge whether the probe fitted the scene with regard to the illumination intensity, direction, and diffuseness. Both smooth and rough probes were used to test whether observers use the additional cues for the illumination direction and diffuseness provided by the 3D texture over the rough probe. The results confirmed that observers are sensitive to the intensity, direction, and diffuseness of the illumination also in real scenes. For some lighting combinations on scene and probe, the awareness of a mismatch between the probe and scene was found to depend on which lighting condition was on the scene and which on the probe, which we called the “swap effect.” For these cases, the observers judged the fit to be better if the average luminance of the visible parts of the probe was closer to the average luminance of the visible parts of the scene objects. The use of a rough instead of smooth probe was found to significantly improve observers' abilities to detect mismatches in lighting diffuseness and directions. PMID:25926970

Thermal monitoring of hydrothermal activity by permanent infrared automatic stations: Results obtained at Solfatara di Pozzuoli, Campi Flegrei (Italy)

NASA Astrophysics Data System (ADS)

Chiodini, G.; Vilardo, G.; Augusti, V.; Granieri, D.; Caliro, S.; Minopoli, C.; Terranova, C.

2007-12-01

A permanent automatic infrared (IR) station was installed at Solfatara crater, the most active zone of Campi Flegrei caldera. After a positive in situ calibration of the IR camera, we analyze 2175 thermal IR images of the same scene from 2004 to 2007. The scene includes a portion of the steam heated hot soils of Solfatara. The experiment was initiated to detect and quantify temperature changes of the shallow thermal structure of a quiescent volcano such as Solfatara over long periods. Ambient temperature is the main parameter affecting IR temperatures, while air humidity and rain control image quality. A geometric correction of the images was necessary to remove the effects of slow movement of the camera. After a suitable correction the images give a reliable and detailed picture of the temperature changes, over the period October 2004 to January 2007, which suggests that origin of the changes were linked to anthropogenic activity, vegetation growth, and the increase of the flux of hydrothermal fluids in the area of the hottest fumaroles. Two positive temperature anomalies were registered after the occurrence of two seismic swarms which affected the hydrothermal system of Solfatara in October 2005 and October 2006. It is worth noting that these signs were detected in a system characterized by a low level of activity with respect to systems affected by real volcanic crisis where more spectacular results will be expected. Results of the experiment show that this kind of monitoring system can be a suitable tool for volcanic surveillance.

Statistics of high-level scene context.

PubMed

Greene, Michelle R

2013-01-01

CONTEXT IS CRITICAL FOR RECOGNIZING ENVIRONMENTS AND FOR SEARCHING FOR OBJECTS WITHIN THEM: contextual associations have been shown to modulate reaction time and object recognition accuracy, as well as influence the distribution of eye movements and patterns of brain activations. However, we have not yet systematically quantified the relationships between objects and their scene environments. Here I seek to fill this gap by providing descriptive statistics of object-scene relationships. A total of 48, 167 objects were hand-labeled in 3499 scenes using the LabelMe tool (Russell et al., 2008). From these data, I computed a variety of descriptive statistics at three different levels of analysis: the ensemble statistics that describe the density and spatial distribution of unnamed "things" in the scene; the bag of words level where scenes are described by the list of objects contained within them; and the structural level where the spatial distribution and relationships between the objects are measured. The utility of each level of description for scene categorization was assessed through the use of linear classifiers, and the plausibility of each level for modeling human scene categorization is discussed. Of the three levels, ensemble statistics were found to be the most informative (per feature), and also best explained human patterns of categorization errors. Although a bag of words classifier had similar performance to human observers, it had a markedly different pattern of errors. However, certain objects are more useful than others, and ceiling classification performance could be achieved using only the 64 most informative objects. As object location tends not to vary as a function of category, structural information provided little additional information. Additionally, these data provide valuable information on natural scene redundancy that can be exploited for machine vision, and can help the visual cognition community to design experiments guided by statistics rather than intuition.

Scene and human face recognition in the central vision of patients with glaucoma

PubMed Central

Aptel, Florent; Attye, Arnaud; Guyader, Nathalie; Boucart, Muriel; Chiquet, Christophe; Peyrin, Carole

2018-01-01

Primary open-angle glaucoma (POAG) firstly mainly affects peripheral vision. Current behavioral studies support the idea that visual defects of patients with POAG extend into parts of the central visual field classified as normal by static automated perimetry analysis. This is particularly true for visual tasks involving processes of a higher level than mere detection. The purpose of this study was to assess visual abilities of POAG patients in central vision. Patients were assigned to two groups following a visual field examination (Humphrey 24–2 SITA-Standard test). Patients with both peripheral and central defects and patients with peripheral but no central defect, as well as age-matched controls, participated in the experiment. All participants had to perform two visual tasks where low-contrast stimuli were presented in the central 6° of the visual field. A categorization task of scene images and human face images assessed high-level visual recognition abilities. In contrast, a detection task using the same stimuli assessed low-level visual function. The difference in performance between detection and categorization revealed the cost of high-level visual processing. Compared to controls, patients with a central visual defect showed a deficit in both detection and categorization of all low-contrast images. This is consistent with the abnormal retinal sensitivity as assessed by perimetry. However, the deficit was greater for categorization than detection. Patients without a central defect showed similar performances to the controls concerning the detection and categorization of faces. However, while the detection of scene images was well-maintained, these patients showed a deficit in their categorization. This suggests that the simple loss of peripheral vision could be detrimental to scene recognition, even when the information is displayed in central vision. This study revealed subtle defects in the central visual field of POAG patients that cannot be predicted by static automated perimetry assessment using Humphrey 24–2 SITA-Standard test. PMID:29481572

Continuous Change Detection and Classification (CCDC) of Land Cover Using All Available Landsat Data

NASA Astrophysics Data System (ADS)

Zhu, Z.; Woodcock, C. E.

2012-12-01

A new algorithm for Continuous Change Detection and Classification (CCDC) of land cover using all available Landsat data is developed. This new algorithm is capable of detecting many kinds of land cover change as new images are collected and at the same time provide land cover maps for any given time. To better identify land cover change, a two step cloud, cloud shadow, and snow masking algorithm is used for eliminating "noisy" observations. Next, a time series model that has components of seasonality, trend, and break estimates the surface reflectance and temperature. The time series model is updated continuously with newly acquired observations. Due to the high variability in spectral response for different kinds of land cover change, the CCDC algorithm uses a data-driven threshold derived from all seven Landsat bands. When the difference between observed and predicted exceeds the thresholds three consecutive times, a pixel is identified as land cover change. Land cover classification is done after change detection. Coefficients from the time series models and the Root Mean Square Error (RMSE) from model fitting are used as classification inputs for the Random Forest Classifier (RFC). We applied this new algorithm for one Landsat scene (Path 12 Row 31) that includes all of Rhode Island as well as much of Eastern Massachusetts and parts of Connecticut. A total of 532 Landsat images acquired between 1982 and 2011 were processed. During this period, 619,924 pixels were detected to change once (91% of total changed pixels) and 60,199 pixels were detected to change twice (8% of total changed pixels). The most frequent land cover change category is from mixed forest to low density residential which occupies more than 8% of total land cover change pixels.

A spectral image processing algorithm for evaluating the influence of the illuminants on the reconstructed reflectance

NASA Astrophysics Data System (ADS)

Toadere, Florin

2017-12-01

A spectral image processing algorithm that allows the illumination of the scene with different illuminants together with the reconstruction of the scene's reflectance is presented. Color checker spectral image and CIE A (warm light 2700 K), D65 (cold light 6500 K) and Cree TW Series LED T8 (4000 K) are employed for scene illumination. Illuminants used in the simulations have different spectra and, as a result of their illumination, the colors of the scene change. The influence of the illuminants on the reconstruction of the scene's reflectance is estimated. Demonstrative images and reflectance showing the operation of the algorithm are illustrated.

A test of size-scaling and relative-size hypotheses for the moon illusion.

PubMed

Redding, Gordon M

2002-11-01

In two experiments participants reproduced the size of the moon in pictorial scenes under two conditions: when the scene element was normally oriented, producing a depth gradient like a floor, or when the scene element was inverted, producing a depth gradient like a ceiling. Target moons were located near to or far from the scene element. Consistent with size constancy scaling, the illusion reversed when the "floor" of a pictorial scene was inverted to represent a "ceiling." Relative size contrast predicted a reduction or increase in the illusion with no change in direction. The relation between pictorial and natural moon illusions is discussed.

Modeling Of Object- And Scene-Prototypes With Hierarchically Structured Classes

NASA Astrophysics Data System (ADS)

Ren, Z.; Jensch, P.; Ameling, W.

1989-03-01

The success of knowledge-based image analysis methodology and implementation tools depends largely on an appropriately and efficiently built model wherein the domain-specific context information about and the inherent structure of the observed image scene have been encoded. For identifying an object in an application environment a computer vision system needs to know firstly the description of the object to be found in an image or in an image sequence, secondly the corresponding relationships between object descriptions within the image sequence. This paper presents models of image objects scenes by means of hierarchically structured classes. Using the topovisual formalism of graph and higraph, we are currently studying principally the relational aspect and data abstraction of the modeling in order to visualize the structural nature resident in image objects and scenes, and to formalize. their descriptions. The goal is to expose the structure of image scene and the correspondence of image objects in the low level image interpretation. process. The object-based system design approach has been applied to build the model base. We utilize the object-oriented programming language C + + for designing, testing and implementing the abstracted entity classes and the operation structures which have been modeled topovisually. The reference images used for modeling prototypes of objects and scenes are from industrial environments as'well as medical applications.

Parafoveal Target Detectability Reversal Predicted by Local Luminance and Contrast Gain Control

NASA Technical Reports Server (NTRS)

Ahumada, Albert J., Jr.; Beard, Bettina L.; Null, Cynthia H. (Technical Monitor)

1996-01-01

This project is part of a program to develop image discrimination models for the prediction of the detectability of objects in a range of backgrounds. We wanted to see if the models could predict parafoveal object detection as well as they predict detection in foveal vision. We also wanted to make our simplified models more general by local computation of luminance and contrast gain control. A signal image (0.78 x 0.17 deg) was made by subtracting a simulated airport runway scene background image (2.7 deg square) from the same scene containing an obstructing aircraft. Signal visibility contrast thresholds were measured in a fully crossed factorial design with three factors: eccentricity (0 deg or 4 deg), background (uniform or runway scene background), and fixed-pattern white noise contrast (0%, 5%, or 10%). Three experienced observers responded to three repetitions of 60 2IFC trials in each condition and thresholds were estimated by maximum likelihood probit analysis. In the fovea the average detection contrast threshold was 4 dB lower for the runway background than for the uniform background, but in the parafovea, the average threshold was 6 dB higher for the runway background than for the uniform background. This interaction was similar across the different noise levels and for all three observers. A likely reason for the runway background giving a lower threshold in the fovea is the low luminance near the signal in that scene. In our model, the local luminance computation is controlled by a spatial spread parameter. When this parameter and a corresponding parameter for the spatial spread of contrast gain were increased for the parafoveal predictions, the model predicts the interaction of background with eccentricity.

Deep Neural Network for Structural Prediction and Lane Detection in Traffic Scene.

PubMed

Li, Jun; Mei, Xue; Prokhorov, Danil; Tao, Dacheng

2017-03-01

Hierarchical neural networks have been shown to be effective in learning representative image features and recognizing object classes. However, most existing networks combine the low/middle level cues for classification without accounting for any spatial structures. For applications such as understanding a scene, how the visual cues are spatially distributed in an image becomes essential for successful analysis. This paper extends the framework of deep neural networks by accounting for the structural cues in the visual signals. In particular, two kinds of neural networks have been proposed. First, we develop a multitask deep convolutional network, which simultaneously detects the presence of the target and the geometric attributes (location and orientation) of the target with respect to the region of interest. Second, a recurrent neuron layer is adopted for structured visual detection. The recurrent neurons can deal with the spatial distribution of visible cues belonging to an object whose shape or structure is difficult to explicitly define. Both the networks are demonstrated by the practical task of detecting lane boundaries in traffic scenes. The multitask convolutional neural network provides auxiliary geometric information to help the subsequent modeling of the given lane structures. The recurrent neural network automatically detects lane boundaries, including those areas containing no marks, without any explicit prior knowledge or secondary modeling.

Automatic detection of artifacts in converted S3D video

NASA Astrophysics Data System (ADS)

Bokov, Alexander; Vatolin, Dmitriy; Zachesov, Anton; Belous, Alexander; Erofeev, Mikhail

2014-03-01

In this paper we present algorithms for automatically detecting issues specific to converted S3D content. When a depth-image-based rendering approach produces a stereoscopic image, the quality of the result depends on both the depth maps and the warping algorithms. The most common problem with converted S3D video is edge-sharpness mismatch. This artifact may appear owing to depth-map blurriness at semitransparent edges: after warping, the object boundary becomes sharper in one view and blurrier in the other, yielding binocular rivalry. To detect this problem we estimate the disparity map, extract boundaries with noticeable differences, and analyze edge-sharpness correspondence between views. We pay additional attention to cases involving a complex background and large occlusions. Another problem is detection of scenes that lack depth volume: we present algorithms for detecting at scenes and scenes with at foreground objects. To identify these problems we analyze the features of the RGB image as well as uniform areas in the depth map. Testing of our algorithms involved examining 10 Blu-ray 3D releases with converted S3D content, including Clash of the Titans, The Avengers, and The Chronicles of Narnia: The Voyage of the Dawn Treader. The algorithms we present enable improved automatic quality assessment during the production stage.

Mirage: a visible signature evaluation tool

NASA Astrophysics Data System (ADS)

Culpepper, Joanne B.; Meehan, Alaster J.; Shao, Q. T.; Richards, Noel

2017-10-01

This paper presents the Mirage visible signature evaluation tool, designed to provide a visible signature evaluation capability that will appropriately reflect the effect of scene content on the detectability of targets, providing a capability to assess visible signatures in the context of the environment. Mirage is based on a parametric evaluation of input images, assessing the value of a range of image metrics and combining them using the boosted decision tree machine learning method to produce target detectability estimates. It has been developed using experimental data from photosimulation experiments, where human observers search for vehicle targets in a variety of digital images. The images used for tool development are synthetic (computer generated) images, showing vehicles in many different scenes and exhibiting a wide variation in scene content. A preliminary validation has been performed using k-fold cross validation, where 90% of the image data set was used for training and 10% of the image data set was used for testing. The results of the k-fold validation from 200 independent tests show a prediction accuracy between Mirage predictions of detection probability and observed probability of detection of r(262) = 0:63, p < 0:0001 (Pearson correlation) and a MAE = 0:21 (mean absolute error).

Attentional effects on gaze preference for salient loci in traffic scenes.

PubMed

Sakai, Hiroyuki; Shin, Duk; Kohama, Takeshi; Uchiyama, Yuji

2012-01-01

Alerting drivers for self-regulation of attention might decrease crash risks attributable to absent-minded driving. However, no reliable method exists for monitoring driver attention. Therefore, we examined attentional effects on gaze preference for salient loci (GPS) in traffic scenes. In an active viewing (AV) condition requiring endogenous attention for traffic scene comprehension, participants identified appropriate speeds for driving in presented traffic scene images. In a passive viewing (PV) condition requiring no endogenous attention, participants passively viewed traffic scene images. GPS was quantified by the mean saliency value averaged across fixation locations. Results show that GPS was less during AV than during PV. Additionally, gaze dwell time on signboards was shorter for AV than for PV. These results suggest that, in the absence of endogenous attention for traffic scene comprehension, gaze tends to concentrate on irrelevant salient loci in a traffic environment. Therefore, increased GPS can indicate absent-minded driving. The present study demonstrated that, without endogenous attention for traffic scene comprehension, gaze tends to concentrate on irrelevant salient loci in a traffic environment. This result suggests that increased gaze preference for salient loci indicates absent-minded driving, which is otherwise difficult to detect.

3D Traffic Scene Understanding From Movable Platforms.

PubMed

Geiger, Andreas; Lauer, Martin; Wojek, Christian; Stiller, Christoph; Urtasun, Raquel

2014-05-01

In this paper, we present a novel probabilistic generative model for multi-object traffic scene understanding from movable platforms which reasons jointly about the 3D scene layout as well as the location and orientation of objects in the scene. In particular, the scene topology, geometry, and traffic activities are inferred from short video sequences. Inspired by the impressive driving capabilities of humans, our model does not rely on GPS, lidar, or map knowledge. Instead, it takes advantage of a diverse set of visual cues in the form of vehicle tracklets, vanishing points, semantic scene labels, scene flow, and occupancy grids. For each of these cues, we propose likelihood functions that are integrated into a probabilistic generative model. We learn all model parameters from training data using contrastive divergence. Experiments conducted on videos of 113 representative intersections show that our approach successfully infers the correct layout in a variety of very challenging scenarios. To evaluate the importance of each feature cue, experiments using different feature combinations are conducted. Furthermore, we show how by employing context derived from the proposed method we are able to improve over the state-of-the-art in terms of object detection and object orientation estimation in challenging and cluttered urban environments.

