Text Detection and Translation from Natural Scenes

DTIC Science & Technology

2001-06-01

is no explicit tags around Chinese words. A module for Chinese word segmentation is included in the system. This segmentor uses a word- frequency ... list to make segmentation decisions. We tested the EBMT based method using randomly selected 50 signs from our database, assuming perfect sign

Systems and Methods for Automated Water Detection Using Visible Sensors

NASA Technical Reports Server (NTRS)

Rankin, Arturo L. (Inventor); Matthies, Larry H. (Inventor); Bellutta, Paolo (Inventor)

2016-01-01

Systems and methods are disclosed that include automated machine vision that can utilize images of scenes captured by a 3D imaging system configured to image light within the visible light spectrum to detect water. One embodiment includes autonomously detecting water bodies within a scene including capturing at least one 3D image of a scene using a sensor system configured to detect visible light and to measure distance from points within the scene to the sensor system, and detecting water within the scene using a processor configured to detect regions within each of the at least one 3D images that possess at least one characteristic indicative of the presence of water.

Guidance of Attention to Objects and Locations by Long-Term Memory of Natural Scenes

ERIC Educational Resources Information Center

Becker, Mark W.; Rasmussen, Ian P.

2008-01-01

Four flicker change-detection experiments demonstrate that scene-specific long-term memory guides attention to both behaviorally relevant locations and objects within a familiar scene. Participants performed an initial block of change-detection trials, detecting the addition of an object to a natural scene. After a 30-min delay, participants…

Scene incongruity and attention.

PubMed

Mack, Arien; Clarke, Jason; Erol, Muge; Bert, John

2017-02-01

Does scene incongruity, (a mismatch between scene gist and a semantically incongruent object), capture attention and lead to conscious perception? We explored this question using 4 different procedures: Inattention (Experiment 1), Scene description (Experiment 2), Change detection (Experiment 3), and Iconic Memory (Experiment 4). We found no differences between scene incongruity and scene congruity in Experiments 1, 2, and 4, although in Experiment 3 change detection was faster for scenes containing an incongruent object. We offer an explanation for why the change detection results differ from the results of the other three experiments. In all four experiments, participants invariably failed to report the incongruity and routinely mis-described it by normalizing the incongruent object. None of the results supports the claim that semantic incongruity within a scene invariably captures attention and provide strong evidence of the dominant role of scene gist in determining what is perceived. Copyright © 2016 Elsevier Inc. All rights reserved.

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.

Idiosyncratic characteristics of saccadic eye movements when viewing different visual environments.

PubMed

Andrews, T J; Coppola, D M

1999-08-01

Eye position was recorded in different viewing conditions to assess whether the temporal and spatial characteristics of saccadic eye movements in different individuals are idiosyncratic. Our aim was to determine the degree to which oculomotor control is based on endogenous factors. A total of 15 naive subjects viewed five visual environments: (1) The absence of visual stimulation (i.e. a dark room); (2) a repetitive visual environment (i.e. simple textured patterns); (3) a complex natural scene; (4) a visual search task; and (5) reading text. Although differences in visual environment had significant effects on eye movements, idiosyncrasies were also apparent. For example, the mean fixation duration and size of an individual's saccadic eye movements when passively viewing a complex natural scene covaried significantly with those same parameters in the absence of visual stimulation and in a repetitive visual environment. In contrast, an individual's spatio-temporal characteristics of eye movements during active tasks such as reading text or visual search covaried together, but did not correlate with the pattern of eye movements detected when viewing a natural scene, simple patterns or in the dark. These idiosyncratic patterns of eye movements in normal viewing reveal an endogenous influence on oculomotor control. The independent covariance of eye movements during different visual tasks shows that saccadic eye movements during active tasks like reading or visual search differ from those engaged during the passive inspection of visual scenes.

Can cigarette warnings counterbalance effects of smoking scenes in movies?

PubMed

Golmier, Isabelle; Chebat, Jean-Charles; Gélinas-Chebat, Claire

2007-02-01

Scenes in movies where smoking occurs have been empirically shown to influence teenagers to smoke cigarettes. The capacity of a Canadian warning label on cigarette packages to decrease the effects of smoking scenes in popular movies has been investigated. A 2 x 3 factorial design was used to test the effects of the same movie scene with or without electronic manipulation of all elements related to smoking, and cigarette pack warnings, i.e., no warning, text-only warning, and text+picture warning. Smoking-related stereotypes and intent to smoke of teenagers were measured. It was found that, in the absence of warning, and in the presence of smoking scenes, teenagers showed positive smoking-related stereotypes. However, these effects were not observed if the teenagers were first exposed to a picture and text warning. Also, smoking-related stereotypes mediated the relationship of the combined presentation of a text and picture warning and a smoking scene on teenagers' intent to smoke. Effectiveness of Canadian warning labels to prevent or to decrease cigarette smoking among teenagers is discussed, and areas of research are proposed.

Effects of capacity limits, memory loss, and sound type in change deafness.

PubMed

Gregg, Melissa K; Irsik, Vanessa C; Snyder, Joel S

2017-11-01

Change deafness, the inability to notice changes to auditory scenes, has the potential to provide insights about sound perception in busy situations typical of everyday life. We determined the extent to which change deafness to sounds is due to the capacity of processing multiple sounds and the loss of memory for sounds over time. We also determined whether these processing limitations work differently for varying types of sounds within a scene. Auditory scenes composed of naturalistic sounds, spectrally dynamic unrecognizable sounds, tones, and noise rhythms were presented in a change-detection task. On each trial, two scenes were presented that were same or different. We manipulated the number of sounds within each scene to measure memory capacity and the silent interval between scenes to measure memory loss. For all sounds, change detection was worse as scene size increased, demonstrating the importance of capacity limits. Change detection to the natural sounds did not deteriorate much as the interval between scenes increased up to 2,000 ms, but it did deteriorate substantially with longer intervals. For artificial sounds, in contrast, change-detection performance suffered even for very short intervals. The results suggest that change detection is generally limited by capacity, regardless of sound type, but that auditory memory is more enduring for sounds with naturalistic acoustic structures.

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.

Recognition and defect detection of dot-matrix text via variation-model based learning

NASA Astrophysics Data System (ADS)

Ohyama, Wataru; Suzuki, Koushi; Wakabayashi, Tetsushi

2017-03-01

An algorithm for recognition and defect detection of dot-matrix text printed on products is proposed. Extraction and recognition of dot-matrix text contains several difficulties, which are not involved in standard camera-based OCR, that the appearance of dot-matrix characters is corrupted and broken by illumination, complex texture in the background and other standard characters printed on product packages. We propose a dot-matrix text extraction and recognition method which does not require any user interaction. The method employs detected location of corner points and classification score. The result of evaluation experiment using 250 images shows that recall and precision of extraction are 78.60% and 76.03%, respectively. Recognition accuracy of correctly extracted characters is 94.43%. Detecting printing defect of dot-matrix text is also important in the production scene to avoid illegal productions. We also propose a detection method for printing defect of dot-matrix characters. The method constructs a feature vector of which elements are classification scores of each character class and employs support vector machine to classify four types of printing defect. The detection accuracy of the proposed method is 96.68 %.

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.

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.

Eye movements during change detection: implications for search constraints, memory limitations, and scanning strategies.

PubMed

Zelinsky, G J

2001-02-01

Search, memory, and strategy constraints on change detection were analyzed in terms of oculomotor variables. Observers viewed a repeating sequence of three displays (Scene 1-->Mask-->Scene 2-->Mask...) and indicated the presence-absence of a changing object between Scenes 1 and 2. Scenes depicted real-world objects arranged on a surface. Manipulations included set size (one, three, or nine items) and the orientation of the changing objects (similar or different). Eye movements increased with the number of potentially changing objects in the scene, with this set size effect suggesting a relationship between change detection and search. A preferential fixation analysis determined that memory constraints are better described by the operation comparing the pre- and postchange objects than as a capacity limitation, and a scanpath analysis revealed a change detection strategy relying on the peripheral encoding and comparison of display items. These findings support a signal-in-noise interpretation of change detection in which the signal varies with the similarity of the changing objects and the noise is determined by the distractor objects and scene background.

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,…

Our Environment in Miniature: Dust and the Early Twentieth-Century Forensic Imagination

PubMed Central

BURNEY, IAN

2013-01-01

This article explores the articulation of the crime scene as a distinct space of theory and practice in the early twentieth century. In particular it focuses on the evidentiary hopes invested in what would at first seem an unpromising forensic object: dust. Ubiquitous and, to the uninitiated, characterless, dust nevertheless featured as an exemplary object of cutting-edge forensic analysis in two contemporary domains: writings of criminologists and works of detective fiction. The article considers how in these texts dust came to mark the furthest reach of a new forensic capacity they were promoting, one that drew freely upon the imagination to invest crime scene traces with meaning. PMID:23766552

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.

The Effect of Consistency on Short-Term Memory for Scenes.

PubMed

Gong, Mingliang; Xuan, Yuming; Xu, Xinwen; Fu, Xiaolan

2017-01-01

Which is more detectable, the change of a consistent or an inconsistent object in a scene? This question has been debated for decades. We noted that the change of objects in scenes might simultaneously be accompanied with gist changes. In the present study we aimed to examine how the alteration of gist, as well as the consistency of the changed objects, modulated change detection. In Experiment 1, we manipulated the semantic content by either keeping or changing the consistency of the scene. Results showed that the changes of consistent and inconsistent scenes were equally detected. More importantly, the changes were more accurately detected when scene consistency changed than when the consistency remained unchanged, regardless of the consistency of the memory scenes. A phase-scrambled version of stimuli was adopted in Experiment 2 to decouple the possible confounding effect of low-level factors. The results of Experiment 2 demonstrated that the effect found in Experiment 1 was indeed due to the change of high-level semantic consistency rather than the change of low-level physical features. Together, the study suggests that the change of consistency plays an important role in scene short-term memory, which might be attributed to the sensitivity to the change of semantic content.

The Effect of Consistency on Short-Term Memory for Scenes

PubMed Central

Gong, Mingliang; Xuan, Yuming; Xu, Xinwen; Fu, Xiaolan

2017-01-01

Which is more detectable, the change of a consistent or an inconsistent object in a scene? This question has been debated for decades. We noted that the change of objects in scenes might simultaneously be accompanied with gist changes. In the present study we aimed to examine how the alteration of gist, as well as the consistency of the changed objects, modulated change detection. In Experiment 1, we manipulated the semantic content by either keeping or changing the consistency of the scene. Results showed that the changes of consistent and inconsistent scenes were equally detected. More importantly, the changes were more accurately detected when scene consistency changed than when the consistency remained unchanged, regardless of the consistency of the memory scenes. A phase-scrambled version of stimuli was adopted in Experiment 2 to decouple the possible confounding effect of low-level factors. The results of Experiment 2 demonstrated that the effect found in Experiment 1 was indeed due to the change of high-level semantic consistency rather than the change of low-level physical features. Together, the study suggests that the change of consistency plays an important role in scene short-term memory, which might be attributed to the sensitivity to the change of semantic content. PMID:29046654

Scene text detection via extremal region based double threshold convolutional network classification

PubMed Central

Zhu, Wei; Lou, Jing; Chen, Longtao; Xia, Qingyuan

2017-01-01

In this paper, we present a robust text detection approach in natural images which is based on region proposal mechanism. A powerful low-level detector named saliency enhanced-MSER extended from the widely-used MSER is proposed by incorporating saliency detection methods, which ensures a high recall rate. Given a natural image, character candidates are extracted from three channels in a perception-based illumination invariant color space by saliency-enhanced MSER algorithm. A discriminative convolutional neural network (CNN) is jointly trained with multi-level information including pixel-level and character-level information as character candidate classifier. Each image patch is classified as strong text, weak text and non-text by double threshold filtering instead of conventional one-step classification, leveraging confident scores obtained via CNN. To further prune non-text regions, we develop a recursive neighborhood search algorithm to track credible texts from weak text set. Finally, characters are grouped into text lines using heuristic features such as spatial location, size, color, and stroke width. We compare our approach with several state-of-the-art methods, and experiments show that our method achieves competitive performance on public datasets ICDAR 2011 and ICDAR 2013. PMID:28820891

Automatic generation of pictorial transcripts of video programs

NASA Astrophysics Data System (ADS)

Shahraray, Behzad; Gibbon, David C.