Rapid detection of person information in a naturalistic scene.

PubMed

Fletcher-Watson, Sue; Findlay, John M; Leekam, Susan R; Benson, Valerie

2008-01-01

A preferential-looking paradigm was used to investigate how gaze is distributed in naturalistic scenes. Two scenes were presented side by side: one contained a single person (person-present) and one did not (person-absent). Eye movements were recorded, the principal measures being the time spent looking at each region of the scenes, and the latency and location of the first fixation within each trial. We studied gaze patterns during free viewing, and also in a task requiring gender discrimination of the human figure depicted. Results indicated a strong bias towards looking to the person-present scene. This bias was present on the first fixation after image presentation, confirming previous findings of ultra-rapid processing of complex information. Faces attracted disproportionately many fixations, the preference emerging in the first fixation and becoming stronger in the following ones. These biases were exaggerated in the gender-discrimination task. A tendency to look at the object being fixated by the person in the scene was shown to be strongest at a slightly later point in the gaze sequence. We conclude that human bodies and faces are subject to special perceptual processing when presented as part of a naturalistic scene.

Embodied memory allows accurate and stable perception of hidden objects despite orientation change.

PubMed

Pan, Jing Samantha; Bingham, Ned; Bingham, Geoffrey P

2017-07-01

Rotating a scene in a frontoparallel plane (rolling) yields a change in orientation of constituent images. When using only information provided by static images to perceive a scene after orientation change, identification performance typically decreases (Rock & Heimer, 1957). However, rolling generates optic flow information that relates the discrete, static images (before and after the change) and forms an embodied memory that aids recognition. The embodied memory hypothesis predicts that upon detecting a continuous spatial transformation of image structure, or in other words, seeing the continuous rolling process and objects undergoing rolling observers should accurately perceive objects during and after motion. Thus, in this case, orientation change should not affect performance. We tested this hypothesis in three experiments and found that (a) using combined optic flow and image structure, participants identified locations of previously perceived but currently occluded targets with great accuracy and stability (Experiment 1); (b) using combined optic flow and image structure information, participants identified hidden targets equally well with or without 30° orientation changes (Experiment 2); and (c) when the rolling was unseen, identification of hidden targets after orientation change became worse (Experiment 3). Furthermore, when rolling was unseen, although target identification was better when participants were told about the orientation change than when they were not told, performance was still worse than when there was no orientation change. Therefore, combined optic flow and image structure information, not mere knowledge about the rolling, enables accurate and stable perception despite orientation change. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Crime scene units: a look to the future

NASA Astrophysics Data System (ADS)

Baldwin, Hayden B.

1999-02-01

The scientific examination of physical evidence is well recognized as a critical element in conducting successful criminal investigations and prosecutions. The forensic science field is an ever changing discipline. With the arrival of DNA, new processing techniques for latent prints, portable lasers, and electro-static dust print lifters, and training of evidence technicians has become more important than ever. These scientific and technology breakthroughs have increased the possibility of collecting and analyzing physical evidence that was never possible before. The problem arises with the collection of physical evidence from the crime scene not from the analysis of the evidence. The need for specialized units in the processing of all crime scenes is imperative. These specialized units, called crime scene units, should be trained and equipped to handle all forms of crime scenes. The crime scenes units would have the capability to professionally evaluate and collect pertinent physical evidence from the crime scenes.

Visual memory for moving scenes.

PubMed

DeLucia, Patricia R; Maldia, Maria M

2006-02-01

In the present study, memory for picture boundaries was measured with scenes that simulated self-motion along the depth axis. The results indicated that boundary extension (a distortion in memory for picture boundaries) occurred with moving scenes in the same manner as that reported previously for static scenes. Furthermore, motion affected memory for the boundaries but this effect of motion was not consistent with representational momentum of the self (memory being further forward in a motion trajectory than actually shown). We also found that memory for the final position of the depicted self in a moving scene was influenced by properties of the optical expansion pattern. The results are consistent with a conceptual framework in which the mechanisms that underlie boundary extension and representational momentum (a) process different information and (b) both contribute to the integration of successive views of a scene while the scene is changing.

Change detection in Arctic satellite imagery using clustering of sparse approximations (CoSA) over learned feature dictionaries

NASA Astrophysics Data System (ADS)

Moody, Daniela I.; Wilson, Cathy J.; Rowland, Joel C.; Altmann, Garrett L.

2015-06-01

Advanced pattern recognition and computer vision algorithms are of great interest for landscape characterization, change detection, and change monitoring in satellite imagery, in support of global climate change science and modeling. We present results from an ongoing effort to extend neuroscience-inspired models for feature extraction to the environmental sciences, and we demonstrate our work using Worldview-2 multispectral satellite imagery. We use a Hebbian learning rule to derive multispectral, multiresolution dictionaries directly from regional satellite normalized band difference index data. These feature dictionaries are used to build sparse scene representations, from which we automatically generate land cover labels via our CoSA algorithm: Clustering of Sparse Approximations. These data adaptive feature dictionaries use joint spectral and spatial textural characteristics to help separate geologic, vegetative, and hydrologic features. Land cover labels are estimated in example Worldview-2 satellite images of Barrow, Alaska, taken at two different times, and are used to detect and discuss seasonal surface changes. Our results suggest that an approach that learns from both spectral and spatial features is promising for practical pattern recognition problems in high resolution satellite imagery.

Visual Object Recognition with 3D-Aware Features in KITTI Urban Scenes

PubMed Central

Yebes, J. Javier; Bergasa, Luis M.; García-Garrido, Miguel Ángel

2015-01-01

Driver assistance systems and autonomous robotics rely on the deployment of several sensors for environment perception. Compared to LiDAR systems, the inexpensive vision sensors can capture the 3D scene as perceived by a driver in terms of appearance and depth cues. Indeed, providing 3D image understanding capabilities to vehicles is an essential target in order to infer scene semantics in urban environments. One of the challenges that arises from the navigation task in naturalistic urban scenarios is the detection of road participants (e.g., cyclists, pedestrians and vehicles). In this regard, this paper tackles the detection and orientation estimation of cars, pedestrians and cyclists, employing the challenging and naturalistic KITTI images. This work proposes 3D-aware features computed from stereo color images in order to capture the appearance and depth peculiarities of the objects in road scenes. The successful part-based object detector, known as DPM, is extended to learn richer models from the 2.5D data (color and disparity), while also carrying out a detailed analysis of the training pipeline. A large set of experiments evaluate the proposals, and the best performing approach is ranked on the KITTI website. Indeed, this is the first work that reports results with stereo data for the KITTI object challenge, achieving increased detection ratios for the classes car and cyclist compared to a baseline DPM. PMID:25903553

Visual Object Recognition with 3D-Aware Features in KITTI Urban Scenes.

PubMed

Yebes, J Javier; Bergasa, Luis M; García-Garrido, Miguel Ángel

2015-04-20

Driver assistance systems and autonomous robotics rely on the deployment of several sensors for environment perception. Compared to LiDAR systems, the inexpensive vision sensors can capture the 3D scene as perceived by a driver in terms of appearance and depth cues. Indeed, providing 3D image understanding capabilities to vehicles is an essential target in order to infer scene semantics in urban environments. One of the challenges that arises from the navigation task in naturalistic urban scenarios is the detection of road participants (e.g., cyclists, pedestrians and vehicles). In this regard, this paper tackles the detection and orientation estimation of cars, pedestrians and cyclists, employing the challenging and naturalistic KITTI images. This work proposes 3D-aware features computed from stereo color images in order to capture the appearance and depth peculiarities of the objects in road scenes. The successful part-based object detector, known as DPM, is extended to learn richer models from the 2.5D data (color and disparity), while also carrying out a detailed analysis of the training pipeline. A large set of experiments evaluate the proposals, and the best performing approach is ranked on the KITTI website. Indeed, this is the first work that reports results with stereo data for the KITTI object challenge, achieving increased detection ratios for the classes car and cyclist compared to a baseline DPM.

The roles of garment design and scene complexity in the daytime conspicuity of high-visibility safety apparel.

PubMed

Sayer, James R; Buonarosa, Mary Lynn

2008-01-01

This study examines the effects of high-visibility garment design on daytime pedestrian conspicuity in work zones. Factors assessed were garment color, amount of background material, pedestrian arm motion, scene complexity, and driver age. The study was conducted in naturalistic conditions on public roads in real traffic. Drivers drove two passes on a 31-km route and indicated when they detected pedestrians outfitted in the fluorescent garments. The locations of the vehicle and the pedestrian were recorded. Detection distances between fluorescent yellow-green and fluorescent red-orange garments were not significantly different, nor were there any significant two-way interactions involving garment color. Pedestrians were detected at longer distances in lower complexity scenes. Arm motion significantly increased detection distances for pedestrians wearing a Class 2 vest, but had little added benefit on detection distances for pedestrians wearing a Class 2 jacket. Daytime detection distances for pedestrians wearing Class 2 or Class 3 garments are longest when the complexity of the surround is low. The more background information a driver has to search through, the longer it is likely to take the driver to locate a pedestrian--even when wearing a high-visibility garment. These findings will provide information to safety garment manufacturers about characteristics of high-visibility safety garments which make them effective for daytime use.

Moving Object Detection on a Vehicle Mounted Back-Up Camera

PubMed Central

Kim, Dong-Sun; Kwon, Jinsan

2015-01-01

In the detection of moving objects from vision sources one usually assumes that the scene has been captured by stationary cameras. In case of backing up a vehicle, however, the camera mounted on the vehicle moves according to the vehicle’s movement, resulting in ego-motions on the background. This results in mixed motion in the scene, and makes it difficult to distinguish between the target objects and background motions. Without further treatments on the mixed motion, traditional fixed-viewpoint object detection methods will lead to many false-positive detection results. In this paper, we suggest a procedure to be used with the traditional moving object detection methods relaxing the stationary cameras restriction, by introducing additional steps before and after the detection. We also decribe the implementation as a FPGA platform along with the algorithm. The target application of this suggestion is use with a road vehicle’s rear-view camera systems. PMID:26712761

Saliency Detection on Light Field.

PubMed

Li, Nianyi; Ye, Jinwei; Ji, Yu; Ling, Haibin; Yu, Jingyi

2017-08-01

Existing saliency detection approaches use images as inputs and are sensitive to foreground/background similarities, complex background textures, and occlusions. We explore the problem of using light fields as input for saliency detection. Our technique is enabled by the availability of commercial plenoptic cameras that capture the light field of a scene in a single shot. We show that the unique refocusing capability of light fields provides useful focusness, depths, and objectness cues. We further develop a new saliency detection algorithm tailored for light fields. To validate our approach, we acquire a light field database of a range of indoor and outdoor scenes and generate the ground truth saliency map. Experiments show that our saliency detection scheme can robustly handle challenging scenarios such as similar foreground and background, cluttered background, complex occlusions, etc., and achieve high accuracy and robustness.

Detection of gait characteristics for scene registration in video surveillance system.

PubMed

Havasi, László; Szlávik, Zoltán; Szirányi, Tamás

2007-02-01

This paper presents a robust walk-detection algorithm, based on our symmetry approach which can be used to extract gait characteristics from video-image sequences. To obtain a useful descriptor of a walking person, we temporally track the symmetries of a person's legs. Our method is suitable for use in indoor or outdoor surveillance scenes. Determining the leading leg of the walking subject is important, and the presented method can identify this from two successive walk steps (one walk cycle). We tested the accuracy of the presented walk-detection method in a possible application: Image registration methods are presented which are applicable to multicamera systems viewing human subjects in motion.

Modeling the effects of contrast enhancement on target acquisition performance

NASA Astrophysics Data System (ADS)

Du Bosq, Todd W.; Fanning, Jonathan D.

2008-04-01

Contrast enhancement and dynamic range compression are currently being used to improve the performance of infrared imagers by increasing the contrast between the target and the scene content, by better utilizing the available gray levels either globally or locally. This paper assesses the range-performance effects of various contrast enhancement algorithms for target identification with well contrasted vehicles. Human perception experiments were performed to determine field performance using contrast enhancement on the U.S. Army RDECOM CERDEC NVESD standard military eight target set using an un-cooled LWIR camera. The experiments compare the identification performance of observers viewing linearly scaled images and various contrast enhancement processed images. Contrast enhancement is modeled in the US Army thermal target acquisition model (NVThermIP) by changing the scene contrast temperature. The model predicts improved performance based on any improved target contrast, regardless of feature saturation or enhancement. To account for the equivalent blur associated with each contrast enhancement algorithm, an additional effective MTF was calculated and added to the model. The measured results are compared with the predicted performance based on the target task difficulty metric used in NVThermIP.

Continuous video coherence computing model for detecting scene boundaries

NASA Astrophysics Data System (ADS)

Kang, Hang-Bong

2001-07-01

The scene boundary detection is important in the semantic understanding of video data and is usually determined by coherence between shots. To measure the coherence, two approaches have been proposed. One is a discrete approach and the other one is a continuous approach. In this paper, we use the continuous approach and propose some modifications on the causal First-In-First-Out(FIFO) short-term memory-based model. One modification is that we allow dynamic memory size in computing coherence reliably regardless of the size of each shot. Another modification is that some shots can be removed from the memory buffer not by the FIFO rule. These removed shots have no or small foreground objects. Using this model, we detect scene boundaries by computing shot coherence. In computing coherence, we add one new term which is the number of intermediate shots between two comparing shots because the effect of intermediate shots is important in computing shot recall. In addition, we also consider shot activity because this is important to reflect human perception. We experiment our computing model on different genres of videos and have obtained reasonable results.

Constrained sampling experiments reveal principles of detection in natural scenes.

PubMed

Sebastian, Stephen; Abrams, Jared; Geisler, Wilson S

2017-07-11

A fundamental everyday visual task is to detect target objects within a background scene. Using relatively simple stimuli, vision science has identified several major factors that affect detection thresholds, including the luminance of the background, the contrast of the background, the spatial similarity of the background to the target, and uncertainty due to random variations in the properties of the background and in the amplitude of the target. Here we use an experimental approach based on constrained sampling from multidimensional histograms of natural stimuli, together with a theoretical analysis based on signal detection theory, to discover how these factors affect detection in natural scenes. We sorted a large collection of natural image backgrounds into multidimensional histograms, where each bin corresponds to a particular luminance, contrast, and similarity. Detection thresholds were measured for a subset of bins spanning the space, where a natural background was randomly sampled from a bin on each trial. In low-uncertainty conditions, both the background bin and the amplitude of the target were fixed, and, in high-uncertainty conditions, they varied randomly on each trial. We found that thresholds increase approximately linearly along all three dimensions and that detection accuracy is unaffected by background bin and target amplitude uncertainty. The results are predicted from first principles by a normalized matched-template detector, where the dynamic normalizing gain factor follows directly from the statistical properties of the natural backgrounds. The results provide an explanation for classic laws of psychophysics and their underlying neural mechanisms.

Scene perception in posterior cortical atrophy: categorization, description and fixation patterns

PubMed Central

Shakespeare, Timothy J.; Yong, Keir X. X.; Frost, Chris; Kim, Lois G.; Warrington, Elizabeth K.; Crutch, Sebastian J.

2013-01-01

Partial or complete Balint's syndrome is a core feature of the clinico-radiological syndrome of posterior cortical atrophy (PCA), in which individuals experience a progressive deterioration of cortical vision. Although multi-object arrays are frequently used to detect simultanagnosia in the clinical assessment and diagnosis of PCA, to date there have been no group studies of scene perception in patients with the syndrome. The current study involved three linked experiments conducted in PCA patients and healthy controls. Experiment 1 evaluated the accuracy and latency of complex scene perception relative to individual faces and objects (color and grayscale) using a categorization paradigm. PCA patients were both less accurate (faces < scenes < objects) and slower (scenes < objects < faces) than controls on all categories, with performance strongly associated with their level of basic visual processing impairment; patients also showed a small advantage for color over grayscale stimuli. Experiment 2 involved free description of real world scenes. PCA patients generated fewer features and more misperceptions than controls, though perceptual errors were always consistent with the patient's global understanding of the scene (whether correct or not). Experiment 3 used eye tracking measures to compare patient and control eye movements over initial and subsequent fixations of scenes. Patients' fixation patterns were significantly different to those of young and age-matched controls, with comparable group differences for both initial and subsequent fixations. Overall, these findings describe the variability in everyday scene perception exhibited by individuals with PCA, and indicate the importance of exposure duration in the perception of complex scenes. PMID:24106469

Pedestrian detection in video surveillance using fully convolutional YOLO neural network

NASA Astrophysics Data System (ADS)

Molchanov, V. V.; Vishnyakov, B. V.; Vizilter, Y. V.; Vishnyakova, O. V.; Knyaz, V. A.

2017-06-01

More than 80% of video surveillance systems are used for monitoring people. Old human detection algorithms, based on background and foreground modelling, could not even deal with a group of people, to say nothing of a crowd. Recent robust and highly effective pedestrian detection algorithms are a new milestone of video surveillance systems. Based on modern approaches in deep learning, these algorithms produce very discriminative features that can be used for getting robust inference in real visual scenes. They deal with such tasks as distinguishing different persons in a group, overcome problem with sufficient enclosures of human bodies by the foreground, detect various poses of people. In our work we use a new approach which enables to combine detection and classification tasks into one challenge using convolution neural networks. As a start point we choose YOLO CNN, whose authors propose a very efficient way of combining mentioned above tasks by learning a single neural network. This approach showed competitive results with state-of-the-art models such as FAST R-CNN, significantly overcoming them in speed, which allows us to apply it in real time video surveillance and other video monitoring systems. Despite all advantages it suffers from some known drawbacks, related to the fully-connected layers that obstruct applying the CNN to images with different resolution. Also it limits the ability to distinguish small close human figures in groups which is crucial for our tasks since we work with rather low quality images which often include dense small groups of people. In this work we gradually change network architecture to overcome mentioned above problems, train it on a complex pedestrian dataset and finally get the CNN detecting small pedestrians in real scenes.

Top-attack modeling and automatic target detection using synthetic FLIR scenery

NASA Astrophysics Data System (ADS)

Weber, Bruce A.; Penn, Joseph A.

2004-09-01

A series of experiments have been performed to verify the utility of algorithmic tools for the modeling and analysis of cold-target signatures in synthetic, top-attack, FLIR video sequences. The tools include: MuSES/CREATION for the creation of synthetic imagery with targets, an ARL target detection algorithm to detect imbedded synthetic targets in scenes, and an ARL scoring algorithm, using Receiver-Operating-Characteristic (ROC) curve analysis, to evaluate detector performance. Cold-target detection variability was examined as a function of target emissivity, surrounding clutter type, and target placement in non-obscuring clutter locations. Detector metrics were also individually scored so as to characterize the effect of signature/clutter variations. Results show that using these tools, a detailed, physically meaningful, target detection analysis is possible and that scenario specific target detectors may be developed by selective choice and/or weighting of detector metrics. However, developing these tools into a reliable predictive capability will require the extension of these results to the modeling and analysis of a large number of data sets configured for a wide range of target and clutter conditions. Finally, these tools should also be useful for the comparison of competitive detection algorithms by providing well defined, and controllable target detection scenarios, as well as for the training and testing of expert human observers.

Change Detection Based on Persistent Scatterer Interferometry - a New Method of Monitoring Building Changes

NASA Astrophysics Data System (ADS)

Yang, C. H.; Kenduiywo, B. K.; Soergel, U.

2016-06-01

Persistent Scatterer Interferometry (PSI) is a technique to detect a network of extracted persistent scatterer (PS) points which feature temporal phase stability and strong radar signal throughout time-series of SAR images. The small surface deformations on such PS points are estimated. PSI particularly works well in monitoring human settlements because regular substructures of man-made objects give rise to large number of PS points. If such structures and/or substructures substantially alter or even vanish due to big change like construction, their PS points are discarded without additional explorations during standard PSI procedure. Such rejected points are called big change (BC) points. On the other hand, incoherent change detection (ICD) relies on local comparison of multi-temporal images (e.g. image difference, image ratio) to highlight scene modifications of larger size rather than detail level. However, image noise inevitably degrades ICD accuracy. We propose a change detection approach based on PSI to synergize benefits of PSI and ICD. PS points are extracted by PSI procedure. A local change index is introduced to quantify probability of a big change for each point. We propose an automatic thresholding method adopting change index to extract BC points along with a clue of the period they emerge. In the end, PS ad BC points are integrated into a change detection image. Our method is tested at a site located around north of Berlin main station where steady, demolished, and erected building substructures are successfully detected. The results are consistent with ground truth derived from time-series of aerial images provided by Google Earth. In addition, we apply our technique for traffic infrastructure, business district, and sports playground monitoring.

Reduced Change Blindness Suggests Enhanced Attention to Detail in Individuals with Autism

ERIC Educational Resources Information Center

Smith, Hayley; Milne, Elizabeth

2009-01-01

Background: The phenomenon of change blindness illustrates that a limited number of items within the visual scene are attended to at any one time. It has been suggested that individuals with autism focus attention on less contextually relevant aspects of the visual scene, show superior perceptual discrimination and notice details which are often…

An attentional bias for LEGO® people using a change detection task: Are LEGO® people animate?

PubMed

LaPointe, Mitchell R P; Cullen, Rachael; Baltaretu, Bianca; Campos, Melissa; Michalski, Natalie; Sri Satgunarajah, Suja; Cadieux, Michelle L; Pachai, Matthew V; Shore, David I

2016-09-01

Animate objects have been shown to elicit attentional priority in a change detection task. This benefit has been seen for both human and nonhuman animals compared with inanimate objects. One explanation for these results has been based on the importance animate objects have served over the course of our species' history. In the present set of experiments, we present stimuli, which could be perceived as animate, but with which our distant ancestors would have had no experience, and natural selection could have no direct pressure on their prioritization. In the first experiment, we compared LEGO® "people" with LEGO "nonpeople" in a change detection task. In a second experiment, we attempt to control the heterogeneity of the nonanimate objects by using LEGO blocks, matched in size and colour to LEGO people. In the third experiment, we occlude the faces of the LEGO people to control for facial pattern recognition. In the final 2 experiments, we attempt to obscure high-level categorical information processing of the stimuli by inverting and blurring the scenes. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

D Visualization of Mangrove and Aquaculture Conversion in Banate Bay, Iloilo

NASA Astrophysics Data System (ADS)

Domingo, G. A.; Mallillin, M. M.; Perez, A. M. C.; Claridades, A. R. C.; Tamondong, A. M.

2017-10-01

Studies have shown that mangrove forests in the Philippines have been drastically reduced due to conversion to fishponds, salt ponds, reclamation, as well as other forms of industrial development and as of 2011, Iloilo's 95 % mangrove forest was converted to fishponds. In this research, six (6) Landsat images acquired on the years 1973, 1976, 2000, 2006, 2010, and 2016, were classified using Support Vector Machine (SVM) Classification to determine land cover changes, particularly the area change of mangrove and aquaculture from 1976 to 2016. The results of the classification were used as layers for the generation of 3D visualization models using four (4) platforms namely Google Earth, ArcScene, Virtual Terrain Project, and Terragen. A perception survey was conducted among respondents with different levels of expertise in spatial analysis, 3D visualization, as well as in forestry, fisheries, and aquatic resources to assess the usability, effectiveness, and potential of the various platforms used. Change detection showed that largest negative change for mangrove areas happened from 1976 to 2000, with the mangrove area decreasing from 545.374 hectares to 286.935 hectares. Highest increase in fishpond area occurred from 1973 to 1976 rising from 2,930.67 hectares to 3,441.51 hectares. Results of the perception survey showed that ArcScene is preferred for spatial analysis while respondents favored Terragen for 3D visualization and for forestry, fishery and aquatic resources applications.

Real-time maritime scene simulation for ladar sensors

NASA Astrophysics Data System (ADS)

Christie, Chad L.; Gouthas, Efthimios; Swierkowski, Leszek; Williams, Owen M.

2011-06-01

Continuing interest exists in the development of cost-effective synthetic environments for testing Laser Detection and Ranging (ladar) sensors. In this paper we describe a PC-based system for real-time ladar scene simulation of ships and small boats in a dynamic maritime environment. In particular, we describe the techniques employed to generate range imagery accompanied by passive radiance imagery. Our ladar scene generation system is an evolutionary extension of the VIRSuite infrared scene simulation program and includes all previous features such as ocean wave simulation, the physically-realistic representation of boat and ship dynamics, wake generation and simulation of whitecaps, spray, wake trails and foam. A terrain simulation extension is also under development. In this paper we outline the development, capabilities and limitations of the VIRSuite extensions.

Fusing Cubesat and Landsat 8 data for near-daily mapping of leaf area index at 3 m resolution

NASA Astrophysics Data System (ADS)

McCabe, M.; Houborg, R.

2017-12-01

Constellations of small cubesats are emerging as a relatively inexpensive observational resource with the potential to overcome spatio-temporal constraints of traditional single-sensor satellite missions. With more than 130 compact 3U (i.e., 10 x 10 x 30 cm) cubesats currently in orbit, the company "Planet" has realized near-daily image capture in RGB and the near-infrared (NIR) at 3 m resolution for every location on the earth. However cross-sensor inconsistencies can be a limiting factor, which result from relatively low signal-to-noise ratios, varying overpass times, and sensor-specific spectral response functions. In addition, the sensor radiometric information content is more limited compared to conventional satellite systems such as Landsat. In this study, a synergistic machine-learning framework utilizing Planet, Landsat 8, and MODIS data is developed to produce Landsat 8 consistent LAI with a factor of 10 increase in spatial resolution and a daily observing potential, globally. The Cubist machine-learning technique is used to establish scene-specific links between scale-consistent cubesat RGB+NIR imagery and Landsat 8 LAI. The scheme implements a novel LAI target sampling technique for model training purposes, which accounts for changes in cover conditions over the cubesat and Landsat acquisition timespans. Results over an agricultural region in Saudi Arabia highlight the utility of the approach for detecting high frequency (i.e., near-daily) and fine-scale (i.e., 3 m) intra-field dynamics in LAI with demonstrated potential for timely identification of developing crop risks. The framework maximizes the utility of ultra-high resolution cubesat data for agricultural management and resource efficiency optimization at the precision scale.

See It With Your Own Eyes: Markerless Mobile Augmented Reality for Radiation Awareness in the Hybrid Room.

PubMed

Loy Rodas, Nicolas; Barrera, Fernando; Padoy, Nicolas

2017-02-01

We present an approach to provide awareness to the harmful ionizing radiation generated during X-ray-guided minimally invasive procedures. A hand-held screen is used to display directly in the user's view information related to radiation safety in a mobile augmented reality (AR) manner. Instead of using markers, we propose a method to track the observer's viewpoint, which relies on the use of multiple RGB-D sensors and combines equipment detection for tracking initialization with a KinectFusion-like approach for frame-to-frame tracking. Two of the sensors are ceiling-mounted and a third one is attached to the hand-held screen. The ceiling cameras keep an updated model of the room's layout, which is used to exploit context information and improve the relocalization procedure. The system is evaluated on a multicamera dataset generated inside an operating room (OR) and containing ground-truth poses of the AR display. This dataset includes a wide variety of sequences with different scene configurations, occlusions, motion in the scene, and abrupt viewpoint changes. Qualitative results illustrating the different AR visualization modes for radiation awareness provided by the system are also presented. Our approach allows the user to benefit from a large AR visualization area and permits to recover from tracking failure caused by vast motion or changes in the scene just by looking at a piece of equipment. The system enables the user to see the 3-D propagation of radiation, the medical staff's exposure, and/or the doses deposited on the patient's surface as seen through his own eyes.

Serene Scene

NASA Image and Video Library

2012-05-21

Even in a peaceful looking scene such as this one of Saturn and its moon Tethys, NASA Cassini spacecraft reveals clues about how Saturn is ever-changing; scars are seen here of the huge storm that raged through much of 2011.

Limits of Spatial Attention in Three-Dimensional Space and Dual-task Driving Performance

PubMed Central

Andersen, George J.; Ni, Rui; Bian, Zheng; Kang, Julie

2010-01-01

The present study examined the limits of spatial attention while performing two driving relevant tasks that varied in depth. The first task was to maintain a fixed headway distance behind a lead vehicle that varied speed. The second task was to detect a light-change target in an array of lights located above the roadway. In Experiment 1 the light detection task required drivers to encode color and location. The results indicated that reaction time to detect a light-change target increased and accuracy decreased as a function of the horizontal location of the light-change target and as a function of the distance from the driver. In a second experiment the light change task was changed to a singleton search (detect the onset of a yellow light) and the workload of the car following task was systematically varied. The results of Experiment 2 indicated that RT increased as a function of task workload, the 2D position of the light-change target and the distance of the light-change target. A multiple regression analysis indicated that the effect of distance on light detection performance was not due to changes in the projected size of the light target. In Experiment 3 we found that the distance effect in detecting a light change could not be explained by the location of eye fixations. The results demonstrate that when drivers attend to a roadway scene attention is limited in three-dimensional space. These results have important implications for developing tests for assessing crash risk among drivers as well as the design of in vehicle technologies such as head-up displays. PMID:21094336

Moving vehicles segmentation based on Gaussian motion model

NASA Astrophysics Data System (ADS)

Zhang, Wei; Fang, Xiang Z.; Lin, Wei Y.

2005-07-01

Moving objects segmentation is a challenge in computer vision. This paper focuses on the segmentation of moving vehicles in dynamic scene. We analyses the psychology of human vision and present a framework for segmenting moving vehicles in the highway. The proposed framework consists of two parts. Firstly, we propose an adaptive background update method in which the background is updated according to the change of illumination conditions and thus can adapt to the change of illumination sensitively. Secondly, we construct a Gaussian motion model to segment moving vehicles, in which the motion vectors of the moving pixels are modeled as a Gaussian model and an on-line EM algorithm is used to update the model. The Gaussian distribution of the adaptive model is elevated to determine which moving vectors result from moving vehicles and which from other moving objects such as waving trees. Finally, the pixels with motion vector result from the moving vehicles are segmented. Experimental results of several typical scenes show that the proposed model can detect the moving vehicles correctly and is immune from influence of the moving objects caused by the waving trees and the vibration of camera.

Invisible Cirrus Clouds

NASA Technical Reports Server (NTRS)

2002-01-01

The Moderate-resolution Imaging Spectroradiometer's (MODIS') cloud detection capability is so sensitive that it can detect clouds that would be indistinguishable to the human eye. This pair of images highlights MODIS' ability to detect what scientists call 'sub-visible cirrus.' The image on top shows the scene using data collected in the visible part of the electromagnetic spectrum-the part our eyes can see. Clouds are apparent in the center and lower right of the image, while the rest of the image appears to be relatively clear. However, data collected at 1.38um (lower image) show that a thick layer of previously undetected cirrus clouds obscures the entire scene. These kinds of cirrus are called 'sub-visible' because they can't be detected using only visible light. MODIS' 1.38um channel detects electromagnetic radiation in the infrared region of the spectrum. These images were made from data collected on April 4, 2000. Image courtesy Mark Gray, MODIS Atmosphere Team

Text Detection, Tracking and Recognition in Video: A Comprehensive Survey.

PubMed

Yin, Xu-Cheng; Zuo, Ze-Yu; Tian, Shu; Liu, Cheng-Lin

2016-04-14

Intelligent analysis of video data is currently in wide demand because video is a major source of sensory data in our lives. Text is a prominent and direct source of information in video, while recent surveys of text detection and recognition in imagery [1], [2] focus mainly on text extraction from scene images. Here, this paper presents a comprehensive survey of text detection, tracking and recognition in video with three major contributions. First, a generic framework is proposed for video text extraction that uniformly describes detection, tracking, recognition, and their relations and interactions. Second, within this framework, a variety of methods, systems and evaluation protocols of video text extraction are summarized, compared, and analyzed. Existing text tracking techniques, tracking based detection and recognition techniques are specifically highlighted. Third, related applications, prominent challenges, and future directions for video text extraction (especially from scene videos and web videos) are also thoroughly discussed.

Concurrent-scene/alternate-pattern analysis for robust video-based docking systems

NASA Technical Reports Server (NTRS)

Udomkesmalee, Suraphol

1991-01-01

A typical docking target employs a three-point design of retroreflective tape, one at each endpoint of the center-line, and one on the tip of the central post. Scenes, sensed via laser diode illumination, produce pictures with spots corresponding to desired reflection from the retroreflectors and other reflections. Control corrections for each axis of the vehicle can then be properly applied if the desired spots are accurately tracked. However, initial acquisition of these three spots (detection and identification problem) are non-trivial under a severe noise environment. Signal-to-noise enhancement, accomplished by subtracting the non-illuminated scene from the target scene illuminated by laser diodes, can not eliminate every false spot. Hence, minimization of docking failures due to target mistracking would suggest needed inclusion of added processing features pertaining to target locations. In this paper, we present a concurrent processing scheme for a modified docking target scene which could lead to a perfect docking system. Since the non-illuminated target scene is already available, adding another feature to the three-point design by marking two non-reflective lines, one between the two end-points and one from the tip of the central post to the center-line, would allow this line feature to be picked-up only when capturing the background scene (sensor data without laser illumination). Therefore, instead of performing the image subtraction to generate a picture with a high signal-to-noise ratio, a processed line-image based on the robust line detection technique (Hough transform) can be used to fuse with the actively sensed three-point target image to deduce the true locations of the docking target. This dual-channel confirmation scheme is necessary if a fail-safe system is to be realized from both the sensing and processing point-of-views. Detailed algorithms and preliminary results are presented.

Misidentifying a tennis racket as keys: object identification in people with age-related macular degeneration.