1995-03-01

An automatic authoring system for the generation of pictorial transcripts of video programs which are accompanied by closed caption information is presented. A number of key frames, each of which represents the visual information in a segment of the video (i.e., a scene), are selected automatically by performing a content-based sampling of the video program. The textual information is recovered from the closed caption signal and is initially segmented based on its implied temporal relationship with the video segments. The text segmentation boundaries are then adjusted, based on lexical analysis and/or caption control information, to account for synchronization errors due to possible delays in the detection of scene boundaries or the transmission of the caption information. The closed caption text is further refined through linguistic processing for conversion to lower- case with correct capitalization. The key frames and the related text generate a compact multimedia presentation of the contents of the video program which lends itself to efficient storage and transmission. This compact representation can be viewed on a computer screen, or used to generate the input to a commercial text processing package to generate a printed version of the program.

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.

Guidance of attention to objects and locations by long-term memory of natural scenes.

PubMed

Becker, Mark W; Rasmussen, Ian P

2008-11-01

Four flicker change-detection experiments demonstrate that scene-specific long-term memory guides attention to both behaviorally relevant locations and objects within a familiar scene. Participants performed an initial block of change-detection trials, detecting the addition of an object to a natural scene. After a 30-min delay, participants performed an unanticipated 2nd block of trials. When the same scene occurred in the 2nd block, the change within the scene was (a) identical to the original change, (b) a new object appearing in the original change location, (c) the same object appearing in a new location, or (d) a new object appearing in a new location. Results suggest that attention is rapidly allocated to previously relevant locations and then to previously relevant objects. This pattern of locations dominating objects remained when object identity information was made more salient. Eye tracking verified that scene memory results in more direct scan paths to previously relevant locations and objects. This contextual guidance suggests that a high-capacity long-term memory for scenes is used to insure that limited attentional capacity is allocated efficiently rather than being squandered.

Changing scenes: memory for naturalistic events following change blindness.

PubMed

Mäntylä, Timo; Sundström, Anna

2004-11-01

Research on scene perception indicates that viewers often fail to detect large changes to scene regions when these changes occur during a visual disruption such as a saccade or a movie cut. In two experiments, we examined whether this relative inability to detect changes would produce systematic biases in event memory. In Experiment 1, participants decided whether two successively presented images were the same or different, followed by a memory task, in which they recalled the content of the viewed scene. In Experiment 2, participants viewed a short video, in which an actor carried out a series of daily activities, and central scenes' attributes were changed during a movie cut. A high degree of change blindness was observed in both experiments, and these effects were related to scene complexity (Experiment 1) and level of retrieval support (Experiment 2). Most important, participants reported the changed, rather than the initial, event attributes following a failure in change detection. These findings suggest that attentional limitations during encoding contribute to biases in episodic memory.

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.

Sustained change blindness to incremental scene rotation: a dissociation between explicit change detection and visual memory.

PubMed

Hollingworth, Andrew; Henderson, John M

2004-07-01

In a change detection paradigm, the global orientation of a natural scene was incrementally changed in 1 degree intervals. In Experiments 1 and 2, participants demonstrated sustained change blindness to incremental rotation, often coming to consider a significantly different scene viewpoint as an unchanged continuation of the original view. Experiment 3 showed that participants who failed to detect the incremental rotation nevertheless reliably detected a single-step rotation back to the initial view. Together, these results demonstrate an important dissociation between explicit change detection and visual memory. Following a change, visual memory is updated to reflect the changed state of the environment, even if the change was not detected.

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.

Use of an Infrared Thermometer with Laser Targeting in Morphological Scene Change Detection for Fire Detection

NASA Astrophysics Data System (ADS)

Tickle, Andrew J.; Singh, Harjap; Grindley, Josef E.

2013-06-01

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. This is a robust technique and can be applied many areas from leak detection to movement tracking, and further augmented to perform additional functions such as watermarking and facial detection. Fire is a severe problem, and in areas where traditional fire alarm systems are not installed or feasible, it may not be detected until it is too late. Shown here is a way of adapting the traditional Morphological Scene Change Detector (MSCD) with a temperature sensor so if both the temperature sensor and scene change detector are triggered, there is a high likelihood of fire present. Such a system would allow integration into autonomous mobile robots so that not only security patrols could be undertaken, but also fire detection.

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.

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.

The Development of Change Detection

ERIC Educational Resources Information Center

Shore, David I.; Burack, Jacob A.; Miller, Danny; Joseph, Shari; Enns, James T.

2006-01-01

Changes to a scene often go unnoticed if the objects of the change are unattended, making change detection an index of where attention is focused during scene perception. We measured change detection in school-age children and young adults by repeatedly alternating two versions of an image. To provide an age-fair assessment we used a bimanual…

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…

Logo detection and classification in a sport video: video indexing for sponsorship revenue control

NASA Astrophysics Data System (ADS)

Kovar, Bohumil; Hanjalic, Alan

2001-12-01

This paper presents a novel approach to detecting and classifying a trademark logo in frames of a sport video. In view of the fact that we attempt to detect and recognize a logo in a natural scene, the algorithm developed in this paper differs from traditional techniques for logo detection and classification that are applicable either to well-structured general text documents (e.g. invoices, memos, bank cheques) or to specialized trademark logo databases, where logos appear isolated on a clear background and where their detection and classification is not disturbed by the surrounding visual detail. Although the development of our algorithm is still in its starting phase, experimental results performed so far on a set of soccer TV broadcasts are very encouraging.

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.

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…

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…

Con-Text: Text Detection for Fine-grained Object Classification.

PubMed

Karaoglu, Sezer; Tao, Ran; van Gemert, Jan C; Gevers, Theo

2017-05-24

This work focuses on fine-grained object classification using recognized scene text in natural images. While the state-of-the-art relies on visual cues only, this paper is the first work which proposes to combine textual and visual cues. Another novelty is the textual cue extraction. Unlike the state-of-the-art text detection methods, we focus more on the background instead of text regions. Once text regions are detected, they are further processed by two methods to perform text recognition i.e. ABBYY commercial OCR engine and a state-of-the-art character recognition algorithm. Then, to perform textual cue encoding, bi- and trigrams are formed between the recognized characters by considering the proposed spatial pairwise constraints. Finally, extracted visual and textual cues are combined for fine-grained classification. The proposed method is validated on four publicly available datasets: ICDAR03, ICDAR13, Con-Text and Flickr-logo. We improve the state-of-the-art end-to-end character recognition by a large margin of 15% on ICDAR03. We show that textual cues are useful in addition to visual cues for fine-grained classification. We show that textual cues are also useful for logo retrieval. Adding textual cues outperforms visual- and textual-only in fine-grained classification (70.7% to 60.3%) and logo retrieval (57.4% to 54.8%).

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

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.

Localizing text in scene images by boundary clustering, stroke segmentation, and string fragment classification.

PubMed

Yi, Chucai; Tian, Yingli

2012-09-01

In this paper, we propose a novel framework to extract text regions from scene images with complex backgrounds and multiple text appearances. This framework consists of three main steps: boundary clustering (BC), stroke segmentation, and string fragment classification. In BC, we propose a new bigram-color-uniformity-based method to model both text and attachment surface, and cluster edge pixels based on color pairs and spatial positions into boundary layers. Then, stroke segmentation is performed at each boundary layer by color assignment to extract character candidates. We propose two algorithms to combine the structural analysis of text stroke with color assignment and filter out background interferences. Further, we design a robust string fragment classification based on Gabor-based text features. The features are obtained from feature maps of gradient, stroke distribution, and stroke width. The proposed framework of text localization is evaluated on scene images, born-digital images, broadcast video images, and images of handheld objects captured by blind persons. Experimental results on respective datasets demonstrate that the framework outperforms state-of-the-art localization algorithms.

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

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

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.

The role of iconic memory in change-detection tasks.

PubMed

Becker, M W; Pashler, H; Anstis, S M

2000-01-01

In three experiments, subjects attempted to detect the change of a single item in a visually presented array of items. Subjects' ability to detect a change was greatly reduced if a blank interstimulus interval (ISI) was inserted between the original array and an array in which one item had changed ('change blindness'). However, change detection improved when the location of the change was cued during the blank ISI. This suggests that people represent more information of a scene than change blindness might suggest. We test two possible hypotheses why, in the absence of a cue, this representation fails to produce good change detection. The first claims that the intervening events employed to create change blindness result in multiple neural transients which co-occur with the to-be-detected change. Poor detection rates occur because a serial search of all the transient locations is required to detect the change, during which time the representation of the original scene fades. The second claims that the occurrence of the second frame overwrites the representation of the first frame, unless that information is insulated against overwriting by attention. The results support the second hypothesis. We conclude that people may have a fairly rich visual representation of a scene while the scene is present, but fail to detect changes because they lack the ability to simultaneously represent two complete visual representations.

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).

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.

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

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.

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.

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…

A Dual-Process Account of Auditory Change Detection

ERIC Educational Resources Information Center

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

2010-01-01

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…

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.

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.

Change detection in urban and rural driving scenes: Effects of target type and safety relevance on change blindness.

PubMed

Beanland, Vanessa; Filtness, Ashleigh J; Jeans, Rhiannon

2017-03-01

The ability to detect changes is crucial for safe driving. Previous research has demonstrated that drivers often experience change blindness, which refers to failed or delayed change detection. The current study explored how susceptibility to change blindness varies as a function of the driving environment, type of object changed, and safety relevance of the change. Twenty-six fully-licenced drivers completed a driving-related change detection task. Changes occurred to seven target objects (road signs, cars, motorcycles, traffic lights, pedestrians, animals, or roadside trees) across two environments (urban or rural). The contextual safety relevance of the change was systematically manipulated within each object category, ranging from high safety relevance (i.e., requiring a response by the driver) to low safety relevance (i.e., requiring no response). When viewing rural scenes, compared with urban scenes, participants were significantly faster and more accurate at detecting changes, and were less susceptible to "looked-but-failed-to-see" errors. Interestingly, safety relevance of the change differentially affected performance in urban and rural environments. In urban scenes, participants were more efficient at detecting changes with higher safety relevance, whereas in rural scenes the effect of safety relevance has marginal to no effect on change detection. Finally, even after accounting for safety relevance, change blindness varied significantly between target types. Overall the results suggest that drivers are less susceptible to change blindness for objects that are likely to change or move (e.g., traffic lights vs. road signs), and for moving objects that pose greater danger (e.g., wild animals vs. pedestrians). Copyright © 2017 Elsevier Ltd. All rights reserved.

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.

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.

Web pages: What can you see in a single fixation?

PubMed

Jahanian, Ali; Keshvari, Shaiyan; Rosenholtz, Ruth

2018-01-01

Research in human vision suggests that in a single fixation, humans can extract a significant amount of information from a natural scene, e.g. the semantic category, spatial layout, and object identities. This ability is useful, for example, for quickly determining location, navigating around obstacles, detecting threats, and guiding eye movements to gather more information. In this paper, we ask a new question: What can we see at a glance at a web page - an artificial yet complex "real world" stimulus? Is it possible to notice the type of website, or where the relevant elements are, with only a glimpse? We find that observers, fixating at the center of a web page shown for only 120 milliseconds, are well above chance at classifying the page into one of ten categories. Furthermore, this ability is supported in part by text that they can read at a glance. Users can also understand the spatial layout well enough to reliably localize the menu bar and to detect ads, even though the latter are often camouflaged among other graphical elements. We discuss the parallels between web page gist and scene gist, and the implications of our findings for both vision science and human-computer interaction.

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…

Common and Innovative Visuals: A sparsity modeling framework for video.