PubMed

Thibaut, Miguel; Tran, Thi Ha Chau; Delerue, Céline; Boucart, Muriel

2015-05-01

Previous studies showed that people with age-related macular degeneration (AMD) can categorise a pre-defined target object or scene with high accuracy (above 80%). In these studies participants were asked to detect the target (e.g. an animal) in serial visual presentation. People with AMD must rely on peripheral vision which is more adapted to the low resolution required for detection than for the higher resolution required to identify a specific exemplar. We investigated the ability of people with central vision loss to identify photographs of objects and scenes. Photographs of isolated objects, natural scenes and objects in scenes were centrally displayed for 2 s each. Participants were asked to name the stimuli. We measured accuracy and naming times in 20 patients with AMD, 15 age-matched and 12 young controls. Accuracy was lower (by about 30%) and naming times were longer (by about 300 ms) in people with AMD than in age-matched controls in the three categories of images. Correct identification occurred in 62-66% of the stimuli for patients. More than 20% of the misidentifications resulted from a structural and/or semantic similarity between the object and the name (e.g. spectacles for dog plates or dolphin for shark). Accuracy and naming times did not differ significantly between young and older normally sighted participants indicating that the deficits resulted from pathology rather than to normal ageing. These results show that, in contrast to performance for categorisation of a single pre-defined target, people with central vision loss are impaired at identifying various objects and scenes. The decrease in accuracy and the increase in response times in patients with AMD indicate that peripheral vision might be sufficient for object and scene categorisation but not for precise scene or object identification. © 2015 The Authors Ophthalmic & Physiological Optics © 2015 The College of Optometrists.

Viewing nature scenes positively affects recovery of autonomic function following acute-mental stress.

PubMed

Brown, Daniel K; Barton, Jo L; Gladwell, Valerie F

2013-06-04

A randomized crossover study explored whether viewing different scenes prior to a stressor altered autonomic function during the recovery from the stressor. The two scenes were (a) nature (composed of trees, grass, fields) or (b) built (composed of man-made, urban scenes lacking natural characteristics) environments. Autonomic function was assessed using noninvasive techniques of heart rate variability; in particular, time domain analyses evaluated parasympathetic activity, using root-mean-square of successive differences (RMSSD). During stress, secondary cardiovascular markers (heart rate, systolic and diastolic blood pressure) showed significant increases from baseline which did not differ between the two viewing conditions. Parasympathetic activity, however, was significantly higher in recovery following the stressor in the viewing scenes of nature condition compared to viewing scenes depicting built environments (RMSSD; 50.0 ± 31.3 vs 34.8 ± 14.8 ms). Thus, viewing nature scenes prior to a stressor alters autonomic activity in the recovery period. The secondary aim was to examine autonomic function during viewing of the two scenes. Standard deviation of R-R intervals (SDRR), as change from baseline, during the first 5 min of viewing nature scenes was greater than during built scenes. Overall, this suggests that nature can elicit improvements in the recovery process following a stressor.

Viewing Nature Scenes Positively Affects Recovery of Autonomic Function Following Acute-Mental Stress

PubMed Central

2013-01-01

A randomized crossover study explored whether viewing different scenes prior to a stressor altered autonomic function during the recovery from the stressor. The two scenes were (a) nature (composed of trees, grass, fields) or (b) built (composed of man-made, urban scenes lacking natural characteristics) environments. Autonomic function was assessed using noninvasive techniques of heart rate variability; in particular, time domain analyses evaluated parasympathetic activity, using root-mean-square of successive differences (RMSSD). During stress, secondary cardiovascular markers (heart rate, systolic and diastolic blood pressure) showed significant increases from baseline which did not differ between the two viewing conditions. Parasympathetic activity, however, was significantly higher in recovery following the stressor in the viewing scenes of nature condition compared to viewing scenes depicting built environments (RMSSD; 50.0 ± 31.3 vs 34.8 ± 14.8 ms). Thus, viewing nature scenes prior to a stressor alters autonomic activity in the recovery period. The secondary aim was to examine autonomic function during viewing of the two scenes. Standard deviation of R-R intervals (SDRR), as change from baseline, during the first 5 min of viewing nature scenes was greater than during built scenes. Overall, this suggests that nature can elicit improvements in the recovery process following a stressor. PMID:23590163

Neural Correlates of Fixation Duration during Real-world Scene Viewing: Evidence from Fixation-related (FIRE) fMRI.

PubMed

Henderson, John M; Choi, Wonil

2015-06-01

During active scene perception, our eyes move from one location to another via saccadic eye movements, with the eyes fixating objects and scene elements for varying amounts of time. Much of the variability in fixation duration is accounted for by attentional, perceptual, and cognitive processes associated with scene analysis and comprehension. For this reason, current theories of active scene viewing attempt to account for the influence of attention and cognition on fixation duration. Yet almost nothing is known about the neurocognitive systems associated with variation in fixation duration during scene viewing. We addressed this topic using fixation-related fMRI, which involves coregistering high-resolution eye tracking and magnetic resonance scanning to conduct event-related fMRI analysis based on characteristics of eye movements. We observed that activation in visual and prefrontal executive control areas was positively correlated with fixation duration, whereas activation in ventral areas associated with scene encoding and medial superior frontal and paracentral regions associated with changing action plans was negatively correlated with fixation duration. The results suggest that fixation duration in scene viewing is controlled by cognitive processes associated with real-time scene analysis interacting with motor planning, consistent with current computational models of active vision for scene perception.

Integration of an open interface PC scene generator using COTS DVI converter hardware

NASA Astrophysics Data System (ADS)

Nordland, Todd; Lyles, Patrick; Schultz, Bret

2006-05-01

Commercial-Off-The-Shelf (COTS) personal computer (PC) hardware is increasingly capable of computing high dynamic range (HDR) scenes for military sensor testing at high frame rates. New electro-optical and infrared (EO/IR) scene projectors feature electrical interfaces that can accept the DVI output of these PC systems. However, military Hardware-in-the-loop (HWIL) facilities such as those at the US Army Aviation and Missile Research Development and Engineering Center (AMRDEC) utilize a sizeable inventory of existing projection systems that were designed to use the Silicon Graphics Incorporated (SGI) digital video port (DVP, also known as DVP2 or DD02) interface. To mate the new DVI-based scene generation systems to these legacy projection systems, CG2 Inc., a Quantum3D Company (CG2), has developed a DVI-to-DVP converter called Delta DVP. This device takes progressive scan DVI input, converts it to digital parallel data, and combines and routes color components to derive a 16-bit wide luminance channel replicated on a DVP output interface. The HWIL Functional Area of AMRDEC has developed a suite of modular software to perform deterministic real-time, wave band-specific rendering of sensor scenes, leveraging the features of commodity graphics hardware and open source software. Together, these technologies enable sensor simulation and test facilities to integrate scene generation and projection components with diverse pedigrees.

Case Study of the Failure of two 13.8kV Control & Metering Transformers that caused significant Equipment Damage

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dreifuerst, G R; Chew, D B; Mangonon, H L

The degradation and failure of cast-coil epoxy windings within 13.8kV control power transformers and metering potential transformers has been shown to be dangerous to both equipment and personnel, even though best industrial design practices were followed. Accident scenes will be examined for two events at a U.S. Department of Energy laboratory. Failure modes will be explained and current design practices discussed with changes suggested to prevent a recurrence and to minimize future risk. New maintenance philosophies utilizing partial discharge testing of the transformers as a prediction of end-of-life will be examined.

Comparative Evaluation of Background Subtraction Algorithms in Remote Scene Videos Captured by MWIR Sensors

PubMed Central

Yao, Guangle; Lei, Tao; Zhong, Jiandan; Jiang, Ping; Jia, Wenwu

2017-01-01

Background subtraction (BS) is one of the most commonly encountered tasks in video analysis and tracking systems. It distinguishes the foreground (moving objects) from the video sequences captured by static imaging sensors. Background subtraction in remote scene infrared (IR) video is important and common to lots of fields. This paper provides a Remote Scene IR Dataset captured by our designed medium-wave infrared (MWIR) sensor. Each video sequence in this dataset is identified with specific BS challenges and the pixel-wise ground truth of foreground (FG) for each frame is also provided. A series of experiments were conducted to evaluate BS algorithms on this proposed dataset. The overall performance of BS algorithms and the processor/memory requirements were compared. Proper evaluation metrics or criteria were employed to evaluate the capability of each BS algorithm to handle different kinds of BS challenges represented in this dataset. The results and conclusions in this paper provide valid references to develop new BS algorithm for remote scene IR video sequence, and some of them are not only limited to remote scene or IR video sequence but also generic for background subtraction. The Remote Scene IR dataset and the foreground masks detected by each evaluated BS algorithm are available online: https://github.com/JerryYaoGl/BSEvaluationRemoteSceneIR. PMID:28837112

Multi-temporal thermal analyses for submarine groundwater discharge (SGD) detection over large spatial scales in the Mediterranean

NASA Astrophysics Data System (ADS)

Hennig, Hanna; Mallast, Ulf; Merz, Ralf

2015-04-01

Submarine groundwater discharge (SGD) sites act as important pathways for nutrients and contaminants that deteriorate marine ecosystems. In the Mediterranean it is estimated that 75% of freshwater input is contributed from karst aquifers. Thermal remote sensing can be used for a pre-screening of potential SGD sites in order to optimize field surveys. Although different platforms (ground-, air- and spaceborne) may serve for thermal remote sensing, the most cost-effective are spaceborne platforms (satellites) that likewise cover the largest spatial scale (>100 km per image). Therefore an automatized and objective approach that uses thermal satellite images from Landsat 7 and Landsat 8 was used to localize potential SGD sites on a large spatial scale. The method using descriptive statistic parameter specially range and standard deviation by (Mallast et al., 2014) was adapted to the Mediterranean Sea. Since the method was developed for the Dead Sea were satellite images with cloud cover are rare and no sea level change occurs through tidal cycles it was essential to adapt the method to a region where tidal cycles occur and cloud cover is more frequent . These adaptations include: (1) an automatic and adaptive coastline detection (2) include and process cloud covered scenes to enlarge the data basis, (3) implement tidal data in order to analyze low tide images as SGD is enhanced during these phases and (4) test the applicability for Landsat 8 images that will provide data in the future once Landsat 7 stops working. As previously shown, the range method shows more accurate results compared to the standard deviation. However, the result exclusively depends on two scenes (minimum and maximum) and is largely influenced by outliers. Counteracting on this drawback we developed a new approach. Since it is assumed that sea surface temperature (SST) is stabilized by groundwater at SGD sites, the slope of a bootstrapped linear model fitted to sorted SST per pixel would be less steep than the slope of the surrounding area, resulting in less influence through outliers and an equal weighting of all integrated scenes. Both methods could be used to detect SGD sites in the Mediterranean regardless to the discharge characteristics (diffuse and focused) exceptions are sites with deep emergences. Better results could be shown in bays compared to more exposed sites. Since the range of the SST is mostly influenced by maximum and minimum of the scenes, the slope approach can be seen as a more representative method using all scenes. References: Mallast, U., Gloaguen, R., Friesen, J., Rödiger, T., Geyer, S., Merz, R., Siebert, C., 2014. How to identify groundwater-caused thermal anomalies in lakes based on multi-temporal satellite data in semi-arid regions. Hydrol. Earth Syst. Sci. 18 (7), 2773-2787.

Text Line Detection from Rectangle Traffic Panels of Natural Scene

NASA Astrophysics Data System (ADS)

Wang, Shiyuan; Huang, Linlin; Hu, Jian

2018-01-01

Traffic sign detection and recognition is very important for Intelligent Transportation. Among traffic signs, traffic panel contains rich information. However, due to low resolution and blur in the rectangular traffic panel, it is difficult to extract the character and symbols. In this paper, we propose a coarse-to-fine method to detect the Chinese character on traffic panels from natural scenes. Given a traffic panel Color Quantization is applied to extract candidate regions of Chinese characters. Second, a multi-stage filter based on learning is applied to discard the non-character regions. Third, we aggregate the characters for text lines by Distance Metric Learning method. Experimental results on real traffic images from Baidu Street View demonstrate the effectiveness of the proposed method.

A Region Tracking-Based Vehicle Detection Algorithm in Nighttime Traffic Scenes

PubMed Central

Wang, Jianqiang; Sun, Xiaoyan; Guo, Junbin

2013-01-01

The preceding vehicles detection technique in nighttime traffic scenes is an important part of the advanced driver assistance system (ADAS). This paper proposes a region tracking-based vehicle detection algorithm via the image processing technique. First, the brightness of the taillights during nighttime is used as the typical feature, and we use the existing global detection algorithm to detect and pair the taillights. When the vehicle is detected, a time series analysis model is introduced to predict vehicle positions and the possible region (PR) of the vehicle in the next frame. Then, the vehicle is only detected in the PR. This could reduce the detection time and avoid the false pairing between the bright spots in the PR and the bright spots out of the PR. Additionally, we present a thresholds updating method to make the thresholds adaptive. Finally, experimental studies are provided to demonstrate the application and substantiate the superiority of the proposed algorithm. The results show that the proposed algorithm can simultaneously reduce both the false negative detection rate and the false positive detection rate.

SuBSENSE: a universal change detection method with local adaptive sensitivity.

PubMed

St-Charles, Pierre-Luc; Bilodeau, Guillaume-Alexandre; Bergevin, Robert

2015-01-01

Foreground/background segmentation via change detection in video sequences is often used as a stepping stone in high-level analytics and applications. Despite the wide variety of methods that have been proposed for this problem, none has been able to fully address the complex nature of dynamic scenes in real surveillance tasks. In this paper, we present a universal pixel-level segmentation method that relies on spatiotemporal binary features as well as color information to detect changes. This allows camouflaged foreground objects to be detected more easily while most illumination variations are ignored. Besides, instead of using manually set, frame-wide constants to dictate model sensitivity and adaptation speed, we use pixel-level feedback loops to dynamically adjust our method's internal parameters without user intervention. These adjustments are based on the continuous monitoring of model fidelity and local segmentation noise levels. This new approach enables us to outperform all 32 previously tested state-of-the-art methods on the 2012 and 2014 versions of the ChangeDetection.net dataset in terms of overall F-Measure. The use of local binary image descriptors for pixel-level modeling also facilitates high-speed parallel implementations: our own version, which used no low-level or architecture-specific instruction, reached real-time processing speed on a midlevel desktop CPU. A complete C++ implementation based on OpenCV is available online.

Real Time Intelligent Target Detection and Analysis with Machine Vision

NASA Technical Reports Server (NTRS)

Howard, Ayanna; Padgett, Curtis; Brown, Kenneth

2000-01-01

We present an algorithm for detecting a specified set of targets for an Automatic Target Recognition (ATR) application. ATR involves processing images for detecting, classifying, and tracking targets embedded in a background scene. We address the problem of discriminating between targets and nontarget objects in a scene by evaluating 40x40 image blocks belonging to an image. Each image block is first projected onto a set of templates specifically designed to separate images of targets embedded in a typical background scene from those background images without targets. These filters are found using directed principal component analysis which maximally separates the two groups. The projected images are then clustered into one of n classes based on a minimum distance to a set of n cluster prototypes. These cluster prototypes have previously been identified using a modified clustering algorithm based on prior sensed data. Each projected image pattern is then fed into the associated cluster's trained neural network for classification. A detailed description of our algorithm will be given in this paper. We outline our methodology for designing the templates, describe our modified clustering algorithm, and provide details on the neural network classifiers. Evaluation of the overall algorithm demonstrates that our detection rates approach 96% with a false positive rate of less than 0.03%.

The use of an image registration technique in the urban growth monitoring

NASA Technical Reports Server (NTRS)

Parada, N. D. J. (Principal Investigator); Foresti, C.; Deoliveira, M. D. L. N.; Niero, M.; Parreira, E. M. D. M. F.

1984-01-01

The use of an image registration program in the studies of urban growth is described. This program permits a quick identification of growing areas with the overlap of the same scene in different periods, and with the use of adequate filters. The city of Brasilia, Brazil, is selected for the test area. The dynamics of Brasilia urban growth are analyzed with the overlap of scenes dated June 1973, 1978 and 1983. The results showed the utilization of the image registration technique for the monitoring of dynamic urban growth.

Increasing Student Engagement and Enthusiasm: A Projectile Motion Crime Scene

NASA Astrophysics Data System (ADS)

Bonner, David

2010-05-01

Connecting physics concepts with real-world events allows students to establish a strong conceptual foundation. When such events are particularly interesting to students, it can greatly impact their engagement and enthusiasm in an activity. Activities that involve studying real-world events of high interest can provide students a long-lasting understanding and positive memorable experiences, both of which heighten the learning experiences of those students. One such activity, described in depth in this paper, utilizes a murder mystery and crime scene investigation as an application of basic projectile motion.

Utilization of Local Law Enforcement Aerial Resources in Consequence Management (CM) Response

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wasiolek, Piotr T.; Malchow, Russell L.

2013-03-12

During the past decade the U.S. Department of Homeland Security (DHS) was instrumental in enhancing the nation’s ability to detect and prevent a radiological or nuclear attack in the highest risk cities. Under the DHS Securing the Cities initiative, nearly 13,000 personnel in the New York City region have been trained in preventive radiological and nuclear detection operations, and nearly 8,500 pieces of radiological detection equipment have been funded. As part of the preventive radiological/nuclear detection (PRND) mission, several cities have received funding to purchase commercial aerial radiation detection systems. In 2008, the U.S. Department of Energy, National Nuclear Securitymore » Administration Aerial Measuring System (AMS) program started providing Mobile Aerial Radiological Surveillance (MARS) training to such assets, resulting in over 150 HAZMAT teams’ officers and pilots from 10 law enforcement organizations and fire departments being trained in the aerial radiation detection. From the beginning, the MARS training course covered both the PRND and consequence management (CM) missions. Even if the law enforcement main focus is PRND, their aerial assets can be utilized in the collection of initial radiation data for post-event radiological CM response. Based on over 50 years of AMS operational experience and information collected during MARS training, this presentation will focus on the concepts of CM response using aerial assets as well as utilizing law enforcement/fire department aerial assets in CM. Also discussed will be the need for establishing closer relationships between local jurisdictions’ aerial radiation detection capabilities and state and local radiation control program directors, radiological health department managers, etc. During radiological events these individuals may become primary experts/advisers to Incident Commanders for radiological emergency response, especially in the early stages of a response. The knowledge of the existence, specific capabilities, and use of local aerial radiation detection systems would be critical in planning the response, even before federal assets arrive on the scene. The relationship between local and federal aerial assets and the potential role for the further use of the MARS training and expanded AMS Reachback capabilities in facilitating such interactions will be discussed.« less

Video content parsing based on combined audio and visual information

NASA Astrophysics Data System (ADS)

Zhang, Tong; Kuo, C.-C. Jay

1999-08-01

While previous research on audiovisual data segmentation and indexing primarily focuses on the pictorial part, significant clues contained in the accompanying audio flow are often ignored. A fully functional system for video content parsing can be achieved more successfully through a proper combination of audio and visual information. By investigating the data structure of different video types, we present tools for both audio and visual content analysis and a scheme for video segmentation and annotation in this research. In the proposed system, video data are segmented into audio scenes and visual shots by detecting abrupt changes in audio and visual features, respectively. Then, the audio scene is categorized and indexed as one of the basic audio types while a visual shot is presented by keyframes and associate image features. An index table is then generated automatically for each video clip based on the integration of outputs from audio and visual analysis. It is shown that the proposed system provides satisfying video indexing results.

Information Processing Research.

DTIC Science & Technology

1986-09-01

Kuroe. The 3D MOSAIC Scene Understanding System. In Alan Bundy, Editor, Proceedings of the Eighth International Joint Conference on Artificial ... Artificial Jntelligencel7(1-3):409-460, August, 1981. Given a single picture which is a projection of a three-dimensional scene onto the two...values are detected as outliers by computing the distribution of values over a sliding 80 msec window. During the third pass (based on artificial

Change Detection Algorithms for Surveillance in Visual IoT: A Comparative Study

NASA Astrophysics Data System (ADS)

Akram, Beenish Ayesha; Zafar, Amna; Akbar, Ali Hammad; Wajid, Bilal; Chaudhry, Shafique Ahmad

2018-01-01

The VIoT (Visual Internet of Things) connects virtual information world with real world objects using sensors and pervasive computing. For video surveillance in VIoT, ChD (Change Detection) is a critical component. ChD algorithms identify regions of change in multiple images of the same scene recorded at different time intervals for video surveillance. This paper presents performance comparison of histogram thresholding and classification ChD algorithms using quantitative measures for video surveillance in VIoT based on salient features of datasets. The thresholding algorithms Otsu, Kapur, Rosin and classification methods k-means, EM (Expectation Maximization) were simulated in MATLAB using diverse datasets. For performance evaluation, the quantitative measures used include OSR (Overall Success Rate), YC (Yule's Coefficient) and JC (Jaccard's Coefficient), execution time and memory consumption. Experimental results showed that Kapur's algorithm performed better for both indoor and outdoor environments with illumination changes, shadowing and medium to fast moving objects. However, it reflected degraded performance for small object size with minor changes. Otsu algorithm showed better results for indoor environments with slow to medium changes and nomadic object mobility. k-means showed good results in indoor environment with small object size producing slow change, no shadowing and scarce illumination changes.

The Advanced Linked Extended Reconnaissance & Targeting Technology Demonstration project

NASA Astrophysics Data System (ADS)

Edwards, Mark

2008-04-01

The Advanced Linked Extended Reconnaissance & Targeting (ALERT) Technology Demonstration (TD) project is addressing many operational needs of the future Canadian Army's Surveillance and Reconnaissance forces. Using the surveillance system of the Coyote reconnaissance vehicle as an experimental platform, the ALERT TD project aims to significantly enhance situational awareness by fusing multi-sensor and tactical data, developing automated processes, and integrating beyond line-of-sight sensing. The project is exploiting important advances made in computer processing capability, displays technology, digital communications, and sensor technology since the design of the original surveillance system. As the major research area within the project, concepts are discussed for displaying and fusing multi-sensor and tactical data within an Enhanced Operator Control Station (EOCS). The sensor data can originate from the Coyote's own visible-band and IR cameras, laser rangefinder, and ground-surveillance radar, as well as from beyond line-of-sight systems such as mini-UAVs and unattended ground sensors. Video-rate image processing has been developed to assist the operator to detect poorly visible targets. As a second major area of research, automatic target cueing capabilities have been added to the system. These include scene change detection, automatic target detection and aided target recognition algorithms processing both IR and visible-band images to draw the operator's attention to possible targets. The merits of incorporating scene change detection algorithms are also discussed. In the area of multi-sensor data fusion, up to Joint Defence Labs level 2 has been demonstrated. The human factors engineering aspects of the user interface in this complex environment are presented, drawing upon multiple user group sessions with military surveillance system operators. The paper concludes with Lessons Learned from the project. The ALERT system has been used in a number of C4ISR field trials, most recently at Exercise Empire Challenge in China Lake CA, and at Trial Quest in Norway. Those exercises provided further opportunities to investigate operator interactions. The paper concludes with recommendations for future work in operator interface design.

A dual-waveband dynamic IR scene projector based on DMD

NASA Astrophysics Data System (ADS)

Hu, Yu; Zheng, Ya-wei; Gao, Jiao-bo; Sun, Ke-feng; Li, Jun-na; Zhang, Lei; Zhang, Fang

2016-10-01

Infrared scene simulation system can simulate multifold objects and backgrounds to perform dynamic test and evaluate EO detecting system in the hardware in-the-loop test. The basic structure of a dual-waveband dynamic IR scene projector was introduced in the paper. The system's core device is an IR Digital Micro-mirror Device (DMD) and the radiant source is a mini-type high temperature IR plane black-body. An IR collimation optical system which transmission range includes 3-5μm and 8-12μm is designed as the projection optical system. Scene simulation software was developed with Visual C++ and Vega soft tools and a software flow chart was presented. The parameters and testing results of the system were given, and this system was applied with satisfying performance in an IR imaging simulation testing.

Terminal restriction fragment length polymorphism profiling of bacterial flora derived from single human hair shafts can discriminate individuals.

PubMed

Nishi, Eiji; Watanabe, Kota; Tashiro, Yukihiro; Sakai, Kenji

2017-03-01

Human hairs are the trace evidence most commonly encountered at many crime scenes. However, they have not been effectively utilized for actual criminal investigations because of the low accuracy of their morphological inspection, low detection rate of short tandem repeat (STR) typing, and the problem of heteroplasmy in mitochondrial DNA analysis. Here, we examined the possibility of individual discrimination by comparing profiles of bacterial flora on hair. We carried out the profiling of terminal restriction fragment length polymorphisms (T-RFLP) of the amplified bacterial 16S ribosomal RNA (rRNA) gene from hair samples. Compared with existing STR typing methods that use hair roots, this method using hair shafts allowed the detection of stable bacterial DNA. We successfully obtained the T-RFLP profile from single hair shafts of all volunteers tested. The profiles were specific to each individual, and multiple profiles obtained from the individual him/herself showed higher similarity than those from different individuals. These individual-specific profiles were stably obtained from samples from most volunteers, when collected again after 6months. Storage of the collected hair samples at -30°C was effective for obtaining reproducible T-RF profiles. When unidentified hair samples collected in the laboratory were compared with a pre-constructed database, 17 of 22 hairs were assigned to a small group of people, including the corresponding individuals. These results show that T-RFLP analysis of bacterial flora on a hair shaft found at a crime scene could provide useful information for narrowing down a suspect. Copyright © 2017 Elsevier B.V. All rights reserved.

Neural Mechanisms of Context Effects on Face Recognition: Automatic Binding and Context Shift Decrements

PubMed Central

Hayes, Scott M.; Baena, Elsa; Truong, Trong-Kha; Cabeza, Roberto

2011-01-01

Although people do not normally try to remember associations between faces and physical contexts, these associations are established automatically, as indicated by the difficulty of recognizing familiar faces in different contexts (“butcher-on-the-bus” phenomenon). The present functional MRI (fMRI) study investigated the automatic binding of faces and scenes. In the Face-Face (F-F) condition, faces were presented alone during both encoding and retrieval, whereas in the Face/Scene-Face (FS-F) condition, they were presented overlaid on scenes during encoding but alone during retrieval (context change). Although participants were instructed to focus only on the faces during both encoding and retrieval, recognition performance was worse in the FS-F than the F-F condition (“context shift decrement”—CSD), confirming automatic face-scene binding during encoding. This binding was mediated by the hippocampus as indicated by greater subsequent memory effects (remembered > forgotten) in this region for the FS-F than the F-F condition. Scene memory was mediated by the right parahippocampal cortex, which was reactivated during successful retrieval when the faces were associated with a scene during encoding (FS-F condition). Analyses using the CSD as a regressor yielded a clear hemispheric asymmetry in medial temporal lobe activity during encoding: left hippocampal and parahippocampal activity was associated with a smaller CSD, indicating more flexible memory representations immune to context changes, whereas right hippocampal/rhinal activity was associated with a larger CSD, indicating less flexible representations sensitive to context change. Taken together, the results clarify the neural mechanisms of context effects on face recognition. PMID:19925208

The effect of background and illumination on color identification of real, 3D objects.

PubMed

Allred, Sarah R; Olkkonen, Maria

2013-01-01

For the surface reflectance of an object to be a useful cue to object identity, judgments of its color should remain stable across changes in the object's environment. In 2D scenes, there is general consensus that color judgments are much more stable across illumination changes than background changes. Here we investigate whether these findings generalize to real 3D objects. Observers made color matches to cubes as we independently varied both the illumination impinging on the cube and the 3D background of the cube. As in 2D scenes, we found relatively high but imperfect stability of color judgments under an illuminant shift. In contrast to 2D scenes, we found that background had little effect on average color judgments. In addition, variability of color judgments was increased by an illuminant shift and decreased by embedding the cube within a background. Taken together, these results suggest that in real 3D scenes with ample cues to object segregation, the addition of a background may improve stability of color identification.

Robust Feature Matching in Terrestrial Image Sequences

NASA Astrophysics Data System (ADS)

Abbas, A.; Ghuffar, S.

2018-04-01

From the last decade, the feature detection, description and matching techniques are most commonly exploited in various photogrammetric and computer vision applications, which includes: 3D reconstruction of scenes, image stitching for panoramic creation, image classification, or object recognition etc. However, in terrestrial imagery of urban scenes contains various issues, which include duplicate and identical structures (i.e. repeated windows and doors) that cause the problem in feature matching phase and ultimately lead to failure of results specially in case of camera pose and scene structure estimation. In this paper, we will address the issue related to ambiguous feature matching in urban environment due to repeating patterns.

Robust automatic line scratch detection in films.

PubMed

Newson, Alasdair; Almansa, Andrés; Gousseau, Yann; Pérez, Patrick

2014-03-01

Line scratch detection in old films is a particularly challenging problem due to the variable spatiotemporal characteristics of this defect. Some of the main problems include sensitivity to noise and texture, and false detections due to thin vertical structures belonging to the scene. We propose a robust and automatic algorithm for frame-by-frame line scratch detection in old films, as well as a temporal algorithm for the filtering of false detections. In the frame-by-frame algorithm, we relax some of the hypotheses used in previous algorithms in order to detect a wider variety of scratches. This step's robustness and lack of external parameters is ensured by the combined use of an a contrario methodology and local statistical estimation. In this manner, over-detection in textured or cluttered areas is greatly reduced. The temporal filtering algorithm eliminates false detections due to thin vertical structures by exploiting the coherence of their motion with that of the underlying scene. Experiments demonstrate the ability of the resulting detection procedure to deal with difficult situations, in particular in the presence of noise, texture, and slanted or partial scratches. Comparisons show significant advantages over previous work.

Statistics of high-level scene context

PubMed Central

Greene, Michelle R.

2013-01-01

Context is critical for recognizing environments and for searching for objects within them: contextual associations have been shown to modulate reaction time and object recognition accuracy, as well as influence the distribution of eye movements and patterns of brain activations. However, we have not yet systematically quantified the relationships between objects and their scene environments. Here I seek to fill this gap by providing descriptive statistics of object-scene relationships. A total of 48, 167 objects were hand-labeled in 3499 scenes using the LabelMe tool (Russell et al., 2008). From these data, I computed a variety of descriptive statistics at three different levels of analysis: the ensemble statistics that describe the density and spatial distribution of unnamed “things” in the scene; the bag of words level where scenes are described by the list of objects contained within them; and the structural level where the spatial distribution and relationships between the objects are measured. The utility of each level of description for scene categorization was assessed through the use of linear classifiers, and the plausibility of each level for modeling human scene categorization is discussed. Of the three levels, ensemble statistics were found to be the most informative (per feature), and also best explained human patterns of categorization errors. Although a bag of words classifier had similar performance to human observers, it had a markedly different pattern of errors. However, certain objects are more useful than others, and ceiling classification performance could be achieved using only the 64 most informative objects. As object location tends not to vary as a function of category, structural information provided little additional information. Additionally, these data provide valuable information on natural scene redundancy that can be exploited for machine vision, and can help the visual cognition community to design experiments guided by statistics rather than intuition. PMID:24194723

Efficient summary statistical representation when change localization fails.

PubMed

Haberman, Jason; Whitney, David

2011-10-01

People are sensitive to the summary statistics of the visual world (e.g., average orientation/speed/facial expression). We readily derive this information from complex scenes, often without explicit awareness. Given the fundamental and ubiquitous nature of summary statistical representation, we tested whether this kind of information is subject to the attentional constraints imposed by change blindness. We show that information regarding the summary statistics of a scene is available despite limited conscious access. In a novel experiment, we found that while observers can suffer from change blindness (i.e., not localize where change occurred between two views of the same scene), observers could nevertheless accurately report changes in the summary statistics (or "gist") about the very same scene. In the experiment, observers saw two successively presented sets of 16 faces that varied in expression. Four of the faces in the first set changed from one emotional extreme (e.g., happy) to another (e.g., sad) in the second set. Observers performed poorly when asked to locate any of the faces that changed (change blindness). However, when asked about the ensemble (which set was happier, on average), observer performance remained high. Observers were sensitive to the average expression even when they failed to localize any specific object change. That is, even when observers could not locate the very faces driving the change in average expression between the two sets, they nonetheless derived a precise ensemble representation. Thus, the visual system may be optimized to process summary statistics in an efficient manner, allowing it to operate despite minimal conscious access to the information presented.

Utilizing ERTS-1 imagery for tectonic analysis through study of the Bighorn Mountains region

NASA Technical Reports Server (NTRS)

Hoppin, R. A. (Principal Investigator)

1973-01-01

The author has identified the following significant results. Comparisons of imagery of three seasons, late summer-fall, winter, and spring indicate that for this region fall imagery is the best for overall geologic analysis. Winter scenes with light to moderate snow cover provide excellent topographic detail owing to snow enhancement, lower sun angle, and clarity of the atmosphere. Spring imagery has considerable reduction of tonal contrast owing to the low reflecting heavy green grass cover which subdues lithologic effects; heavy snow cover in the uplands masks topography. Mapping of geologic formations is impractical in most cases. Separation into tonal units can provide some general clues on structure. A given tonal unit can include parts of several geologic formations and different stratigraphic units can have the same tonal signature. Drainage patterns and anomalies provide the most consistent clues for detecting folds, monoclines, and homoclines. Vegetation only locally reflects lithology and structure. False color infrared 9 x 9 transparencies are the most valuable single imagery. Where these can be supplemented by U-2 color infrared for more detailed work, a tremendous amount of information is available. Adequately field checking such a large area just in one scene is the major logistic problem even in a fairly well known region.

A Validation of Remotely Sensed Fires Using Ground Reports

NASA Astrophysics Data System (ADS)

Ruminski, M. G.; Hanna, J.