PubMed

Abdolhosseini Moghadam, Abdolreza; Kumar, Mrityunjay; Radha, Hayder

2014-05-02

Efficient video representation models are critical for many video analysis and processing tasks. In this paper, we present a framework based on the concept of finding the sparsest solution to model video frames. To model the spatio-temporal information, frames from one scene are decomposed into two components: (i) a common frame, which describes the visual information common to all the frames in the scene/segment, and (ii) a set of innovative frames, which depicts the dynamic behaviour of the scene. The proposed approach exploits and builds on recent results in the field of compressed sensing to jointly estimate the common frame and the innovative frames for each video segment. We refer to the proposed modeling framework by CIV (Common and Innovative Visuals). We show how the proposed model can be utilized to find scene change boundaries and extend CIV to videos from multiple scenes. Furthermore, the proposed model is robust to noise and can be used for various video processing applications without relying on motion estimation and detection or image segmentation. Results for object tracking, video editing (object removal, inpainting) and scene change detection are presented to demonstrate the efficiency and the performance of the proposed model.

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.

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.

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.

Gaze patterns reveal how situation models and text representations contribute to episodic text memory.

PubMed

Johansson, Roger; Oren, Franziska; Holmqvist, Kenneth

2018-06-01

When recalling something you have previously read, to what degree will such episodic remembering activate a situation model of described events versus a memory representation of the text itself? The present study was designed to address this question by recording eye movements of participants who recalled previously read texts while looking at a blank screen. An accumulating body of research has demonstrated that spontaneous eye movements occur during episodic memory retrieval and that fixation locations from such gaze patterns to a large degree overlap with the visuospatial layout of the recalled information. Here we used this phenomenon to investigate to what degree participants' gaze patterns corresponded with the visuospatial configuration of the text itself versus a visuospatial configuration described in it. The texts to be recalled were scene descriptions, where the spatial configuration of the scene content was manipulated to be either congruent or incongruent with the spatial configuration of the text itself. Results show that participants' gaze patterns were more likely to correspond with a visuospatial representation of the described scene than with a visuospatial representation of the text itself, but also that the contribution of those representations of space is sensitive to the text content. This is the first demonstration that eye movements can be used to discriminate on which representational level texts are remembered and the findings provide novel insight into the underlying dynamics in play. Copyright © 2018 Elsevier B.V. All rights reserved.

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.

Recognising the forest, but not the trees: an effect of colour on scene perception and recognition.

PubMed

Nijboer, Tanja C W; Kanai, Ryota; de Haan, Edward H F; van der Smagt, Maarten J

2008-09-01

Colour has been shown to facilitate the recognition of scene images, but only when these images contain natural scenes, for which colour is 'diagnostic'. Here we investigate whether colour can also facilitate memory for scene images, and whether this would hold for natural scenes in particular. In the first experiment participants first studied a set of colour and greyscale natural and man-made scene images. Next, the same images were presented, randomly mixed with a different set. Participants were asked to indicate whether they had seen the images during the study phase. Surprisingly, performance was better for greyscale than for coloured images, and this difference is due to the higher false alarm rate for both natural and man-made coloured scenes. We hypothesized that this increase in false alarm rate was due to a shift from scrutinizing details of the image to recognition of the gist of the (coloured) image. A second experiment, utilizing images without a nameable gist, confirmed this hypothesis as participants now performed equally on greyscale and coloured images. In the final experiment we specifically targeted the more detail-based perception and recognition for greyscale images versus the more gist-based perception and recognition for coloured images with a change detection paradigm. The results show that changes to images are detected faster when image-pairs were presented in greyscale than in colour. This counterintuitive result held for both natural and man-made scenes (but not for scenes without nameable gist) and thus corroborates the shift from more detailed processing of images in greyscale to more gist-based processing of coloured images.

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.

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

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.

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).

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.

A maximally stable extremal region based scene text localization method

NASA Astrophysics Data System (ADS)

Xiao, Chengqiu; Ji, Lixin; Gao, Chao; Li, Shaomei

2015-07-01

Text localization in natural scene images is an important prerequisite for many content-based image analysis tasks. This paper proposes a novel text localization algorithm. Firstly, a fast pruning algorithm is designed to extract Maximally Stable Extremal Regions (MSER) as basic character candidates. Secondly, these candidates are filtered by using the properties of fitting ellipse and the distribution properties of characters to exclude most non-characters. Finally, a new extremal regions projection merging algorithm is designed to group character candidates into words. Experimental results show that the proposed method has an advantage in speed and achieve relatively high precision and recall rates than the latest published algorithms.

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.

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

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.

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

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.

Autonomous detection of indoor and outdoor signs

NASA Astrophysics Data System (ADS)

Holden, Steven; Snorrason, Magnus; Goodsell, Thomas; Stevens, Mark R.

2005-05-01

Most goal-oriented mobile robot tasks involve navigation to one or more known locations. This is generally done using GPS coordinates and landmarks outdoors, or wall-following and fiducial marks indoors. Such approaches ignore the rich source of navigation information that is already in place for human navigation in all man-made environments: signs. A mobile robot capable of detecting and reading arbitrary signs could be tasked using directions that are intuitive to hu-mans, and it could report its location relative to intuitive landmarks (a street corner, a person's office, etc.). Such ability would not require active marking of the environment and would be functional in the absence of GPS. In this paper we present an updated version of a system we call Sign Understanding in Support of Autonomous Navigation (SUSAN). This system relies on cues common to most signs, the presence of text, vivid color, and compact shape. By not relying on templates, SUSAN can detect a wide variety of signs: traffic signs, street signs, store-name signs, building directories, room signs, etc. In this paper we focus on the text detection capability. We present results summarizing probability of detection and false alarm rate across many scenes containing signs of very different designs and in a variety of lighting conditions.

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.

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.

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.

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.

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.

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.

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.

ESARR: enhanced situational awareness via road sign recognition

NASA Astrophysics Data System (ADS)

Perlin, V. E.; Johnson, D. B.; Rohde, M. M.; Lupa, R. M.; Fiorani, G.; Mohammad, S.

2010-04-01

The enhanced situational awareness via road sign recognition (ESARR) system provides vehicle position estimates in the absence of GPS signal via automated processing of roadway fiducials (primarily directional road signs). Sign images are detected and extracted from vehicle-mounted camera system, and preprocessed and read via a custom optical character recognition (OCR) system specifically designed to cope with low quality input imagery. Vehicle motion and 3D scene geometry estimation enables efficient and robust sign detection with low false alarm rates. Multi-level text processing coupled with GIS database validation enables effective interpretation even of extremely low resolution low contrast sign images. In this paper, ESARR development progress will be reported on, including the design and architecture, image processing framework, localization methodologies, and results to date. Highlights of the real-time vehicle-based directional road-sign detection and interpretation system will be described along with the challenges and progress in overcoming them.

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?

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…

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.

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.

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

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.

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.

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.

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.

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.

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.

Fusion and Sense Making of Heterogeneous Sensor Network and Other Sources

DTIC Science & Technology

2017-03-16

multimodal fusion framework that uses both training data and web resources for scene classification, the experimental results on the benchmark datasets...show that the proposed text-aided scene classification framework could significantly improve classification performance. Experimental results also show...human whose adaptability is achieved by reliability- dependent weighting of different sensory modalities. Experimental results show that the proposed

Experiencing "Macbeth": From Text Rendering to Multicultural Performance.

ERIC Educational Resources Information Center

Reisin, Gail

1993-01-01

Shows how one teacher used innovative methods in teaching William Shakespeare's "Macbeth." Outlines student assignments including text renderings, rewriting a scene from the play, and creating a multicultural scrapbook for the play. (HB)

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.

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.

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.

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.

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.

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.

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

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.

Scene Text Recognition using Similarity and a Lexicon with Sparse Belief Propagation

PubMed Central

Weinman, Jerod J.; Learned-Miller, Erik; Hanson, Allen R.

2010-01-01

Scene text recognition (STR) is the recognition of text anywhere in the environment, such as signs and store fronts. Relative to document recognition, it is challenging because of font variability, minimal language context, and uncontrolled conditions. Much information available to solve this problem is frequently ignored or used sequentially. Similarity between character images is often overlooked as useful information. Because of language priors, a recognizer may assign different labels to identical characters. Directly comparing characters to each other, rather than only a model, helps ensure that similar instances receive the same label. Lexicons improve recognition accuracy but are used post hoc. We introduce a probabilistic model for STR that integrates similarity, language properties, and lexical decision. Inference is accelerated with sparse belief propagation, a bottom-up method for shortening messages by reducing the dependency between weakly supported hypotheses. By fusing information sources in one model, we eliminate unrecoverable errors that result from sequential processing, improving accuracy. In experimental results recognizing text from images of signs in outdoor scenes, incorporating similarity reduces character recognition error by 19%, the lexicon reduces word recognition error by 35%, and sparse belief propagation reduces the lexicon words considered by 99.9% with a 12X speedup and no loss in accuracy. PMID:19696446

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.

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.

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 .

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.

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.

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.

Where to Be or Not to Be: The Question of Place in "Hamlet"

ERIC Educational Resources Information Center

Golden, John

2009-01-01

The author does not really like "Hamlet." He loves the play, the language, and the characters, but always finds it difficult to teach. Part of this is because he prefers to assign students scenes to perform as they read a Shakespeare text, but Hamlet does not divide nicely into manageable scenes, and he usually does not have enough teenage Ken…

Kepler Planet Reliability Metrics: Astrophysical Positional Probabilities for Data Release 25

NASA Technical Reports Server (NTRS)

Bryson, Stephen T.; Morton, Timothy D.

2017-01-01

This document is very similar to KSCI-19092-003, Planet Reliability Metrics: Astrophysical Positional Probabilities, which describes the previous release of the astrophysical positional probabilities for Data Release 24. The important changes for Data Release 25 are:1. The computation of the astrophysical positional probabilities uses the Data Release 25 processed pixel data for all Kepler Objects of Interest.2. Computed probabilities now have associated uncertainties, whose computation is described in x4.1.3.3. The scene modeling described in x4.1.2 uses background stars detected via ground-based high-resolution imaging, described in x5.1, that are not in the Kepler Input Catalog or UKIRT catalog. These newly detected stars are presented in Appendix B. Otherwise the text describing the algorithms and examples is largely unchanged from KSCI-19092-003.

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

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 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

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.

Identifying sports videos using replay, text, and camera motion features

NASA Astrophysics Data System (ADS)

Kobla, Vikrant; DeMenthon, Daniel; Doermann, David S.

1999-12-01

Automated classification of digital video is emerging as an important piece of the puzzle in the design of content management systems for digital libraries. The ability to classify videos into various classes such as sports, news, movies, or documentaries, increases the efficiency of indexing, browsing, and retrieval of video in large databases. In this paper, we discuss the extraction of features that enable identification of sports videos directly from the compressed domain of MPEG video. These features include detecting the presence of action replays, determining the amount of scene text in vide, and calculating various statistics on camera and/or object motion. The features are derived from the macroblock, motion,and bit-rate information that is readily accessible from MPEG video with very minimal decoding, leading to substantial gains in processing speeds. Full-decoding of selective frames is required only for text analysis. A decision tree classifier built using these features is able to identify sports clips with an accuracy of about 93 percent.

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.

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.

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.

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…

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…

Color Variations on Mount Sharp, Mars White Balanced

NASA Image and Video Library

2016-12-13

The foreground of this scene from the Mast Camera (Mastcam) on NASA's Curiosity Mars rover shows purple-hued rocks near the rover's late-2016 location on lower Mount Sharp. The scene's middle distance includes higher layers that are future destinations for the mission. Variations in color of the rocks hint at the diversity of their composition on lower Mount Sharp. The purple tone of the foreground rocks has been seen in other rocks where Curiosity's Chemical and Mineralogy (CheMin) instrument has detected hematite. Winds and windblown sand in this part of Curiosity's traverse and in this season tend to keep rocks relatively free of dust, which otherwise can cloak rocks' color. The three frames combined into this mosaic were acquired by the Mastcam's right-eye camera on Nov. 10, 2016, during the 1,516th Martian day, or sol, of Curiosity's work on Mars. The scene is presented with a color adjustment that approximates white balancing, to resemble how the rocks and sand would appear under daytime lighting conditions on Earth. Sunlight on Mars is tinged by the dusty atmosphere and this adjustment helps geologists recognize color patterns they are familiar with on Earth. The view spans about 15 compass degrees, with the left edge toward southeast. The rover's planned direction of travel from its location when this scene was recorded is generally southeastward. The orange-looking rocks just above the purplish foreground ones are in the upper portion of the Murray formation, which is the basal section of Mount Sharp, extending up to a ridge-forming layer called the Hematite Unit. Beyond that is the Clay Unit, which is relatively flat and hard to see from this viewpoint. The next rounded hills are the Sulfate Unit, Curiosity's highest planned destination. The most distant slopes in the scene are higher levels of Mount Sharp, beyond where Curiosity will drive. Figure 1 is a version of the same scene with annotations added as reference points for distance, size and relative elevation. The annotations are triangles with text telling the distance (in kilometers) to the point in the image marked by the triangle, the point's elevation (in meters) relative to the rover's location, and the size (in meters) of an object as big as the triangle at that distance. An annotated figure is available at http://photojournal.jpl.nasa.gov/catalog/PIA21256

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.