2007-12-01

A satellite based analysis of fire detections and smoke emissions for North America is produced daily by NOAA/NESDIS. The analysis incorporates data from the MODIS (Terra and Aqua) and AVHRR (NOAA-15/16/17) polar orbiting instruments and GOES East and West geostationary spacecraft with nominal resolutions of 1km and 4 km for the polar and geostationary platforms respectively. Automated fire detection algorithms are utilized for each of the sensors. Analysts perform a quality control procedure on the automated detects by deleting points that are deemed to be false detects and adding points that the algorithms did not detect. A limited validation of the final quality controlled product was performed using high resolution (30 m) ASTER data in the summer of 2006. Some limitations in using ASTER data are that each scene is only approximately 3600 square km, the data acquisition time is relatively constant at around 1030 local solar time and ASTER is another remotely sensed data source. This study expands on the ASTER validation by using ground reports of prescribed burns in Montana and Idaho for 2003 and 2004. It provides a non-remote sensing data source for comparison. While the ground data do not have the limitations noted above for ASTER there are still limitations. For example, even though the data set covers a much larger area (nearly 600,000 square km) than even several ASTER scenes, it still represents a single region of North America. And while the ground data are not restricted to a narrow time window, only a date is provided with each report, limiting the ability to make detailed conclusions about the detection capabilities for specific instruments, especially for the less temporally frequent polar orbiting MODIS and AVHRR sensors. Comparison of the ground data reports to the quality controlled fire analysis revealed a low rate of overall detection of 23.00% over the entire study period. Examination of the daily detection rates revealed a wide variation, with some days resulting in as little as 5 detects out of 107 reported fires while other days had as many as 84 detections out of 160 reports. Inspection of the satellite imagery from the days with very low detection rates revealed that extensive cloud cover prohibited satellite fire detection. On days when cloud cover was at a minimum, detection rates were substantially higher. An estimate of the fire size was also provided with the ground data set. Statistics will be presented for days with minimal cloud cover which will indicate the probability of detection for fires of various sizes.

A bottom-up model of spatial attention predicts human error patterns in rapid scene recognition.

PubMed

Einhäuser, Wolfgang; Mundhenk, T Nathan; Baldi, Pierre; Koch, Christof; Itti, Laurent

2007-07-20

Humans demonstrate a peculiar ability to detect complex targets in rapidly presented natural scenes. Recent studies suggest that (nearly) no focal attention is required for overall performance in such tasks. Little is known, however, of how detection performance varies from trial to trial and which stages in the processing hierarchy limit performance: bottom-up visual processing (attentional selection and/or recognition) or top-down factors (e.g., decision-making, memory, or alertness fluctuations)? To investigate the relative contribution of these factors, eight human observers performed an animal detection task in natural scenes presented at 20 Hz. Trial-by-trial performance was highly consistent across observers, far exceeding the prediction of independent errors. This consistency demonstrates that performance is not primarily limited by idiosyncratic factors but by visual processing. Two statistical stimulus properties, contrast variation in the target image and the information-theoretical measure of "surprise" in adjacent images, predict performance on a trial-by-trial basis. These measures are tightly related to spatial attention, demonstrating that spatial attention and rapid target detection share common mechanisms. To isolate the causal contribution of the surprise measure, eight additional observers performed the animal detection task in sequences that were reordered versions of those all subjects had correctly recognized in the first experiment. Reordering increased surprise before and/or after the target while keeping the target and distractors themselves unchanged. Surprise enhancement impaired target detection in all observers. Consequently, and contrary to several previously published findings, our results demonstrate that attentional limitations, rather than target recognition alone, affect the detection of targets in rapidly presented visual sequences.

Layout Slam with Model Based Loop Closure for 3d Indoor Corridor Reconstruction

NASA Astrophysics Data System (ADS)

Baligh Jahromi, A.; Sohn, G.; Jung, J.; Shahbazi, M.; Kang, J.

2018-05-01

In this paper, we extend a recently proposed visual Simultaneous Localization and Mapping (SLAM) techniques, known as Layout SLAM, to make it robust against error accumulations, abrupt changes of camera orientation and miss-association of newly visited parts of the scene to the previously visited landmarks. To do so, we present a novel technique of loop closing based on layout model matching; i.e., both model information (topology and geometry of reconstructed models) and image information (photometric features) are used to address a loop-closure detection. The advantages of using the layout-related information in the proposed loop-closing technique are twofold. First, it imposes a metric constraint on the global map consistency and, thus, adjusts the mapping scale drifts. Second, it can reduce matching ambiguity in the context of indoor corridors, where the scene is homogenously textured and extracting sufficient amount of distinguishable point features is a challenging task. To test the impact of the proposed technique on the performance of Layout SLAM, we have performed the experiments on wide-angle videos captured by a handheld camera. This dataset was collected from the indoor corridors of a building at York University. The obtained results demonstrate that the proposed method successfully detects the instances of loops while producing very limited trajectory errors.

Utilizing an Artificial Outcrop to Scaffold Learning Between Laboratory and Field Experiences in a College-Level Introductory Geology Course

NASA Astrophysics Data System (ADS)

Wilson, Meredith

Geologic field trips are among the most beneficial learning experiences for students as they engage the topic of geology, but they are also difficult environments to maximize learning. This action research study explored one facet of the problems associated with teaching geology in the field by attempting to improve the transition of undergraduate students from a traditional laboratory setting to an authentic field environment. Utilizing an artificial outcrop, called the GeoScene, during an introductory college-level non-majors geology course, the transition was studied. The GeoScene was utilized in this study as an intermediary between laboratory and authentic field based experiences, allowing students to apply traditional laboratory learning in an outdoor environment. The GeoScene represented a faux field environment; outside, more complex and tangible than a laboratory, but also simplified geologically and located safely within the confines of an educational setting. This exploratory study employed a mixed-methods action research design. The action research design allowed for systematic inquiry by the teacher/researcher into how the students learned. The mixed-methods approach garnered several types of qualitative and quantitative data to explore phenomena and support conclusions. Several types of data were collected and analyzed, including: visual recordings of the intervention, interviews, analytic memos, student reflections, field practical exams, and a pre/post knowledge and skills survey, to determine whether the intervention affected student comprehension and interpretation of geologic phenomena in an authentic field environment, and if so, how. Students enrolled in two different sections of the same laboratory course, sharing a common lecture, participated in laboratory exercises implementing experiential learning and constructivist pedagogies that focused on learning the basic geological skills necessary for work in a field environment. These laboratory activities were followed by an approximate 15 minute intervention at the GeoScene for a treatment group of students (n=13) to attempt to mitigate potential barriers, such as: self-efficacy, novelty space, and spatial skills, which hinder student performance in an authentic field environment. Comparisons were made to a control group (n=12), who did not participate in GeoScene activities, but completed additional exercises and applications in the laboratory setting. Qualitative data sources suggested that the GeoScene treatment was a positive addition to the laboratory studies and improved the student transition to the field environment by: (1) reducing anxiety and decreasing heightened stimulus associated with the novelty of the authentic field environment, (2) allowing a physical transition between the laboratory and field that shifted concepts learned in the lab to the field environment, and (3) improving critical analysis of geologic phenomena. This was corroborated by the quantitative data that suggested the treatment group may have outperformed the control group in geology content related skills taught in the laboratory, and supported by the GeoScene, while in an authentic field environment (p≤0.01, delta=0.507).

Cross-cultural differences in item and background memory: examining the influence of emotional intensity and scene congruency.

PubMed

Mickley Steinmetz, Katherine R; Sturkie, Charlee M; Rochester, Nina M; Liu, Xiaodong; Gutchess, Angela H

2018-07-01

After viewing a scene, individuals differ in what they prioritise and remember. Culture may be one factor that influences scene memory, as Westerners have been shown to be more item-focused than Easterners (see Masuda, T., & Nisbett, R. E. (2001). Attending holistically versus analytically: Comparing the context sensitivity of Japanese and Americans. Journal of Personality and Social Psychology, 81, 922-934). However, cultures may differ in their sensitivity to scene incongruences and emotion processing, which may account for cross-cultural differences in scene memory. The current study uses hierarchical linear modeling (HLM) to examine scene memory while controlling for scene congruency and the perceived emotional intensity of the images. American and East Asian participants encoded pictures that included a positive, negative, or neutral item placed on a neutral background. After a 20-min delay, participants were shown the item and background separately along with similar and new items and backgrounds to assess memory specificity. Results indicated that even when congruency and emotional intensity were controlled, there was evidence that Americans had better item memory than East Asians. Incongruent scenes were better remembered than congruent scenes. However, this effect did not differ by culture. This suggests that Americans' item focus may result in memory changes that are robust despite variations in scene congruency and perceived emotion.

Efficient structure from motion on large scenes using UAV with position and pose information

NASA Astrophysics Data System (ADS)

Teng, Xichao; Yu, Qifeng; Shang, Yang; Luo, Jing; Wang, Gang

2018-04-01

In this paper, we exploit prior information from global positioning systems and inertial measurement units to speed up the process of large scene reconstruction from images acquired by Unmanned Aerial Vehicles. We utilize weak pose information and intrinsic parameter to obtain the projection matrix for each view. As compared to unmanned aerial vehicles' flight altitude, topographic relief can usually be ignored, we assume that the scene is flat and use weak perspective camera to get projective transformations between two views. Furthermore, we propose an overlap criterion and select potentially matching view pairs between projective transformed views. A robust global structure from motion method is used for image based reconstruction. Our real world experiments show that the approach is accurate, scalable and computationally efficient. Moreover, projective transformations between views can also be used to eliminate false matching.

The Identification and Modeling of Visual Cue Usage in Manual Control Task Experiments

NASA Technical Reports Server (NTRS)

Sweet, Barbara Townsend; Trejo, Leonard J. (Technical Monitor)

1999-01-01

Many fields of endeavor require humans to conduct manual control tasks while viewing a perspective scene. Manual control refers to tasks in which continuous, or nearly continuous, control adjustments are required. Examples include flying an aircraft, driving a car, and riding a bicycle. Perspective scenes can arise through natural viewing of the world, simulation of a scene (as in flight simulators), or through imaging devices (such as the cameras on an unmanned aerospace vehicle). Designers frequently have some degree of control over the content and characteristics of a perspective scene; airport designers can choose runway markings, vehicle designers can influence the size and shape of windows, as well as the location of the pilot, and simulator database designers can choose scene complexity and content. Little theoretical framework exists to help designers determine the answers to questions related to perspective scene content. An empirical approach is most commonly used to determine optimum perspective scene configurations. The goal of the research effort described in this dissertation has been to provide a tool for modeling the characteristics of human operators conducting manual control tasks with perspective-scene viewing. This is done for the purpose of providing an algorithmic, as opposed to empirical, method for analyzing the effects of changing perspective scene content for closed-loop manual control tasks.

An Improved Text Localization Method for Natural Scene Images

NASA Astrophysics Data System (ADS)

Jiang, Mengdi; Cheng, Jianghua; Chen, Minghui; Ku, Xishu

2018-01-01

In order to extract text information effectively from natural scene image with complex background, multi-orientation perspective and multilingual languages, we present a new method based on the improved Stroke Feature Transform (SWT). Firstly, The Maximally Stable Extremal Region (MSER) method is used to detect text candidate regions. Secondly, the SWT algorithm is used in the candidate regions, which can improve the edge detection compared with tradition SWT method. Finally, the Frequency-tuned (FT) visual saliency is introduced to remove non-text candidate regions. The experiment results show that, the method can achieve good robustness for complex background with multi-orientation perspective, various characters and font sizes.

Interactive object modelling based on piecewise planar surface patches.

PubMed

Prankl, Johann; Zillich, Michael; Vincze, Markus

2013-06-01

Detecting elements such as planes in 3D is essential to describe objects for applications such as robotics and augmented reality. While plane estimation is well studied, table-top scenes exhibit a large number of planes and methods often lock onto a dominant plane or do not estimate 3D object structure but only homographies of individual planes. In this paper we introduce MDL to the problem of incrementally detecting multiple planar patches in a scene using tracked interest points in image sequences. Planar patches are reconstructed and stored in a keyframe-based graph structure. In case different motions occur, separate object hypotheses are modelled from currently visible patches and patches seen in previous frames. We evaluate our approach on a standard data set published by the Visual Geometry Group at the University of Oxford [24] and on our own data set containing table-top scenes. Results indicate that our approach significantly improves over the state-of-the-art algorithms.

Some of the thousand words a picture is worth.

PubMed

Mandler, J M; Johnson, N S

1976-09-01

The effects of real-world schemata on recognition of complex pictures were studied. Two kinds of pictures were used: pictures of objects forming real-world scenes and unorganized collections of the same objects. The recognition test employed distractors that varied four types of information: inventory, spatial location, descriptive and spatial composition. Results emphasized the selective nature of schemata since superior recognition of one kind of information was offset by loss of another. Spatial location information was better recognized in real-world scenes and spatial composition information was better recognized in unorganized scenes. Organized and unorganized pictures did not differ with respect of inventory and descriptive information. The longer the pictures were studied, the longer subjects took to recognize them. Reaction time for hits, misses, and false alarms increased dramatically as presentation time increased from 5 to 60 sec. It was suggested that detection of a difference in a distractor terminated search, but that when no difference was detected, an exhaustive search of the available information took place.

Interactive object modelling based on piecewise planar surface patches☆

PubMed Central

Prankl, Johann; Zillich, Michael; Vincze, Markus

2013-01-01

Detecting elements such as planes in 3D is essential to describe objects for applications such as robotics and augmented reality. While plane estimation is well studied, table-top scenes exhibit a large number of planes and methods often lock onto a dominant plane or do not estimate 3D object structure but only homographies of individual planes. In this paper we introduce MDL to the problem of incrementally detecting multiple planar patches in a scene using tracked interest points in image sequences. Planar patches are reconstructed and stored in a keyframe-based graph structure. In case different motions occur, separate object hypotheses are modelled from currently visible patches and patches seen in previous frames. We evaluate our approach on a standard data set published by the Visual Geometry Group at the University of Oxford [24] and on our own data set containing table-top scenes. Results indicate that our approach significantly improves over the state-of-the-art algorithms. PMID:24511219

An Algorithm for Pedestrian Detection in Multispectral Image Sequences

NASA Astrophysics Data System (ADS)

Kniaz, V. V.; Fedorenko, V. V.

2017-05-01

The growing interest for self-driving cars provides a demand for scene understanding and obstacle detection algorithms. One of the most challenging problems in this field is the problem of pedestrian detection. Main difficulties arise from a diverse appearances of pedestrians. Poor visibility conditions such as fog and low light conditions also significantly decrease the quality of pedestrian detection. This paper presents a new optical flow based algorithm BipedDetet that provides robust pedestrian detection on a single-borad computer. The algorithm is based on the idea of simplified Kalman filtering suitable for realization on modern single-board computers. To detect a pedestrian a synthetic optical flow of the scene without pedestrians is generated using slanted-plane model. The estimate of a real optical flow is generated using a multispectral image sequence. The difference of the synthetic optical flow and the real optical flow provides the optical flow induced by pedestrians. The final detection of pedestrians is done by the segmentation of the difference of optical flows. To evaluate the BipedDetect algorithm a multispectral dataset was collected using a mobile robot.

Adaptive convergence nonuniformity correction algorithm.

PubMed

Qian, Weixian; Chen, Qian; Bai, Junqi; Gu, Guohua

2011-01-01

Nowadays, convergence and ghosting artifacts are common problems in scene-based nonuniformity correction (NUC) algorithms. In this study, we introduce the idea of space frequency to the scene-based NUC. Then the convergence speed factor is presented, which can adaptively change the convergence speed by a change of the scene dynamic range. In fact, the convergence speed factor role is to decrease the statistical data standard deviation. The nonuniformity space relativity characteristic was summarized by plenty of experimental statistical data. The space relativity characteristic was used to correct the convergence speed factor, which can make it more stable. Finally, real and simulated infrared image sequences were applied to demonstrate the positive effect of our algorithm.

Oculomotor capture during real-world scene viewing depends on cognitive load.

PubMed

Matsukura, Michi; Brockmole, James R; Boot, Walter R; Henderson, John M

2011-03-25

It has been claimed that gaze control during scene viewing is largely governed by stimulus-driven, bottom-up selection mechanisms. Recent research, however, has strongly suggested that observers' top-down control plays a dominant role in attentional prioritization in scenes. A notable exception to this strong top-down control is oculomotor capture, where visual transients in a scene draw the eyes. One way to test whether oculomotor capture during scene viewing is independent of an observer's top-down goal setting is to reduce observers' cognitive resource availability. In the present study, we examined whether increasing observers' cognitive load influences the frequency and speed of oculomotor capture during scene viewing. In Experiment 1, we tested whether increasing observers' cognitive load modulates the degree of oculomotor capture by a new object suddenly appeared in a scene. Similarly, in Experiment 2, we tested whether increasing observers' cognitive load modulates the degree of oculomotor capture by an object's color change. In both experiments, the degree of oculomotor capture decreased as observers' cognitive resources were reduced. These results suggest that oculomotor capture during scene viewing is dependent on observers' top-down selection mechanisms. Copyright © 2011 Elsevier Ltd. All rights reserved.

Assessment of Cloud Screening with Apparent Surface Reflectance in Support of the ICESat-2 Mission

NASA Technical Reports Server (NTRS)

Yang, Yuekui; Marshak, Alexander; Palm, Stephen P.; Wang, Zhuosen; Schaaf, Crystal

2011-01-01

The separation of cloud and clear scenes is usually one of the first steps in satellite data analysis. Before deriving a geophysical product, almost every satellite mission requires a cloud mask to label a scene as either clear or cloudy through a cloud detection procedure. For clear scenes, products such as surface properties may be retrieved; for cloudy scenes, scientist can focus on studying the cloud properties. Hence the quality of cloud detection directly affects the quality of most satellite operational and research products. This is certainly true for the Ice, Cloud, and land Elevation Satellite-2 (lCESat-2), which is the successor to the ICESat-l. As a top priority mission, ICESat-2 will continue to provide measurements of ice sheets and sea ice elevation on a global scale. Studies have shown that clouds can significantly affect the accuracy of the retrieved results. For example, some of the photons (a photon is a basic unit of light) in the laser beam will be scattered by cloud particles on its way. So instead of traveling in a straight line, these photons are scattered sideways and have traveled a longer path. This will result in biases in ice sheet elevation measurements. Hence cloud screening must be done and be done accurately before the retrievals.

Real-time movement detection and analysis for video surveillance applications

NASA Astrophysics Data System (ADS)

Hueber, Nicolas; Hennequin, Christophe; Raymond, Pierre; Moeglin, Jean-Pierre

2014-06-01

Pedestrian movement along critical infrastructures like pipes, railways or highways, is of major interest in surveillance applications as well as its behavior in urban environment. The goal is to anticipate illicit or dangerous human activities. For this purpose, we propose an all-in-one small autonomous system which delivers high level statistics and reports alerts in specific cases. This situational awareness project leads us to manage efficiently the scene by performing movement analysis. A dynamic background extraction algorithm is developed to reach the degree of robustness against natural and urban environment perturbations and also to match the embedded implementation constraints. When changes are detected in the scene, specific patterns are applied to detect and highlight relevant movements. Depending on the applications, specific descriptors can be extracted and fused in order to reach a high level of interpretation. In this paper, our approach is applied to two operational use cases: pedestrian urban statistics and railway surveillance. In the first case, a grid of prototypes is deployed over a city centre to collect pedestrian movement statistics up to a macroscopic level of analysis. The results demonstrate the relevance of the delivered information; in particular, the flow density map highlights pedestrian preferential paths along the streets. In the second case, one prototype is set next to high speed train tracks to secure the area. The results exhibit a low false alarm rate and assess our approach of a large sensor network for delivering a precise operational picture without overwhelming a supervisor.

Efficient RPG detection in noisy 3D image data

NASA Astrophysics Data System (ADS)

Pipitone, Frank

2011-06-01

We address the automatic detection of Ambush weapons such as rocket propelled grenades (RPGs) from range data which might be derived from multiple camera stereo with textured illumination or by other means. We describe our initial work in a new project involving the efficient acquisition of 3D scene data as well as discrete point invariant techniques to perform real time search for threats to a convoy. The shapes of the jump boundaries in the scene are exploited in this paper, rather than on-surface points, due to the large error typical of depth measurement at long range and the relatively high resolution obtainable in the transverse direction. We describe examples of the generation of a novel range-scaled chain code for detecting and matching jump boundaries.

Mining Very High Resolution INSAR Data Based On Complex-GMRF Cues And Relevance Feedback

NASA Astrophysics Data System (ADS)

Singh, Jagmal; Popescu, Anca; Soccorsi, Matteo; Datcu, Mihai

2012-01-01

With the increase in number of remote sensing satellites, the number of image-data scenes in our repositories is also increasing and a large quantity of these scenes are never received and used. Thus automatic retrieval of de- sired image-data using query by image content to fully utilize the huge repository volume is becoming of great interest. Generally different users are interested in scenes containing different kind of objects and structures. So its important to analyze all the image information mining (IIM) methods so that its easier for user to select a method depending upon his/her requirement. We concentrate our study only on high-resolution SAR images and we propose to use InSAR observations instead of only one single look complex (SLC) images for mining scenes containing coherent objects such as high-rise buildings. However in case of objects with less coherence like areas with vegetation cover, SLC images exhibits better performance. We demonstrate IIM performance comparison using complex-Gauss Markov Random Fields as texture descriptor for image patches and SVM relevance- feedback.

Data registration without explicit correspondence for adjustment of camera orientation parameter estimation

NASA Astrophysics Data System (ADS)

Barsai, Gabor

Creating accurate, current digital maps and 3-D scenes is a high priority in today's fast changing environment. The nation's maps are in a constant state of revision, with many alterations or new additions each day. Digital maps have become quite common. Google maps, Mapquest and others are examples. These also have 3-D viewing capability. Many details are now included, such as the height of low bridges, in the attribute data for the objects displayed on digital maps and scenes. To expedite the updating of these datasets, they should be created autonomously, without human intervention, from data streams. Though systems exist that attain fast, or even real-time performance mapping and reconstruction, they are typically restricted to creating sketches from the data stream, and not accurate maps or scenes. The ever increasing amount of image data available from private companies, governments and the internet, suggest the development of an automated system is of utmost importance. The proposed framework can create 3-D views autonomously; which extends the functionality of digital mapping. The first step to creating 3-D views is to reconstruct the scene of the area to be mapped. To reconstruct a scene from heterogeneous sources, the data has to be registered: either to each other or, preferably, to a general, absolute coordinate system. Registering an image is based on the reconstruction of the geometric relationship of the image to the coordinate system at the time of imaging. Registration is the process of determining the geometric transformation parameters of a dataset in one coordinate system, the source, with respect to the other coordinate system, the target. The advantages of fusing these datasets by registration manifests itself by the data contained in the complementary information that different modality datasets have. The complementary characteristics of these systems can be fully utilized only after successful registration of the photogrammetric and alternative data relative to a common reference frame. This research provides a novel approach to finding registration parameters, without the explicit use of conjugate points, but using conjugate features. These features are open or closed free-form linear features, there is no need for a parametric or any other type of representation of these features The proposed method will use different modality datasets of the same area: lidar data, image data and GIS data. There are two datasets: one from the Ohio State University and the other from San Bernardino, California. The reconstruction of scenes from imagery and range data, using laser and radar data, has been an active research area in the fields of photogrammetry and computer vision. Automatic, or just less human intervention, would have a great impact on alleviating the "bottle-neck" that describes the current state of creating knowledge from data. Pixels or laser points, the output of the sensor, represent a discretization of the real world. By themselves, these data points do not contain representative information. The values that are associated with them, intensity values and coordinates, do not define an object, and thus accurate maps are not possible just from data. Data is not an end product, nor does it directly provide answers to applications, although implicitly, the information about the object in question is contained in the data. In some form, the data from the initial data acquisition by the sensor has to be further processed to create useable information, and this information has to be combined with facts, procedures and heuristics that can be used to make inferences for reconstruction. To reconstruct a scene perfectly, whether it is an urban or rural scene, requires prior knowledge, heuristics. Buildings are, usually, smooth surfaces and many buildings are blocky with orthogonal, straight edges and sides; streets are smooth; vegetation is rough, with different shapes and sizes of trees, bushes. This research provides a path to fuse data from lidar, GIS and digital multispectral images and reconstructing the precise 3-D scene model, without human intervention, regardless of the type of data or features in the data. The data are initially registered to each other using GPS/INS initial positional values, then conjugate features are found in the datasets to refine the registration. The novelty of the research is that no conjugate points are necessary in the various datasets, and registration is performed without human intervention. The proposed system uses the original lidar and GIS data and finds edges of buildings with the help of the digital images, utilizing the exterior orientation parameters to project the lidar points onto the edge extracted image/map. These edge points are then utilized to orient and locate the datasets, in a correct position with respect to each other.

Staircase-scene-based nonuniformity correction in aerial point target detection systems.

PubMed

Huo, Lijun; Zhou, Dabiao; Wang, Dejiang; Liu, Rang; He, Bin

2016-09-01

Focal-plane arrays (FPAs) are often interfered by heavy fixed-pattern noise, which severely degrades the detection rate and increases the false alarms in airborne point target detection systems. Thus, high-precision nonuniformity correction is an essential preprocessing step. In this paper, a new nonuniformity correction method is proposed based on a staircase scene. This correction method can compensate for the nonlinear response of the detector and calibrate the entire optical system with computational efficiency and implementation simplicity. Then, a proof-of-concept point target detection system is established with a long-wave Sofradir FPA. Finally, the local standard deviation of the corrected image and the signal-to-clutter ratio of the Airy disk of a Boeing B738 are measured to evaluate the performance of the proposed nonuniformity correction method. Our experimental results demonstrate that the proposed correction method achieves high-quality corrections.

An Evaluation of Pixel-Based Methods for the Detection of Floating Objects on the Sea Surface

NASA Astrophysics Data System (ADS)

Borghgraef, Alexander; Barnich, Olivier; Lapierre, Fabian; Van Droogenbroeck, Marc; Philips, Wilfried; Acheroy, Marc

2010-12-01

Ship-based automatic detection of small floating objects on an agitated sea surface remains a hard problem. Our main concern is the detection of floating mines, which proved a real threat to shipping in confined waterways during the first Gulf War, but applications include salvaging, search-and-rescue operation, perimeter, or harbour defense. Detection in infrared (IR) is challenging because a rough sea is seen as a dynamic background of moving objects with size order, shape, and temperature similar to those of the floating mine. In this paper we have applied a selection of background subtraction algorithms to the problem, and we show that the recent algorithms such as ViBe and behaviour subtraction, which take into account spatial and temporal correlations within the dynamic scene, significantly outperform the more conventional parametric techniques, with only little prior assumptions about the physical properties of the scene.

Change Detection in Uav Video Mosaics Combining a Feature Based Approach and Extended Image Differencing

NASA Astrophysics Data System (ADS)

Saur, Günter; Krüger, Wolfgang

2016-06-01

Change detection is an important task when using unmanned aerial vehicles (UAV) for video surveillance. We address changes of short time scale using observations in time distances of a few hours. Each observation (previous and current) is a short video sequence acquired by UAV in near-Nadir view. Relevant changes are, e.g., recently parked or moved vehicles. Examples for non-relevant changes are parallaxes caused by 3D structures of the scene, shadow and illumination changes, and compression or transmission artifacts. In this paper we present (1) a new feature based approach to change detection, (2) a combination with extended image differencing (Saur et al., 2014), and (3) the application to video sequences using temporal filtering. In the feature based approach, information about local image features, e.g., corners, is extracted in both images. The label "new object" is generated at image points, where features occur in the current image and no or weaker features are present in the previous image. The label "vanished object" corresponds to missing or weaker features in the current image and present features in the previous image. This leads to two "directed" change masks and differs from image differencing where only one "undirected" change mask is extracted which combines both label types to the single label "changed object". The combination of both algorithms is performed by merging the change masks of both approaches. A color mask showing the different contributions is used for visual inspection by a human image interpreter.

Method and apparatus for coherent imaging of infrared energy

DOEpatents

Hutchinson, Donald P.

1998-01-01

A coherent camera system performs ranging, spectroscopy, and thermal imaging. Local oscillator radiation is combined with target scene radiation to enable heterodyne detection by the coherent camera's two-dimensional photodetector array. Versatility enables deployment of the system in either a passive mode (where no laser energy is actively transmitted toward the target scene) or an active mode (where a transmitting laser is used to actively illuminate the target scene). The two-dimensional photodetector array eliminates the need to mechanically scan the detector. Each element of the photodetector array produces an intermediate frequency signal that is amplified, filtered, and rectified by the coherent camera's integrated circuitry. By spectroscopic examination of the frequency components of each pixel of the detector array, a high-resolution, three-dimensional or holographic image of the target scene is produced for applications such as air pollution studies, atmospheric disturbance monitoring, and military weapons targeting.

Method and apparatus for coherent imaging of infrared energy

DOEpatents

Hutchinson, D.P.

1998-05-12

A coherent camera system performs ranging, spectroscopy, and thermal imaging. Local oscillator radiation is combined with target scene radiation to enable heterodyne detection by the coherent camera`s two-dimensional photodetector array. Versatility enables deployment of the system in either a passive mode (where no laser energy is actively transmitted toward the target scene) or an active mode (where a transmitting laser is used to actively illuminate the target scene). The two-dimensional photodetector array eliminates the need to mechanically scan the detector. Each element of the photodetector array produces an intermediate frequency signal that is amplified, filtered, and rectified by the coherent camera`s integrated circuitry. By spectroscopic examination of the frequency components of each pixel of the detector array, a high-resolution, three-dimensional or holographic image of the target scene is produced for applications such as air pollution studies, atmospheric disturbance monitoring, and military weapons targeting. 8 figs.

Illumination discrimination in the absence of a fixed surface-reflectance layout

PubMed Central

Radonjić, Ana; Ding, Xiaomao; Krieger, Avery; Aston, Stacey; Hurlbert, Anya C.; Brainard, David H.

2018-01-01

Previous studies have shown that humans can discriminate spectral changes in illumination and that this sensitivity depends both on the chromatic direction of the illumination change and on the ensemble of surfaces in the scene. These studies, however, always used stimulus scenes with a fixed surface-reflectance layout. Here we compared illumination discrimination for scenes in which the surface reflectance layout remains fixed (fixed-surfaces condition) to those in which surface reflectances were shuffled randomly across scenes, but with the mean scene reflectance held approximately constant (shuffled-surfaces condition). Illumination discrimination thresholds in the fixed-surfaces condition were commensurate with previous reports. Thresholds in the shuffled-surfaces condition, however, were considerably elevated. Nonetheless, performance in the shuffled-surfaces condition exceeded that attainable through random guessing. Analysis of eye fixations revealed that in the fixed-surfaces condition, low illumination discrimination thresholds (across observers) were predicted by low overall fixation spread and high consistency of fixation location and fixated surface reflectances across trial intervals. Performance in the shuffled-surfaces condition was not systematically related to any of the eye-fixation characteristics we examined for that condition, but was correlated with performance in the fixed-surfaces condition. PMID:29904786

Stimulus change detection in phasic auditory units in the frog midbrain: frequency and ear specific adaptation.

PubMed

Ponnath, Abhilash; Hoke, Kim L; Farris, Hamilton E

2013-04-01

Neural adaptation, a reduction in the response to a maintained stimulus, is an important mechanism for detecting stimulus change. Contributing to change detection is the fact that adaptation is often stimulus specific: adaptation to a particular stimulus reduces excitability to a specific subset of stimuli, while the ability to respond to other stimuli is unaffected. Phasic cells (e.g., cells responding to stimulus onset) are good candidates for detecting the most rapid changes in natural auditory scenes, as they exhibit fast and complete adaptation to an initial stimulus presentation. We made recordings of single phasic auditory units in the frog midbrain to determine if adaptation was specific to stimulus frequency and ear of input. In response to an instantaneous frequency step in a tone, 28% of phasic cells exhibited frequency specific adaptation based on a relative frequency change (delta-f=±16%). Frequency specific adaptation was not limited to frequency steps, however, as adaptation was also overcome during continuous frequency modulated stimuli and in response to spectral transients interrupting tones. The results suggest that adaptation is separated for peripheral (e.g., frequency) channels. This was tested directly using dichotic stimuli. In 45% of binaural phasic units, adaptation was ear specific: adaptation to stimulation of one ear did not affect responses to stimulation of the other ear. Thus, adaptation exhibited specificity for stimulus frequency and lateralization at the level of the midbrain. This mechanism could be employed to detect rapid stimulus change within and between sound sources in complex acoustic environments.

Stimulus change detection in phasic auditory units in the frog midbrain: frequency and ear specific adaptation

PubMed Central

Ponnath, Abhilash; Hoke, Kim L.

2013-01-01

Neural adaptation, a reduction in the response to a maintained stimulus, is an important mechanism for detecting stimulus change. Contributing to change detection is the fact that adaptation is often stimulus specific: adaptation to a particular stimulus reduces excitability to a specific subset of stimuli, while the ability to respond to other stimuli is unaffected. Phasic cells (e.g., cells responding to stimulus onset) are good candidates for detecting the most rapid changes in natural auditory scenes, as they exhibit fast and complete adaptation to an initial stimulus presentation. We made recordings of single phasic auditory units in the frog midbrain to determine if adaptation was specific to stimulus frequency and ear of input. In response to an instantaneous frequency step in a tone, 28 % of phasic cells exhibited frequency specific adaptation based on a relative frequency change (delta-f = ±16 %). Frequency specific adaptation was not limited to frequency steps, however, as adaptation was also overcome during continuous frequency modulated stimuli and in response to spectral transients interrupting tones. The results suggest that adaptation is separated for peripheral (e.g., frequency) channels. This was tested directly using dichotic stimuli. In 45 % of binaural phasic units, adaptation was ear specific: adaptation to stimulation of one ear did not affect responses to stimulation of the other ear. Thus, adaptation exhibited specificity for stimulus frequency and lateralization at the level of the midbrain. This mechanism could be employed to detect rapid stimulus change within and between sound sources in complex acoustic environments. PMID:23344947

Color appearance and color rendering of HDR scenes: an experiment

NASA Astrophysics Data System (ADS)

Parraman, Carinna; Rizzi, Alessandro; McCann, John J.