From Image Analysis to Computer Vision: Motives, Methods, and Milestones.

DTIC Science & Technology

1998-07-01

images. Initially, work on digital image analysis dealt with specific classes of images such as text, photomicrographs, nuclear particle tracks, and aerial...photographs; but by the 1960’s, general algorithms and paradigms for image analysis began to be formulated. When the artificial intelligence...scene, but eventually from image sequences obtained by a moving camera; at this stage, image analysis had become scene analysis or computer vision

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.

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.

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/ .

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

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.

In the eye of the beholder: A simulator study of the impact of Google Glass on driving performance.

PubMed

Young, Kristie L; Stephens, Amanda N; Stephan, Karen L; Stuart, Geoffrey W

2016-01-01

This study examined whether, and to what extent, driving is affected by reading text on Google Glass. Reading text requires a high level of visual resources and can interfere with safe driving. However, it is currently unclear if the impact of reading text on a head-mounted display, such as Google Glass (Glass), will differ from that found with more traditional head-down electronic devices, such as a dash-mounted smartphone. A total of 20 drivers (22-48 years) completed the Lane Change Test while driving undistracted and while reading text on Glass and on a smartphone. Measures of lateral vehicle control and event detection were examined along with subjective workload and secondary task performance. Results revealed that drivers' lane keeping ability was significantly impaired by reading text on both Glass and the smartphone. When using Glass, drivers also failed to detect a greater number of lane change signs compared to when using the phone or driving undistracted. In terms of subjective workload, drivers rated reading on Glass as subjectively easier than on the smartphone, which may possibly encourage greater use of this device while driving. Overall, the results suggest that, despite Glass allowing drivers to better maintain their visual attention on the forward scene, drivers are still not able to effectively divide their cognitive attention across the Glass display and the road environment, resulting in impaired driving performance. Copyright © 2015 Elsevier Ltd. All rights reserved.

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.

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…

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.

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.

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

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.

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.

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.

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.

[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.

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).

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

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.

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%.

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.

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

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…

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.

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.

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.

Generating descriptive visual words and visual phrases for large-scale image applications.

PubMed

Zhang, Shiliang; Tian, Qi; Hua, Gang; Huang, Qingming; Gao, Wen

2011-09-01

Bag-of-visual Words (BoWs) representation has been applied for various problems in the fields of multimedia and computer vision. The basic idea is to represent images as visual documents composed of repeatable and distinctive visual elements, which are comparable to the text words. Notwithstanding its great success and wide adoption, visual vocabulary created from single-image local descriptors is often shown to be not as effective as desired. In this paper, descriptive visual words (DVWs) and descriptive visual phrases (DVPs) are proposed as the visual correspondences to text words and phrases, where visual phrases refer to the frequently co-occurring visual word pairs. Since images are the carriers of visual objects and scenes, a descriptive visual element set can be composed by the visual words and their combinations which are effective in representing certain visual objects or scenes. Based on this idea, a general framework is proposed for generating DVWs and DVPs for image applications. In a large-scale image database containing 1506 object and scene categories, the visual words and visual word pairs descriptive to certain objects or scenes are identified and collected as the DVWs and DVPs. Experiments show that the DVWs and DVPs are informative and descriptive and, thus, are more comparable with the text words than the classic visual words. We apply the identified DVWs and DVPs in several applications including large-scale near-duplicated image retrieval, image search re-ranking, and object recognition. The combination of DVW and DVP performs better than the state of the art in large-scale near-duplicated image retrieval in terms of accuracy, efficiency and memory consumption. The proposed image search re-ranking algorithm: DWPRank outperforms the state-of-the-art algorithm by 12.4% in mean average precision and about 11 times faster in efficiency.

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.

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.

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.

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.

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

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.

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 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

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.

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.

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.

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%.

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.

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.

Atmosphere-based image classification through luminance and hue

NASA Astrophysics Data System (ADS)

Xu, Feng; Zhang, Yujin

2005-07-01

In this paper a novel image classification system is proposed. Atmosphere serves an important role in generating the scene"s topic or in conveying the message behind the scene"s story, which belongs to abstract attribute level in semantic levels. At first, five atmosphere semantic categories are defined according to rules of photo and film grammar, followed by global luminance and hue features. Then the hierarchical SVM classifiers are applied. In each classification stage, corresponding features are extracted and the trained linear SVM is implemented, resulting in two classes. After three stages of classification, five atmosphere categories are obtained. At last, the text annotation of the atmosphere semantics and the corresponding features by Extensible Markup Language (XML) in MPEG-7 is defined, which can be integrated into more multimedia applications (such as searching, indexing and accessing of multimedia content). The experiment is performed on Corel images and film frames. The classification results prove the effectiveness of the definition of atmosphere semantic classes and the corresponding features.

Aligning Where to See and What to Tell: Image Captioning with Region-Based Attention and Scene-Specific Contexts.

PubMed

Fu, Kun; Jin, Junqi; Cui, Runpeng; Sha, Fei; Zhang, Changshui

2017-12-01

Recent progress on automatic generation of image captions has shown that it is possible to describe the most salient information conveyed by images with accurate and meaningful sentences. In this paper, we propose an image captioning system that exploits the parallel structures between images and sentences. In our model, the process of generating the next word, given the previously generated ones, is aligned with the visual perception experience where the attention shifts among the visual regions-such transitions impose a thread of ordering in visual perception. This alignment characterizes the flow of latent meaning, which encodes what is semantically shared by both the visual scene and the text description. Our system also makes another novel modeling contribution by introducing scene-specific contexts that capture higher-level semantic information encoded in an image. The contexts adapt language models for word generation to specific scene types. We benchmark our system and contrast to published results on several popular datasets, using both automatic evaluation metrics and human evaluation. We show that either region-based attention or scene-specific contexts improves systems without those components. Furthermore, combining these two modeling ingredients attains the state-of-the-art performance.

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

Sci-Vis Framework

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

Arthur Bleeker, PNNL

2015-03-11

SVF is a full featured OpenGL 3d framework that allows for rapid creation of complex visualizations. The SVF framework handles much of the lifecycle and complex tasks required for a 3d visualization. Unlike a game framework SVF was designed to use fewer resources, work well in a windowed environment, and only render when necessary. The scene also takes advantage of multiple threads to free up the UI thread as much as possible. Shapes (actors) in the scene are created by adding or removing functionality (through support objects) during runtime. This allows a highly flexible and dynamic means of creating highlymore » complex actors without the code complexity (it also helps overcome the lack of multiple inheritance in Java.) All classes are highly customizable and there are abstract classes which are intended to be subclassed to allow a developer to create more complex and highly performant actors. There are multiple demos included in the framework to help the developer get started and shows off nearly all of the functionality. Some simple shapes (actors) are already created for you such as text, bordered text, radial text, text area, complex paths, NURBS paths, cube, disk, grid, plane, geometric shapes, and volumetric area. It also comes with various camera types for viewing that can be dragged, zoomed, and rotated. Picking or selecting items in the scene can be accomplished in various ways depending on your needs (raycasting or color picking.) The framework currently has functionality for tooltips, animation, actor pools, color gradients, 2d physics, text, 1d/2d/3d textures, children, blending, clipping planes, view frustum culling, custom shaders, and custom actor states« less

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.

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.

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

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.

Background Characterization Techniques For Pattern Recognition Applications

NASA Astrophysics Data System (ADS)

Noah, Meg A.; Noah, Paul V.; Schroeder, John W.; Kessler, Bernard V.; Chernick, Julian A.

1989-08-01

The Department of Defense has a requirement to investigate technologies for the detection of air and ground vehicles in a clutter environment. The use of autonomous systems using infrared, visible, and millimeter wave detectors has the potential to meet DOD's needs. In general, however, the hard-ware technology (large detector arrays with high sensitivity) has outpaced the development of processing techniques and software. In a complex background scene the "problem" is as much one of clutter rejection as it is target detection. The work described in this paper has investigated a new, and innovative, methodology for background clutter characterization, target detection and target identification. The approach uses multivariate statistical analysis to evaluate a set of image metrics applied to infrared cloud imagery and terrain clutter scenes. The techniques are applied to two distinct problems: the characterization of atmospheric water vapor cloud scenes for the Navy's Infrared Search and Track (IRST) applications to support the Infrared Modeling Measurement and Analysis Program (IRAMMP); and the detection of ground vehicles for the Army's Autonomous Homing Munitions (AHM) problems. This work was sponsored under two separate Small Business Innovative Research (SBIR) programs by the Naval Surface Warfare Center (NSWC), White Oak MD, and the Army Material Systems Analysis Activity at Aberdeen Proving Ground MD. The software described in this paper will be available from the respective contract technical representatives.

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.

Automatic image orientation detection via confidence-based integration of low-level and semantic cues.

PubMed

Luo, Jiebo; Boutell, Matthew

2005-05-01

Automatic image orientation detection for natural images is a useful, yet challenging research topic. Humans use scene context and semantic object recognition to identify the correct image orientation. However, it is difficult for a computer to perform the task in the same way because current object recognition algorithms are extremely limited in their scope and robustness. As a result, existing orientation detection methods were built upon low-level vision features such as spatial distributions of color and texture. Discrepant detection rates have been reported for these methods in the literature. We have developed a probabilistic approach to image orientation detection via confidence-based integration of low-level and semantic cues within a Bayesian framework. Our current accuracy is 90 percent for unconstrained consumer photos, impressive given the findings of a psychophysical study conducted recently. The proposed framework is an attempt to bridge the gap between computer and human vision systems and is applicable to other problems involving semantic scene content understanding.

STS-40 crewmembers remove specimens from SLS-1 Rack 9 Refrigerator / Freezer

NASA Image and Video Library

1991-06-14

STS040-202-033 (5-14 June 1991) --- A medium closeup scene shows astronaut James P. Bagian (left) and an unidentified crewmember (partially out of frame) looking at a vacant refrigerator in the Spacelab Life Sciences (SLS-1) module aboard the Earth-orbiting Space Shuttle Columbia. Following the detection of problems with the refrigerator, its contents were temporarily removed. This scene was photographed with a 35mm camera.

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).

ASTER cloud coverage reassessment using MODIS cloud mask products

NASA Astrophysics Data System (ADS)

Tonooka, Hideyuki; Omagari, Kunjuro; Yamamoto, Hirokazu; Tachikawa, Tetsushi; Fujita, Masaru; Paitaer, Zaoreguli

2010-10-01

In the Advanced Spaceborne Thermal Emission and Reflection radiometer (ASTER) Project, two kinds of algorithms are used for cloud assessment in Level-1 processing. The first algorithm based on the LANDSAT-5 TM Automatic Cloud Cover Assessment (ACCA) algorithm is used for a part of daytime scenes observed with only VNIR bands and all nighttime scenes, and the second algorithm based on the LANDSAT-7 ETM+ ACCA algorithm is used for most of daytime scenes observed with all spectral bands. However, the first algorithm does not work well for lack of some spectral bands sensitive to cloud detection, and the two algorithms have been less accurate over snow/ice covered areas since April 2008 when the SWIR subsystem developed troubles. In addition, they perform less well for some combinations of surface type and sun elevation angle. We, therefore, have developed the ASTER cloud coverage reassessment system using MODIS cloud mask (MOD35) products, and have reassessed cloud coverage for all ASTER archived scenes (>1.7 million scenes). All of the new cloud coverage data are included in Image Management System (IMS) databases of the ASTER Ground Data System (GDS) and NASA's Land Process Data Active Archive Center (LP DAAC) and used for ASTER product search by users, and cloud mask images are distributed to users through Internet. Daily upcoming scenes (about 400 scenes per day) are reassessed and inserted into the IMS databases in 5 to 7 days after each scene observation date. Some validation studies for the new cloud coverage data and some mission-related analyses using those data are also demonstrated in the present paper.