2009-01-01

In order to gain a deeper understanding of the appearance of coloured objects in a three-dimensional scene, the research introduces a multidisciplinary experimental approach. The experiment employed two identical 3-D Mondrians, which were viewed and compared side by side. Each scene was subjected to different lighting conditions. First, we used an illumination cube to diffuse the light and illuminate all the objects from each direction. This produced a low-dynamicrange (LDR) image of the 3-D Mondrian scene. Second, in order to make a high-dynamic range (HDR) image of the same objects, we used a directional 150W spotlight and an array of WLEDs assembled in a flashlight. The scenes were significant as each contained exactly the same three-dimensional painted colour blocks that were arranged in the same position in the still life. The blocks comprised 6 hue colours and 5 tones from white to black. Participants from the CREATE project were asked to consider the change in the appearance of a selection of colours according to lightness, hue, and chroma, and to rate how the change in illumination affected appearance. We measured the light coming to the eye from still-life surfaces with a colorimeter (Yxy). We captured the scene radiance using multiple exposures with a number of different cameras. We have begun a programme of digital image processing of these scene capture methods. This multi-disciplinary programme continues until 2010, so this paper is an interim report on the initial phases and a description of the ongoing project.

Frames of mental illness in the Yoruba genre of Nigerian movies: implications for orthodox mental health care.

PubMed

Atilola, Olayinka; Olayiwola, Funmilayo

2013-06-01

This study examines the modes of framing mental illness in the Yoruba genre of Nigerian movies. All Yoruba films on display in a convenient sample of movie rental shops in Ibadan (Nigeria) were sampled for content. Of the 103 films studied, 27 (26.2%) contained scenes depicting mental illness. Psychotic symptoms were the most commonly depicted, while effective treatments were mostly depicted as taking place in unorthodox settings. The most commonly depicted aetiology of mental illness was sorcery and enchantment by witches and wizards, as well as other supernatural forces. Scenes of mental illness are common in Nigerian movies and these depictions-though reflecting the popular explanatory models of Yoruba-speaking Nigerians about mental illness- may impede utilization of mental health care services and ongoing efforts to reduce psychiatry stigma in this region. Efforts to reduce stigma and improve service utilization should engage the film industry.

Synchronous contextual irregularities affect early scene processing: replication and extension.

PubMed

Mudrik, Liad; Shalgi, Shani; Lamy, Dominique; Deouell, Leon Y

2014-04-01

Whether contextual regularities facilitate perceptual stages of scene processing is widely debated, and empirical evidence is still inconclusive. Specifically, it was recently suggested that contextual violations affect early processing of a scene only when the incongruent object and the scene are presented a-synchronously, creating expectations. We compared event-related potentials (ERPs) evoked by scenes that depicted a person performing an action using either a congruent or an incongruent object (e.g., a man shaving with a razor or with a fork) when scene and object were presented simultaneously. We also explored the role of attention in contextual processing by using a pre-cue to direct subjects׳ attention towards or away from the congruent/incongruent object. Subjects׳ task was to determine how many hands the person in the picture used in order to perform the action. We replicated our previous findings of frontocentral negativity for incongruent scenes that started ~ 210 ms post stimulus presentation, even earlier than previously found. Surprisingly, this incongruency ERP effect was negatively correlated with the reaction times cost on incongruent scenes. The results did not allow us to draw conclusions about the role of attention in detecting the regularity, due to a weak attention manipulation. By replicating the 200-300 ms incongruity effect with a new group of subjects at even earlier latencies than previously reported, the results strengthen the evidence for contextual processing during this time window even when simultaneous presentation of the scene and object prevent the formation of prior expectations. We discuss possible methodological limitations that may account for previous failures to find this an effect, and conclude that contextual information affects object model selection processes prior to full object identification, with semantic knowledge activation stages unfolding only later on. Copyright © 2014 Elsevier Ltd. All rights reserved.

Ground-plane influences on size estimation in early visual processing.

PubMed

Champion, Rebecca A; Warren, Paul A

2010-07-21

Ground-planes have an important influence on the perception of 3D space (Gibson, 1950) and it has been shown that the assumption that a ground-plane is present in the scene plays a role in the perception of object distance (Bruno & Cutting, 1988). Here, we investigate whether this influence is exerted at an early stage of processing, to affect the rapid estimation of 3D size. Participants performed a visual search task in which they searched for a target object that was larger or smaller than distracter objects. Objects were presented against a background that contained either a frontoparallel or slanted 3D surface, defined by texture gradient cues. We measured the effect on search performance of target location within the scene (near vs. far) and how this was influenced by scene orientation (which, e.g., might be consistent with a ground or ceiling plane, etc.). In addition, we investigated how scene orientation interacted with texture gradient information (indicating surface slant), to determine how these separate cues to scene layout were combined. We found that the difference in target detection performance between targets at the front and rear of the simulated scene was maximal when the scene was consistent with a ground-plane - consistent with the use of an elevation cue to object distance. In addition, we found a significant increase in the size of this effect when texture gradient information (indicating surface slant) was present, but no interaction between texture gradient and scene orientation information. We conclude that scene orientation plays an important role in the estimation of 3D size at an early stage of processing, and suggest that elevation information is linearly combined with texture gradient information for the rapid estimation of 3D size. Copyright 2010 Elsevier Ltd. All rights reserved.

A systematic comparison between visual cues for boundary detection.

PubMed

Mély, David A; Kim, Junkyung; McGill, Mason; Guo, Yuliang; Serre, Thomas

2016-03-01

The detection of object boundaries is a critical first step for many visual processing tasks. Multiple cues (we consider luminance, color, motion and binocular disparity) available in the early visual system may signal object boundaries but little is known about their relative diagnosticity and how to optimally combine them for boundary detection. This study thus aims at understanding how early visual processes inform boundary detection in natural scenes. We collected color binocular video sequences of natural scenes to construct a video database. Each scene was annotated with two full sets of ground-truth contours (one set limited to object boundaries and another set which included all edges). We implemented an integrated computational model of early vision that spans all considered cues, and then assessed their diagnosticity by training machine learning classifiers on individual channels. Color and luminance were found to be most diagnostic while stereo and motion were least. Combining all cues yielded a significant improvement in accuracy beyond that of any cue in isolation. Furthermore, the accuracy of individual cues was found to be a poor predictor of their unique contribution for the combination. This result suggested a complex interaction between cues, which we further quantified using regularization techniques. Our systematic assessment of the accuracy of early vision models for boundary detection together with the resulting annotated video dataset should provide a useful benchmark towards the development of higher-level models of visual processing. Copyright © 2016 Elsevier Ltd. All rights reserved.

Information theoretic analysis of edge detection in visual communication

NASA Astrophysics Data System (ADS)

Jiang, Bo; Rahman, Zia-ur

2010-08-01

Generally, the designs of digital image processing algorithms and image gathering devices remain separate. Consequently, the performance of digital image processing algorithms is evaluated without taking into account the artifacts introduced into the process by the image gathering process. However, experiments show that the image gathering process profoundly impacts the performance of digital image processing and the quality of the resulting images. Huck et al. proposed one definitive theoretic analysis of visual communication channels, where the different parts, such as image gathering, processing, and display, are assessed in an integrated manner using Shannon's information theory. In this paper, we perform an end-to-end information theory based system analysis to assess edge detection methods. We evaluate the performance of the different algorithms as a function of the characteristics of the scene, and the parameters, such as sampling, additive noise etc., that define the image gathering system. The edge detection algorithm is regarded to have high performance only if the information rate from the scene to the edge approaches the maximum possible. This goal can be achieved only by jointly optimizing all processes. People generally use subjective judgment to compare different edge detection methods. There is not a common tool that can be used to evaluate the performance of the different algorithms, and to give people a guide for selecting the best algorithm for a given system or scene. Our information-theoretic assessment becomes this new tool to which allows us to compare the different edge detection operators in a common environment.

- and Graph-Based Point Cloud Segmentation of 3d Scenes Using Perceptual Grouping Laws

NASA Astrophysics Data System (ADS)

Xu, Y.; Hoegner, L.; Tuttas, S.; Stilla, U.

2017-05-01

Segmentation is the fundamental step for recognizing and extracting objects from point clouds of 3D scene. In this paper, we present a strategy for point cloud segmentation using voxel structure and graph-based clustering with perceptual grouping laws, which allows a learning-free and completely automatic but parametric solution for segmenting 3D point cloud. To speak precisely, two segmentation methods utilizing voxel and supervoxel structures are reported and tested. The voxel-based data structure can increase efficiency and robustness of the segmentation process, suppressing the negative effect of noise, outliers, and uneven points densities. The clustering of voxels and supervoxel is carried out using graph theory on the basis of the local contextual information, which commonly conducted utilizing merely pairwise information in conventional clustering algorithms. By the use of perceptual laws, our method conducts the segmentation in a pure geometric way avoiding the use of RGB color and intensity information, so that it can be applied to more general applications. Experiments using different datasets have demonstrated that our proposed methods can achieve good results, especially for complex scenes and nonplanar surfaces of objects. Quantitative comparisons between our methods and other representative segmentation methods also confirms the effectiveness and efficiency of our proposals.

A Method of Sky Ripple Residual Nonuniformity Reduction for a Cooled Infrared Imager and Hardware Implementation.

PubMed

Li, Yiyang; Jin, Weiqi; Li, Shuo; Zhang, Xu; Zhu, Jin

2017-05-08

Cooled infrared detector arrays always suffer from undesired ripple residual nonuniformity (RNU) in sky scene observations. The ripple residual nonuniformity seriously affects the imaging quality, especially for small target detection. It is difficult to eliminate it using the calibration-based techniques and the current scene-based nonuniformity algorithms. In this paper, we present a modified temporal high-pass nonuniformity correction algorithm using fuzzy scene classification. The fuzzy scene classification is designed to control the correction threshold so that the algorithm can remove ripple RNU without degrading the scene details. We test the algorithm on a real infrared sequence by comparing it to several well-established methods. The result shows that the algorithm has obvious advantages compared with the tested methods in terms of detail conservation and convergence speed for ripple RNU correction. Furthermore, we display our architecture with a prototype built on a Xilinx Virtex-5 XC5VLX50T field-programmable gate array (FPGA), which has two advantages: (1) low resources consumption; and (2) small hardware delay (less than 10 image rows). It has been successfully applied in an actual system.

LivePhantom: Retrieving Virtual World Light Data to Real Environments.

PubMed

Kolivand, Hoshang; Billinghurst, Mark; Sunar, Mohd Shahrizal

2016-01-01

To achieve realistic Augmented Reality (AR), shadows play an important role in creating a 3D impression of a scene. Casting virtual shadows on real and virtual objects is one of the topics of research being conducted in this area. In this paper, we propose a new method for creating complex AR indoor scenes using real time depth detection to exert virtual shadows on virtual and real environments. A Kinect camera was used to produce a depth map for the physical scene mixing into a single real-time transparent tacit surface. Once this is created, the camera's position can be tracked from the reconstructed 3D scene. Real objects are represented by virtual object phantoms in the AR scene enabling users holding a webcam and a standard Kinect camera to capture and reconstruct environments simultaneously. The tracking capability of the algorithm is shown and the findings are assessed drawing upon qualitative and quantitative methods making comparisons with previous AR phantom generation applications. The results demonstrate the robustness of the technique for realistic indoor rendering in AR systems.

LivePhantom: Retrieving Virtual World Light Data to Real Environments

PubMed Central

2016-01-01

To achieve realistic Augmented Reality (AR), shadows play an important role in creating a 3D impression of a scene. Casting virtual shadows on real and virtual objects is one of the topics of research being conducted in this area. In this paper, we propose a new method for creating complex AR indoor scenes using real time depth detection to exert virtual shadows on virtual and real environments. A Kinect camera was used to produce a depth map for the physical scene mixing into a single real-time transparent tacit surface. Once this is created, the camera’s position can be tracked from the reconstructed 3D scene. Real objects are represented by virtual object phantoms in the AR scene enabling users holding a webcam and a standard Kinect camera to capture and reconstruct environments simultaneously. The tracking capability of the algorithm is shown and the findings are assessed drawing upon qualitative and quantitative methods making comparisons with previous AR phantom generation applications. The results demonstrate the robustness of the technique for realistic indoor rendering in AR systems. PMID:27930663

Enhancing a Simple MODIS Cloud Mask Algorithm for the Landsat Data Continuity Mission

NASA Technical Reports Server (NTRS)

Wilson, Michael J.; Oreopoulos, Lazarous

2011-01-01

The presence of clouds in images acquired by the Landsat series of satellites is usually an undesirable, but generally unavoidable fact. With the emphasis of the program being on land imaging, the suspended liquid/ice particles of which clouds are made of fully or partially obscure the desired observational target. Knowing the amount and location of clouds in a Landsat scene is therefore valuable information for scene selection, for making clear-sky composites from multiple scenes, and for scheduling future acquisitions. The two instruments in the upcoming Landsat Data Continuity Mission (LDCM) will include new channels that will enhance our ability to detect high clouds which are often also thin in the sense that a large fraction of solar radiation can pass through them. This work studies the potential impact of these new channels on enhancing LDCM's cloud detection capabilities compared to previous Landsat missions. We revisit a previously published scheme for cloud detection and add new tests to capture more of the thin clouds that are harder to detect with the more limited arsenal channels. Since there are no Landsat data yet that include the new LDCM channels, we resort to data from another instrument, MODIS, which has these bands, as well as the other bands of LDCM, to test the capabilities of our new algorithm. By comparing our revised scheme's performance against the performance of the official MODIS cloud detection scheme, we conclude that the new scheme performs better than the earlier scheme which was not very good at thin cloud detection.

Using Information From Prior Satellite Scans to Improve Cloud Detection Near the Day-Night Terminator

NASA Technical Reports Server (NTRS)

Yost, Christopher R.; Minnis, Patrick; Trepte, Qing Z.; Palikonda, Rabindra; Ayers, Jeffrey K.; Spangenberg, Doulas A.

2012-01-01

With geostationary satellite data it is possible to have a continuous record of diurnal cycles of cloud properties for a large portion of the globe. Daytime cloud property retrieval algorithms are typically superior to nighttime algorithms because daytime methods utilize measurements of reflected solar radiation. However, reflected solar radiation is difficult to accurately model for high solar zenith angles where the amount of incident radiation is small. Clear and cloudy scenes can exhibit very small differences in reflected radiation and threshold-based cloud detection methods have more difficulty setting the proper thresholds for accurate cloud detection. Because top-of-atmosphere radiances are typically more accurately modeled outside the terminator region, information from previous scans can help guide cloud detection near the terminator. This paper presents an algorithm that uses cloud fraction and clear and cloudy infrared brightness temperatures from previous satellite scan times to improve the performance of a threshold-based cloud mask near the terminator. Comparisons of daytime, nighttime, and terminator cloud fraction derived from Geostationary Operational Environmental Satellite (GOES) radiance measurements show that the algorithm greatly reduces the number of false cloud detections and smoothes the transition from the daytime to the nighttime clod detection algorithm. Comparisons with the Geoscience Laser Altimeter System (GLAS) data show that using this algorithm decreases the number of false detections by approximately 20 percentage points.

Vision System for Coarsely Estimating Motion Parameters for Unknown Fast Moving Objects in Space

PubMed Central

Chen, Min; Hashimoto, Koichi

2017-01-01

Motivated by biological interests in analyzing navigation behaviors of flying animals, we attempt to build a system measuring their motion states. To do this, in this paper, we build a vision system to detect unknown fast moving objects within a given space, calculating their motion parameters represented by positions and poses. We proposed a novel method to detect reliable interest points from images of moving objects, which can be hardly detected by general purpose interest point detectors. 3D points reconstructed using these interest points are then grouped and maintained for detected objects, according to a careful schedule, considering appearance and perspective changes. In the estimation step, a method is introduced to adapt the robust estimation procedure used for dense point set to the case for sparse set, reducing the potential risk of greatly biased estimation. Experiments are conducted against real scenes, showing the capability of the system of detecting multiple unknown moving objects and estimating their positions and poses. PMID:29206189

Onboard Detection of Active Canadian Sulfur Springs: A Europa Analogue

NASA Technical Reports Server (NTRS)

Castano, Rebecca; Wagstaff, Kiri; Gleeson, Damhnait; Pappalardo, Robert; Chien, Steve; Tran, Daniel; Scharenbroich, Lucas; Moghaddam, Baback; Tang, Benyang; Bue, Brian;