Target detection in active polarization images perturbed with additive noise and illumination nonuniformity.

PubMed

Bénière, Arnaud; Goudail, François; Dolfi, Daniel; Alouini, Mehdi

2009-07-01

Active imaging systems that illuminate a scene with polarized light and acquire two images in two orthogonal polarizations yield information about the intensity contrast and the orthogonal state contrast (OSC) in the scene. Both contrasts are relevant for target detection. However, in real systems, the illumination is often spatially or temporally nonuniform. This creates artificial intensity contrasts that can lead to false alarms. We derive generalized likelihood ratio test (GLRT) detectors, for which intensity information is taken into account or not and determine the relevant expressions of the contrast in these two situations. These results are used to determine in which cases considering intensity information in addition to polarimetric information is relevant or not.

Constructing "Macbeth": Text and Framing in a Secondary Urban Classroom

ERIC Educational Resources Information Center

Cantwell, Joanna

2014-01-01

This study focuses on a secondary English classroom in an East London school, and the multimodal nature of the students' construction of the literary heritage text Macbeth, specifically in their dramatic reinterpretation of Act 1, Scene 7, where Lady Macbeth persuades "Macbeth" to pursue his ambitions and kill the current king, Duncan.…

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.

People detection in crowded scenes using active contour models

NASA Astrophysics Data System (ADS)

Sidla, Oliver

2009-01-01

The detection of pedestrians in real-world scenes is a daunting task, especially in crowded situations. Our experience over the last years has shown that active shape models (ASM) can contribute significantly to a robust pedestrian detection system. The paper starts with an overview of shape model approaches, it then explains our approach which builds on top of Eigenshape models which have been trained using real-world data. These models are placed over candidate regions and matched to image gradients using a scoring function which integrates i) point distribution, ii) local gradient orientations iii) local image gradient strengths. A matching and shape model update process is iteratively applied in order to fit the flexible models to the local image content. The weights of the scoring function have a significant impact on the ASM performance. We analyze different settings of scoring weights for gradient magnitude, relative orientation differences, distance between model and gradient in an experiment which uses real-world data. Although for only one pedestrian model in an image computation time is low, the number of necessary processing cycles which is needed to track many people in crowded scenes can become the bottleneck in a real-time application. We describe the measures which have been taken in order to improve the speed of the ASM implementation and make it real-time capable.

A Comparison of Detection and Tracking Methods as Applied to OPIR Optics

DTIC Science & Technology

2014-12-01

foreground % images. The function requires you to input the scenes in vector format % as well as the window size, w. You can also set the variable...2,ii)) hold on end %% Build Scene A_org = A; % Format track data add variance, variance not included here...Kopp, “High energy laser directed energy weapons,” APA , Tech. Rep. APA - TR-2008–0501, Air Power Australia, Apr. 2012. [5] High-energy laser. (n.d

Figure ground discrimination in age-related macular degeneration.

PubMed

Tran, Thi Ha Chau; Guyader, Nathalie; Guerin, Anne; Despretz, Pascal; Boucart, Muriel

2011-03-01

To investigate impairment in discriminating a figure from its background and to study its relation to visual acuity and lesion size in patients with neovascular age-related macular degeneration (AMD). Seventeen patients with neovascular AMD and visual acuity <20/50 were included. Seventeen age-matched healthy subjects participated as controls. Complete ophthalmologic examination was performed on all participants. The stimuli were photographs of scenes containing animals (targets) or other objects (distractors), displayed on a computer monitor screen. Performance was compared in four background conditions: the target in the natural scene; the target isolated on a white background; the target separated by a white space from a structured scene; the target separated by a white space from a nonstructured, shapeless background. Target discriminability (d') was recorded. Performance was lower for patients than for controls. For the patients, it was easier to detect the target when it was separated from its background (under isolated, structured, and nonstructured conditions) than it was when located in a scene. Performance was improved in patients with increasing exposure time but remained lower in controls. Correlations were found between visual acuity, lesion size, and sensitivity for patients. Figure/ground segregation is impaired in patients with AMD. A white space surrounding an object is sufficient to improve the object's detection and to facilitate figure/ground segregation. These results may have practical applications to the rehabilitation of the environment in patients with AMD.

Hyperspectral and Hypertemporal Longwave Infrared Data Characterization

NASA Astrophysics Data System (ADS)

Jeganathan, Nirmalan

The Army Research Lab conducted a persistent imaging experiment called the Spectral and Polarimetric Imagery Collection Experiment (SPICE) in 2012 and 2013 which focused on collecting and exploiting long wave infrared hyperspectral and polarimetric imagery. A part of this dataset was made for public release for research and development purposes. This thesis investigated the hyperspectral portion of this released dataset through data characterization and scene characterization of man-made and natural objects. First, the data were contrasted with MODerate resolution atmospheric TRANsmission (MODTRAN) results and found to be comparable. Instrument noise was characterized using an in-scene black panel, and was found to be comparable with the sensor manufacturer's specication. The temporal and spatial variation of certain objects in the scene were characterized. Temporal target detection was conducted on man-made objects in the scene using three target detection algorithms: spectral angle mapper (SAM), spectral matched lter (SMF) and adaptive coherence/cosine estimator (ACE). SMF produced the best results for detecting the targets when the training and testing data originated from different time periods, with a time index percentage result of 52.9%. Unsupervised and supervised classification were conducted using spectral and temporal target signatures. Temporal target signatures produced better visual classification than spectral target signature for unsupervised classification. Supervised classification yielded better results using the spectral target signatures, with a highest weighted accuracy of 99% for 7-class reference image. Four emissivity retrieval algorithms were applied on this dataset. However, the retrieved emissivities from all four methods did not represent true material emissivity and could not be used for analysis. This spectrally and temporally rich dataset enabled to conduct analysis that was not possible with other data collections. Regarding future work, applying noise-reduction techniques before applying temperature-emissivity retrieval algorithms may produce more realistic emissivity values, which could be used for target detection and material identification.

Mid-infrared hyperspectral imaging for the detection of explosive compounds

NASA Astrophysics Data System (ADS)

Ruxton, K.; Robertson, G.; Miller, W.; Malcolm, G. P. A.; Maker, G. T.

2012-10-01

Active hyperspectral imaging is a valuable tool in a wide range of applications. A developing market is the detection and identification of energetic compounds through analysis of the resulting absorption spectrum. This work presents a selection of results from a prototype mid-infrared (MWIR) hyperspectral imaging instrument that has successfully been used for compound detection at a range of standoff distances. Active hyperspectral imaging utilises a broadly tunable laser source to illuminate the scene with light over a range of wavelengths. While there are a number of illumination methods, this work illuminates the scene by raster scanning the laser beam using a pair of galvanometric mirrors. The resulting backscattered light from the scene is collected by the same mirrors and directed and focussed onto a suitable single-point detector, where the image is constructed pixel by pixel. The imaging instrument that was developed in this work is based around a MWIR optical parametric oscillator (OPO) source with broad tunability, operating at 2.6 μm to 3.7 μm. Due to material handling procedures associated with explosive compounds, experimental work was undertaken initially using simulant compounds. A second set of compounds that was tested alongside the simulant compounds is a range of confusion compounds. By having the broad wavelength tunability of the OPO, extended absorption spectra of the compounds could be obtained to aid in compound identification. The prototype imager instrument has successfully been used to record the absorption spectra for a range of compounds from the simulant and confusion sets and current work is now investigating actual explosive compounds. The authors see a very promising outlook for the MWIR hyperspectral imager. From an applications point of view this format of imaging instrument could be used for a range of standoff, improvised explosive device (IED) detection applications and potential incident scene forensic investigation.

The what, where and how of auditory-object perception.

PubMed

Bizley, Jennifer K; Cohen, Yale E

2013-10-01

The fundamental perceptual unit in hearing is the 'auditory object'. Similar to visual objects, auditory objects are the computational result of the auditory system's capacity to detect, extract, segregate and group spectrotemporal regularities in the acoustic environment; the multitude of acoustic stimuli around us together form the auditory scene. However, unlike the visual scene, resolving the component objects within the auditory scene crucially depends on their temporal structure. Neural correlates of auditory objects are found throughout the auditory system. However, neural responses do not become correlated with a listener's perceptual reports until the level of the cortex. The roles of different neural structures and the contribution of different cognitive states to the perception of auditory objects are not yet fully understood.

The what, where and how of auditory-object perception

PubMed Central

Bizley, Jennifer K.; Cohen, Yale E.

2014-01-01

The fundamental perceptual unit in hearing is the ‘auditory object’. Similar to visual objects, auditory objects are the computational result of the auditory system's capacity to detect, extract, segregate and group spectrotemporal regularities in the acoustic environment; the multitude of acoustic stimuli around us together form the auditory scene. However, unlike the visual scene, resolving the component objects within the auditory scene crucially depends on their temporal structure. Neural correlates of auditory objects are found throughout the auditory system. However, neural responses do not become correlated with a listener's perceptual reports until the level of the cortex. The roles of different neural structures and the contribution of different cognitive states to the perception of auditory objects are not yet fully understood. PMID:24052177

Intensity dependent spread theory

NASA Technical Reports Server (NTRS)

Holben, Richard

1990-01-01

The Intensity Dependent Spread (IDS) procedure is an image-processing technique based on a model of the processing which occurs in the human visual system. IDS processing is relevant to many aspects of machine vision and image processing. For quantum limited images, it produces an ideal trade-off between spatial resolution and noise averaging, performs edge enhancement thus requiring only mean-crossing detection for the subsequent extraction of scene edges, and yields edge responses whose amplitudes are independent of scene illumination, depending only upon the ratio of the reflectance on the two sides of the edge. These properties suggest that the IDS process may provide significant bandwidth reduction while losing only minimal scene information when used as a preprocessor at or near the image plane.

Generating Text from Functional Brain Images

PubMed Central

Pereira, Francisco; Detre, Greg; Botvinick, Matthew

2011-01-01

Recent work has shown that it is possible to take brain images acquired during viewing of a scene and reconstruct an approximation of the scene from those images. Here we show that it is also possible to generate text about the mental content reflected in brain images. We began with images collected as participants read names of concrete items (e.g., “Apartment’’) while also seeing line drawings of the item named. We built a model of the mental semantic representation of concrete concepts from text data and learned to map aspects of such representation to patterns of activation in the corresponding brain image. In order to validate this mapping, without accessing information about the items viewed for left-out individual brain images, we were able to generate from each one a collection of semantically pertinent words (e.g., “door,” “window” for “Apartment’’). Furthermore, we show that the ability to generate such words allows us to perform a classification task and thus validate our method quantitatively. PMID:21927602

Key features for ATA / ATR database design in missile systems

NASA Astrophysics Data System (ADS)

Özertem, Kemal Arda

2017-05-01

Automatic target acquisition (ATA) and automatic target recognition (ATR) are two vital tasks for missile systems, and having a robust detection and recognition algorithm is crucial for overall system performance. In order to have a robust target detection and recognition algorithm, an extensive image database is required. Automatic target recognition algorithms use the database of images in training and testing steps of algorithm. This directly affects the recognition performance, since the training accuracy is driven by the quality of the image database. In addition, the performance of an automatic target detection algorithm can be measured effectively by using an image database. There are two main ways for designing an ATA / ATR database. The first and easy way is by using a scene generator. A scene generator can model the objects by considering its material information, the atmospheric conditions, detector type and the territory. Designing image database by using a scene generator is inexpensive and it allows creating many different scenarios quickly and easily. However the major drawback of using a scene generator is its low fidelity, since the images are created virtually. The second and difficult way is designing it using real-world images. Designing image database with real-world images is a lot more costly and time consuming; however it offers high fidelity, which is critical for missile algorithms. In this paper, critical concepts in ATA / ATR database design with real-world images are discussed. Each concept is discussed in the perspective of ATA and ATR separately. For the implementation stage, some possible solutions and trade-offs for creating the database are proposed, and all proposed approaches are compared to each other with regards to their pros and cons.

Scene-based nonuniformity correction for airborne point target detection systems.

PubMed

Zhou, Dabiao; Wang, Dejiang; Huo, Lijun; Liu, Rang; Jia, Ping

2017-06-26

Images acquired by airborne infrared search and track (IRST) systems are often characterized by nonuniform noise. In this paper, a scene-based nonuniformity correction method for infrared focal-plane arrays (FPAs) is proposed based on the constant statistics of the received radiation ratios of adjacent pixels. The gain of each pixel is computed recursively based on the ratios between adjacent pixels, which are estimated through a median operation. Then, an elaborate mathematical model describing the error propagation, derived from random noise and the recursive calculation procedure, is established. The proposed method maintains the characteristics of traditional methods in calibrating the whole electro-optics chain, in compensating for temporal drifts, and in not preserving the radiometric accuracy of the system. Moreover, the proposed method is robust since the frame number is the only variant, and is suitable for real-time applications owing to its low computational complexity and simplicity of implementation. The experimental results, on different scenes from a proof-of-concept point target detection system with a long-wave Sofradir FPA, demonstrate the compelling performance of the proposed method.

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.

Robust fusion-based processing for military polarimetric imaging systems

NASA Astrophysics Data System (ADS)

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

2017-05-01

Polarisation information within a scene can be exploited in military systems to give enhanced automatic target detection and recognition (ATD/R) performance. However, the performance gain achieved is highly dependent on factors such as the geometry, viewing conditions, and the surface finish of the target. Such performance sensitivities are highly undesirable in many tactical military systems where operational conditions can vary significantly and rapidly during a mission. Within this paper, a range of processing architectures and fusion methods is considered in terms of their practical viability and operational robustness for systems requiring ATD/R. It is shown that polarisation information can give useful performance gains but, to retained system robustness, the introduction of polarimetric processing should be done in such a way as to not compromise other discriminatory scene information in the spectral and spatial domains. The analysis concludes that polarimetric data can be effectively integrated with conventional intensity-based ATD/R by either adapting the ATD/R processing function based on the scene polarisation or else by detection-level fusion. Both of these approaches avoid the introduction of processing bottlenecks and limit the impact of processing on system latency.

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.

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).

How attentional boost interacts with reward: the effect of dopaminergic medications in Parkinson's disease.

PubMed

Kéri, Szabolcs; Nagy, Helga; Levy-Gigi, Einat; Kelemen, Oguz

2013-12-01

There is widespread evidence that dopamine is implicated in the regulation of reward and salience. However, it is less known how these processes interact with attention and recognition memory. To explore this question, we used the attentional boost test in patients with Parkinson's disease (PD) before and after the administration of dopaminergic medications. Participants performed a visual letter detection task (remembering rewarded target letters and ignoring distractor letters) while also viewing a series of photos of natural and urban scenes in the background of the letters. The aim of the game was to retrieve the target letter after each trial and to win as much virtual money as possible. The recognition of background scenes was not rewarded. We enrolled 26 drug-naïve, newly diagnosed patients with PD and 25 healthy controls who were evaluated at baseline and follow-up. Patients with PD received dopamine agonists (pramipexole, ropinirole, rotigotine) during the 12-week follow-up period. At baseline, we found intact attentional boost in patients with PD: they were able to recognize target-associated scenes similarly to controls. At follow-up, patients with PD outperformed controls for both target- and distractor-associated scenes, but not when scenes were presented without letters. The alerting, orienting and executive components of attention were intact in PD. Enhanced attentional boost was replicated in a smaller group of patients with PD (n = 15) receiving l-3,4-dihydroxyphenylalanine (L-DOPA). These results suggest that dopaminergic medications facilitate attentional boost for background information regardless of whether the central task (letter detection) is rewarded or not. © 2013 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Hyperspectral target detection using heavy-tailed distributions

NASA Astrophysics Data System (ADS)

Willis, Chris J.

2009-09-01

One promising approach to target detection in hyperspectral imagery exploits a statistical mixture model to represent scene content at a pixel level. The process then goes on to look for pixels which are rare, when judged against the model, and marks them as anomalies. It is assumed that military targets will themselves be rare and therefore likely to be detected amongst these anomalies. For the typical assumption of multivariate Gaussianity for the mixture components, the presence of the anomalous pixels within the training data will have a deleterious effect on the quality of the model. In particular, the derivation process itself is adversely affected by the attempt to accommodate the anomalies within the mixture components. This will bias the statistics of at least some of the components away from their true values and towards the anomalies. In many cases this will result in a reduction in the detection performance and an increased false alarm rate. This paper considers the use of heavy-tailed statistical distributions within the mixture model. Such distributions are better able to account for anomalies in the training data within the tails of their distributions, and the balance of the pixels within their central masses. This means that an improved model of the majority of the pixels in the scene may be produced, ultimately leading to a better anomaly detection result. The anomaly detection techniques are examined using both synthetic data and hyperspectral imagery with injected anomalous pixels. A range of results is presented for the baseline Gaussian mixture model and for models accommodating heavy-tailed distributions, for different parameterizations of the algorithms. These include scene understanding results, anomalous pixel maps at given significance levels and Receiver Operating Characteristic curves.

"Where Lies Your Text?" ("Twelfth Night" Act I, Scene V): Engaging High School Students from Low Socioeconomic Backgrounds in Reading Multimodal Texts

ERIC Educational Resources Information Center

Callow, Jon; Zammit, Katina

2012-01-01

From the original performances of Shakespeare's plays and the illustrated title page of his First Folios, to the current day use of YouTube, mobile phones and tablets, multimodal texts have been apparent across Western cultures. The rapid development over the last 20 years of technology has markedly increased access to a much broader array of…

A Method of Sky Ripple Residual Nonuniformity Reduction for a Cooled Infrared Imager and Hardware Implementation

PubMed Central

Li, Yiyang; Jin, Weiqi; Li, Shuo; Zhang, Xu; Zhu, Jin

2017-01-01

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. PMID:28481320

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.

Discriminability and dimensionality effects in visual search for featural conjunctions: a functional pop-out.

PubMed

Dehaene, S

1989-07-01

Treisman and Gelade's (1980) feature-integration theory of attention states that a scene must be serially scanned before the objects in it can be accurately perceived. Is serial scanning compatible with the speed observed in the perception of real-world scenes? Most real scenes consist of many more dimensions (color, size, shape, depth, etc.) than those generally found in search paradigms. Furthermore, real objects differ from each other along many of these dimensions. The present experiment assessed the influence of the total number of dimensions and target/distractor discriminability (the number of dimensions that suffice to separate a target from distractors) on search times for a conjunction of features. Search was always found to be serial. However, for the most discriminable targets, search rate was so fast that search times were in the same range as pop-out detection times. Apparently, greater discriminability enables subjects to direct attention at a faster rate and at only a fraction of the items in a scene.

The Influence of New Technologies on the Visual Attention of CSIs Performing a Crime Scene Investigation.

PubMed

de Gruijter, Madeleine; de Poot, Christianne J; Elffers, Henk

2016-01-01

Currently, a series of promising new tools are under development that will enable crime scene investigators (CSIs) to analyze traces in situ during the crime scene investigation or enable them to detect blood and provide information on the age of blood. An experiment is conducted with thirty CSIs investigating a violent robbery at a mock crime scene to study the influence of such technologies on the perception and interpretation of traces during the first phase of the investigation. Results show that in their search for traces, CSIs are not directed by the availability of technologies, which is a reassuring finding. Qualitative findings suggest that CSIs are generally more focused on analyzing perpetrator traces than on reconstructing the event. A focus on perpetrator traces might become a risk when other crime-related traces are overlooked, and when analyzed traces are in fact not crime-related and in consequence lead to the identification of innocent suspects. © 2015 American Academy of Forensic Sciences.

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.

Detection of latent bloodstains beneath painted surfaces using reflected infrared photography.

PubMed

Farrar, Andrew; Porter, Glenn; Renshaw, Adrian

2012-09-01

Bloodstain evidence is a highly valued form of physical evidence commonly found at scenes involving violent crimes. However, painting over bloodstains will often conceal this type of evidence. There is limited research in the scientific literature that describes methods of detecting painted-over bloodstains. This project employed a modified digital single-lens reflex camera to investigate the effectiveness of infrared (IR) photography in detecting latent bloodstain evidence beneath a layer or multiple layers of paint. A qualitative evaluation was completed by comparing images taken of a series of samples using both IR and standard (visible light) photography. Further quantitative image analysis was used to verify the findings. Results from this project indicate that bloodstain evidence can be detected beneath up to six layers of paint using reflected IR; however, the results vary depending on the characteristics of the paint. This technique provides crime scene specialists with a new field method to assist in locating, visualizing, and documenting painted-over bloodstain evidence. © 2012 American Academy of Forensic Sciences.

Dissipation function and adaptive gradient reconstruction based smoke detection in video

NASA Astrophysics Data System (ADS)

Li, Bin; Zhang, Qiang; Shi, Chunlei

2017-11-01

A method for smoke detection in video is proposed. The camera monitoring the scene is assumed to be stationary. With the atmospheric scattering model, dissipation function is reflected transmissivity between the background objects in the scene and the camera. Dark channel prior and fast bilateral filter are used for estimating dissipation function which is only the function of the depth of field. Based on dissipation function, visual background extractor (ViBe) can be used for detecting smoke as a result of smoke's motion characteristics as well as detecting other moving targets. Since smoke has semi-transparent parts, the things which are covered by these parts can be recovered by poisson equation adaptively. The similarity between the recovered parts and the original background parts in the same position is calculated by Normalized Cross Correlation (NCC) and the original background's value is selected from the frame which is nearest to the current frame. The parts with high similarity are considered as smoke parts.

The polymorphism of crime scene investigation: An exploratory analysis of the influence of crime and forensic intelligence on decisions made by crime scene examiners.

PubMed

Resnikoff, Tatiana; Ribaux, Olivier; Baylon, Amélie; Jendly, Manon; Rossy, Quentin

2015-12-01

A growing body of scientific literature recurrently indicates that crime and forensic intelligence influence how crime scene investigators make decisions in their practices. This study scrutinises further this intelligence-led crime scene examination view. It analyses results obtained from two questionnaires. Data have been collected from nine chiefs of Intelligence Units (IUs) and 73 Crime Scene Examiners (CSEs) working in forensic science units (FSUs) in the French speaking part of Switzerland (six cantonal police agencies). Four salient elements emerged: (1) the actual existence of communication channels between IUs and FSUs across the police agencies under consideration; (2) most CSEs take into account crime intelligence disseminated; (3) a differentiated, but significant use by CSEs in their daily practice of this kind of intelligence; (4) a probable deep influence of this kind of intelligence on the most concerned CSEs, specially in the selection of the type of material/trace to detect, collect, analyse and exploit. These results contribute to decipher the subtle dialectic articulating crime intelligence and crime scene investigation, and to express further the polymorph role of CSEs, beyond their most recognised input to the justice system. Indeed, they appear to be central, but implicit, stakeholders in intelligence-led style of policing. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Texts in Tension: Negotiating Jewish Values in the Adult Jewish Learning Classroom

ERIC Educational Resources Information Center

Woocher, Meredith L.

2004-01-01

In this paper, the author begins with a brief classroom scene that illustrates a number of significant features of contemporary American Jewish life. The engagement of adult students with Jewish text study is an example and outgrowth of the flourishing of programs of adult Jewish learning over the past two decades. Thousands of similar Jewish…

Line grouping using perceptual saliency and structure prediction for car detection in traffic scenes

NASA Astrophysics Data System (ADS)

Denasi, Sandra; Quaglia, Giorgio

1993-08-01

Autonomous and guide assisted vehicles make a heavy use of computer vision techniques to perceive the environment where they move. In this context, the European PROMETHEUS program is carrying on activities in order to develop autonomous vehicle monitoring that assists people to achieve safer driving. Car detection is one of the topics that are faced by the program. Our contribution proposes the development of this task in two stages: the localization of areas of interest and the formulation of object hypotheses. In particular, the present paper proposes a new approach that builds structural descriptions of objects from edge segmentations by using geometrical organization. This approach has been applied to the detection of cars in traffic scenes. We have analyzed images taken from a moving vehicle in order to formulate obstacle hypotheses: preliminary results confirm the efficiency of the method.

Detection performance in clutter with variable resolution

NASA Astrophysics Data System (ADS)

Schmieder, D. E.; Weathersby, M. R.

1983-07-01

Experiments were conducted to determine the influence of background clutter on target detection criteria. The experiment consisted of placing observers in front of displayed images on a TV monitor. Observer ability to detect military targets embedded in simulated natural and manmade background clutter was measured when there was unlimited viewing time. Results were described in terms of detection probability versus target resolution for various signal to clutter ratios (SCR). The experiments were preceded by a search for a meaningful clutter definition. The selected definition was a statistical measure computed by averaging the standard deviation of contiguous scene cells over the whole scene. The cell size was comparable to the target size. Observer test results confirmed the expectation that the resolution required for a given detection probability was a continuum function of the clutter level. At the lower SCRs the resolution required for a high probability of detection was near 6 line pairs per target (LP/TGT), while at the higher SCRs it was found that a resoluton of less than 0.25 LP/TGT would yield a high probability of detection. These results are expected to aid in target acquisition performance modeling and to lead to improved specifications for imaging automatic target screeners.

An Experiment Quantifying The Effect Of Clutter On Target Detection

NASA Astrophysics Data System (ADS)

Weathersby, Marshall R.; Schmieder, David E.

1985-01-01

Experiments were conducted to determine the influence of background clutter on target detection criteria. The experiment consisted of placing observers in front of displayed images on a TV monitor. Observer ability to detect military targets embedded in simulated natural and manmade background clutter was measured when there was unlimited viewing time. Results were described in terms of detection probability versus target resolution for various signal to clutter ratios (SCR). The experiments were preceded by a search for a meaningful clutter definition. The selected definition was a statistical measure computed by averaging the standard deviation of contiguous scene cells over the whole scene. The cell size was comparable to the target size. Observer test results confirmed the expectation that the resolution required for a given detection probability was a continuum function of the clutter level. At the lower SCRs the resolution required for a high probability of detection was near 6 lines pairs per target (LP/TGT), while at the higher SCRs it was found that a resolution of less than 0.25 LP/TGT would yield a high probability of detection. These results are expected to aid in target acquisition performance modeling and to lead to improved specifications for imaging automatic target screeners.

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.

Pharmacovigilance and post-black market surveillance.

PubMed

Langlitz, Nicolas

2009-06-01

Pharmacovigilance can be defined as a set of practices aiming at the detection, understanding and assessment of risks related to the use of drugs in a population, and the prevention of consequential adverse effects. In a narrower sense, the term refers exclusively to postmarket surveillance. This paper briefly outlines how pharmacovigilance has come to play a central role in the regulation of novel pharmaceuticals. However, the focus of the text is on mechanisms emerging in an experimental drug scene that aim at dealing with the risks posed by 'designer drugs' newly introduced to the black market. This discussion of pharmacovigilance and 'post-black market surveillance' is situated in the broader context of the more recent dissemination of vigilance as a key element of government in a world too complex for legal and disciplinary measures alone.

Hyperspectral Feature Detection Onboard the Earth Observing One Spacecraft using Superpixel Segmentation and Endmember Extraction

NASA Technical Reports Server (NTRS)

Thompson, David R.; Bornstein, Benjamin; Bue, Brian D.; Tran, Daniel Q.; Chien, Steve A.; Castano, Rebecca

2012-01-01

We present a demonstration of onboard hyperspectral image processing with the potential to reduce mission downlink requirements. The system detects spectral endmembers and then uses them to map units of surface material. This summarizes the content of the scene, reveals spectral anomalies warranting fast response, and reduces data volume by two orders of magnitude. We have integrated this system into the Autonomous Science craft Experiment for operational use onboard the Earth Observing One (EO-1) Spacecraft. The system does not require prior knowledge about spectra of interest. We report on a series of trial overflights in which identical spacecraft commands are effective for autonomous spectral discovery and mapping for varied target features, scenes and imaging conditions.

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 novel array of chemiluminescence sensors for sensitive, rapid and high-throughput detection of explosive triacetone triperoxide at the scene.

PubMed

Li, Xiaohua; Zhang, Zhujun; Tao, Liang

2013-09-15

Triacetone triperoxide (TATP) is relatively easy to make and has been used in various terrorist acts. Early but easy detection of TATP is highly desired. We designed a new type sensor array for H2O2. The unique CL sensor array was based on CeO2 nanoparticles' membranes, which have an excellent catalytic effect on the luminol-H2O2 CL reaction in alkaline medium. It exhibits a linear range for the detection of H2O2 from 1.0×10(-8) to 5.0×10(-5)M (R(2)=0.9991) with a 1s response time. The detection limit is 1.0×10(-9)M. Notably, the present approach allows the design of CL sensor array assays in a more simple, time-saving, long-lifetime, high-throughput, and economical approach when compared with conventional CL sensor. It is conceptually different from conventional CL sensor assays. The novel sensor array has been successfully applied for the detection of TATP at the scene. Copyright © 2013 Elsevier B.V. All rights reserved.

Schlieren optics for leak detection

NASA Technical Reports Server (NTRS)

Peale, Robert E.; Ruffin, Alranzo B.

1995-01-01

The purpose of this research was to develop an optical method of leak detection. Various modifications of schlieren optics were explored with initial emphasis on leak detection of the plumbing within the orbital maneuvering system of the space shuttle (OMS pod). The schlieren scheme envisioned for OMS pod leak detection was that of a high contrast pattern on flexible reflecting material imaged onto a negative of the same pattern. We find that the OMS pod geometry constrains the characteristic length scale of the pattern to the order of 0.001 inch. Our experiments suggest that optical modulation transfer efficiency will be very low for such patterns, which will limit the sensitivity of the technique. Optical elements which allow a negative of the scene to be reversibly recorded using light from the scene itself were explored for their potential in adaptive single-ended schlieren systems. Elements studied include photochromic glass, bacteriorhodopsin, and a transmissive liquid crystal display. The dynamics of writing and reading patterns were studied using intensity profiles from recorded images. Schlieren detection of index gradients in air was demonstrated.

Automated intelligent video surveillance system for ships

NASA Astrophysics Data System (ADS)

Wei, Hai; Nguyen, Hieu; Ramu, Prakash; Raju, Chaitanya; Liu, Xiaoqing; Yadegar, Jacob

2009-05-01

To protect naval and commercial ships from attack by terrorists and pirates, it is important to have automatic surveillance systems able to detect, identify, track and alert the crew on small watercrafts that might pursue malicious intentions, while ruling out non-threat entities. Radar systems have limitations on the minimum detectable range and lack high-level classification power. In this paper, we present an innovative Automated Intelligent Video Surveillance System for Ships (AIVS3) as a vision-based solution for ship security. Capitalizing on advanced computer vision algorithms and practical machine learning methodologies, the developed AIVS3 is not only capable of efficiently and robustly detecting, classifying, and tracking various maritime targets, but also able to fuse heterogeneous target information to interpret scene activities, associate targets with levels of threat, and issue the corresponding alerts/recommendations to the man-in- the-loop (MITL). AIVS3 has been tested in various maritime scenarios and shown accurate and effective threat detection performance. By reducing the reliance on human eyes to monitor cluttered scenes, AIVS3 will save the manpower while increasing the accuracy in detection and identification of asymmetric attacks for ship protection.

Out of Mind, Out of Sight: Unexpected Scene Elements Frequently Go Unnoticed Until Primed.

PubMed

Slavich, George M; Zimbardo, Philip G

2013-12-01

The human visual system employs a sophisticated set of strategies for scanning the environment and directing attention to stimuli that can be expected given the context and a person's past experience. Although these strategies enable us to navigate a very complex physical and social environment, they can also cause highly salient, but unexpected stimuli to go completely unnoticed. To examine the generality of this phenomenon, we conducted eight studies that included 15 different experimental conditions and 1,577 participants in all. These studies revealed that a large majority of participants do not report having seen a woman in the center of an urban scene who was photographed in midair as she was committing suicide. Despite seeing the scene repeatedly, 46 % of all participants failed to report seeing a central figure and only 4.8 % reported seeing a falling person. Frequency of noticing the suicidal woman was highest for participants who read a narrative priming story that increased the extent to which she was schematically congruent with the scene. In contrast to this robust effect of inattentional blindness , a majority of participants reported seeing other peripheral objects in the visual scene that were equally difficult to detect, yet more consistent with the scene. Follow-up qualitative analyses revealed that participants reported seeing many elements that were not actually present, but which could have been expected given the overall context of the scene. Together, these findings demonstrate the robustness of inattentional blindness and highlight the specificity with which different visual primes may increase noticing behavior.

Fixed Pattern Noise pixel-wise linear correction for crime scene imaging CMOS sensor

NASA Astrophysics Data System (ADS)

Yang, Jie; Messinger, David W.; Dube, Roger R.; Ientilucci, Emmett J.

2017-05-01

Filtered multispectral imaging technique might be a potential method for crime scene documentation and evidence detection due to its abundant spectral information as well as non-contact and non-destructive nature. Low-cost and portable multispectral crime scene imaging device would be highly useful and efficient. The second generation crime scene imaging system uses CMOS imaging sensor to capture spatial scene and bandpass Interference Filters (IFs) to capture spectral information. Unfortunately CMOS sensors suffer from severe spatial non-uniformity compared to CCD sensors and the major cause is Fixed Pattern Noise (FPN). IFs suffer from "blue shift" effect and introduce spatial-spectral correlated errors. Therefore, Fixed Pattern Noise (FPN) correction is critical to enhance crime scene image quality and is also helpful for spatial-spectral noise de-correlation. In this paper, a pixel-wise linear radiance to Digital Count (DC) conversion model is constructed for crime scene imaging CMOS sensor. Pixel-wise conversion gain Gi,j and Dark Signal Non-Uniformity (DSNU) Zi,j are calculated. Also, conversion gain is divided into four components: FPN row component, FPN column component, defects component and effective photo response signal component. Conversion gain is then corrected to average FPN column and row components and defects component so that the sensor conversion gain is uniform. Based on corrected conversion gain and estimated image incident radiance from the reverse of pixel-wise linear radiance to DC model, corrected image spatial uniformity can be enhanced to 7 times as raw image, and the bigger the image DC value within its dynamic range, the better the enhancement.

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.

Rapid natural scene categorization in the near absence of attention

PubMed Central

Li, Fei Fei; VanRullen, Rufin; Koch, Christof; Perona, Pietro

2002-01-01

What can we see when we do not pay attention? It is well known that we can be “blind” even to major aspects of natural scenes when we attend elsewhere. The only tasks that do not need attention appear to be carried out in the early stages of the visual system. Contrary to this common belief, we report that subjects can rapidly detect animals or vehicles in briefly presented novel natural scenes while simultaneously performing another attentionally demanding task. By comparison, they are unable to discriminate large T's from L's, or bisected two-color disks from their mirror images under the same conditions. We conclude that some visual tasks associated with “high-level” cortical areas may proceed in the near absence of attention. PMID:12077298

Detecting and Analyzing Multiple Moving Objects in Crowded Environments with Coherent Motion Regions

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

Cheriyadat, Anil M.

Understanding the world around us from large-scale video data requires vision systems that can perform automatic interpretation. While human eyes can unconsciously perceive independent objects in crowded scenes and other challenging operating environments, automated systems have difficulty detecting, counting, and understanding their behavior in similar scenes. Computer scientists at ORNL have a developed a technology termed as "Coherent Motion Region Detection" that invloves identifying multiple indepedent moving objects in crowded scenes by aggregating low-level motion cues extracted from moving objects. Humans and other species exploit such low-level motion cues seamlessely to perform perceptual grouping for visual understanding. The algorithm detectsmore » and tracks feature points on moving objects resulting in partial trajectories that span coherent 3D region in the space-time volume defined by the video. In the case of multi-object motion, many possible coherent motion regions can be constructed around the set of trajectories. The unique approach in the algorithm is to identify all possible coherent motion regions, then extract a subset of motion regions based on an innovative measure to automatically locate moving objects in crowded environments.The software reports snapshot of the object, count, and derived statistics ( count over time) from input video streams. The software can directly process videos streamed over the internet or directly from a hardware device (camera).« less

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.

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

Search and Rescue. Auxiliary Operational Specialty Course. Student Text.

ERIC Educational Resources Information Center

Coast Guard, Washington, DC.

This text, based on the National Search and Rescue (SAR) Plan, was prepared to provide a course of study on common procedures for SAR operations so that any basically qualified person in the U.S. Coast Guard Auxiliary can effectively accomplish a SAR mission and act as on-scene commander if required. There are 13 chapters: Introduction to Search…

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.

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.

Luminance cues constrain chromatic blur discrimination in natural scene stimuli.

PubMed

Sharman, Rebecca J; McGraw, Paul V; Peirce, Jonathan W

2013-03-22

Introducing blur into the color components of a natural scene has very little effect on its percept, whereas blur introduced into the luminance component is very noticeable. Here we quantify the dominance of luminance information in blur detection and examine a number of potential causes. We show that the interaction between chromatic and luminance information is not explained by reduced acuity or spatial resolution limitations for chromatic cues, the effective contrast of the luminance cue, or chromatic and achromatic statistical regularities in the images. Regardless of the quality of chromatic information, the visual system gives primacy to luminance signals when determining edge location. In natural viewing, luminance information appears to be specialized for detecting object boundaries while chromatic information may be used to determine surface properties.

(In) Sensitivity to spatial distortion in natural scenes

PubMed Central

Bex, Peter J.

2010-01-01

The perception of object structure in the natural environment is remarkably stable under large variation in image size and projection, especially given our insensitivity to spatial position outside the fovea. Sensitivity to periodic spatial distortions that were introduced into one quadrant of gray-scale natural images was measured in a 4AFC task. Observers were able to detect the presence of distortions in unfamiliar images even though they did not significantly affect the amplitude spectrum. Sensitivity depended on the spatial period of the distortion and on the image structure at the location of the distortion. The results suggest that the detection of distortion involves decisions made in the late stages of image perception and is based on an expectation of the typical structure of natural scenes. PMID:20462324

Scene-based method for spatial misregistration detection in hyperspectral imagery.

PubMed

Dell'Endice, Francesco; Nieke, Jens; Schläpfer, Daniel; Itten, Klaus I

2007-05-20

Hyperspectral imaging (HSI) sensors suffer from spatial misregistration, an artifact that prevents the accurate acquisition of the spectra. Physical considerations let us assume that the influence of the spatial misregistration on the acquired data depends both on the wavelength and on the across-track position. A scene-based method, based on edge detection, is therefore proposed. Such a procedure measures the variation on the spatial location of an edge between its various monochromatic projections, giving an estimation for spatial misregistration, and also allowing identification of misalignments. The method has been applied to several hyperspectral sensors, either prism, or grating-based designs. The results confirm the dependence assumptions on lambda and theta, spectral wavelength and across-track pixel, respectively. Suggestions are also given to correct for spatial misregistration.

Comparing synthetic imagery with real imagery for visible signature analysis: human observer results

NASA Astrophysics Data System (ADS)

Culpepper, Joanne B.; Richards, Noel; Madden, Christopher S.; Winter, Neal; Wheaton, Vivienne C.

2017-10-01

Synthetic imagery could potentially enhance visible signature analysis by providing a wider range of target images in differing environmental conditions than would be feasible to collect in field trials. Achieving this requires a method for generating synthetic imagery that is both verified to be realistic and produces the same visible signature analysis results as real images. Is target detectability as measured by image metrics the same for real images and synthetic images of the same scene? Is target detectability as measured by human observer trials the same for real images and synthetic images of the same scene, and how realistic do the synthetic images need to be? In this paper we present the results of a small scale exploratory study on the second question: a photosimulation experiment conducted using digital photographs and synthetic images generated of the same scene. Two sets of synthetic images were created: a high fidelity set created using an image generation tool, E-on Vue, and a low fidelity set created using a gaming engine, Unity 3D. The target detection results obtained using digital photographs were compared with those obtained using the two sets of synthetic images. There was a moderate correlation between the high fidelity synthetic image set and the real images in both the probability of correct detection (Pd: PCC = 0.58, SCC = 0.57) and mean search time (MST: PCC = 0.63, SCC = 0.61). There was no correlation between the low fidelity synthetic image set and the real images for the Pd, but a moderate correlation for MST (PCC = 0.67, SCC = 0.55).

Evaluation of Alternate Concepts for Synthetic Vision Flight Displays With Weather-Penetrating Sensor Image Inserts During Simulated Landing Approaches

NASA Technical Reports Server (NTRS)

Parrish, Russell V.; Busquets, Anthony M.; Williams, Steven P.; Nold, Dean E.

2003-01-01

A simulation study was conducted in 1994 at Langley Research Center that used 12 commercial airline pilots repeatedly flying complex Microwave Landing System (MLS)-type approaches to parallel runways under Category IIIc weather conditions. Two sensor insert concepts of 'Synthetic Vision Systems' (SVS) were used in the simulated flights, with a more conventional electro-optical display (similar to a Head-Up Display with raster capability for sensor imagery), flown under less restrictive visibility conditions, used as a control condition. The SVS concepts combined the sensor imagery with a computer-generated image (CGI) of an out-the-window scene based on an onboard airport database. Various scenarios involving runway traffic incursions (taxiing aircraft and parked fuel trucks) and navigational system position errors (both static and dynamic) were used to assess the pilots' ability to manage the approach task with the display concepts. The two SVS sensor insert concepts contrasted the simple overlay of sensor imagery on the CGI scene without additional image processing (the SV display) to the complex integration (the AV display) of the CGI scene with pilot-decision aiding using both object and edge detection techniques for detection of obstacle conflicts and runway alignment errors.

Ghost detection and removal based on super-pixel grouping in exposure fusion

NASA Astrophysics Data System (ADS)

Jiang, Shenyu; Xu, Zhihai; Li, Qi; Chen, Yueting; Feng, Huajun

2014-09-01

A novel multi-exposure images fusion method for dynamic scenes is proposed. The commonly used techniques for high dynamic range (HDR) imaging are based on the combination of multiple differently exposed images of the same scene. The drawback of these methods is that ghosting artifacts will be introduced into the final HDR image if the scene is not static. In this paper, a super-pixel grouping based method is proposed to detect the ghost in the image sequences. We introduce the zero mean normalized cross correlation (ZNCC) as a measure of similarity between a given exposure image and the reference. The calculation of ZNCC is implemented in super-pixel level, and the super-pixels which have low correlation with the reference are excluded by adjusting the weight maps for fusion. Without any prior information on camera response function or exposure settings, the proposed method generates low dynamic range (LDR) images which can be shown on conventional display devices directly with details preserving and ghost effects reduced. Experimental results show that the proposed method generates high quality images which have less ghost artifacts and provide a better visual quality than previous approaches.

Optical system for object detection and delineation in space

NASA Astrophysics Data System (ADS)

Handelman, Amir; Shwartz, Shoam; Donitza, Liad; Chaplanov, Loran

2018-01-01

Object recognition and delineation is an important task in many environments, such as in crime scenes and operating rooms. Marking evidence or surgical tools and attracting the attention of the surrounding staff to the marked objects can affect people's lives. We present an optical system comprising a camera, computer, and small laser projector that can detect and delineate objects in the environment. To prove the optical system's concept, we show that it can operate in a hypothetical crime scene in which a pistol is present and automatically recognize and segment it by various computer-vision algorithms. Based on such segmentation, the laser projector illuminates the actual boundaries of the pistol and thus allows the persons in the scene to comfortably locate and measure the pistol without holding any intermediator device, such as an augmented reality handheld device, glasses, or screens. Using additional optical devices, such as diffraction grating and a cylinder lens, the pistol size can be estimated. The exact location of the pistol in space remains static, even after its removal. Our optical system can be fixed or dynamically moved, making it suitable for various applications that require marking of objects in space.

Study of Threat Scenario Reconstruction based on Multiple Correlation

NASA Astrophysics Data System (ADS)

Yuan, Xuejun; Du, Jing; Qin, Futong; Zhou, Yunyan

2017-10-01

The emergence of intrusion detection technology has solved many network attack problems, ensuring the safety of computer systems. However, because of the isolated output alarm information, large amount of data, and mixed events, it is difficult for the managers to understand the deep logic relationship between the alarm information, thus they cannot deduce the attacker’s true intentions. This paper presents a method of online threat scene reconstruction to handle the alarm information, which reconstructs of the threat scene. For testing, the standard data set is used.

Logarithmic r-θ mapping for hybrid optical neural network filter for multiple objects recognition within cluttered scenes

NASA Astrophysics Data System (ADS)

Kypraios, Ioannis; Young, Rupert C. D.; Chatwin, Chris R.; Birch, Phil M.

2009-04-01

θThe window unit in the design of the complex logarithmic r-θ mapping for hybrid optical neural network filter can allow multiple objects of the same class to be detected within the input image. Additionally, the architecture of the neural network unit of the complex logarithmic r-θ mapping for hybrid optical neural network filter becomes attractive for accommodating the recognition of multiple objects of different classes within the input image by modifying the output layer of the unit. We test the overall filter for multiple objects of the same and of different classes' recognition within cluttered input images and video sequences of cluttered scenes. Logarithmic r-θ mapping for hybrid optical neural network filter is shown to exhibit with a single pass over the input data simultaneously in-plane rotation, out-of-plane rotation, scale, log r-θ map translation and shift invariance, and good clutter tolerance by recognizing correctly the different objects within the cluttered scenes. We record in our results additional extracted information from the cluttered scenes about the objects' relative position, scale and in-plane rotation.

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.

Computed tomography imaging spectrometer (CTIS) with 2D reflective grating for ultraviolet to long-wave infrared detection especially useful for surveying transient events

NASA Technical Reports Server (NTRS)

Muller, Richard E. (Inventor); Mouroulis, Pantazis Z. (Inventor); Maker, Paul D. (Inventor); Wilson, Daniel W. (Inventor)

2003-01-01

The optical system of this invention is an unique type of imaging spectrometer, i.e. an instrument that can determine the spectra of all points in a two-dimensional scene. The general type of imaging spectrometer under which this invention falls has been termed a computed-tomography imaging spectrometer (CTIS). CTIS's have the ability to perform spectral imaging of scenes containing rapidly moving objects or evolving features, hereafter referred to as transient scenes. This invention, a reflective CTIS with an unique two-dimensional reflective grating, can operate in any wavelength band from the ultraviolet through long-wave infrared. Although this spectrometer is especially useful for rapidly occurring events it is also useful for investigation of some slow moving phenomena as in the life sciences.

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…

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.

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.

Target discrimination strategies in optics detection

NASA Astrophysics Data System (ADS)

Sjöqvist, Lars; Allard, Lars; Henriksson, Markus; Jonsson, Per; Pettersson, Magnus

2013-10-01

Detection and localisation of optical assemblies used for weapon guidance or sniper rifle scopes has attracted interest for security and military applications. Typically a laser system is used to interrogate a scene of interest and the retro-reflected radiation is detected. Different system approaches for area coverage can be realised ranging from flood illumination to step-and-stare or continuous scanning schemes. Independently of the chosen approach target discrimination is a crucial issue, particularly if a complex scene such as in an urban environment and autonomous operation is considered. In this work target discrimination strategies in optics detection are discussed. Typical parameters affecting the reflected laser radiation from the target are the wavelength, polarisation properties, temporal effects and the range resolution. Knowledge about the target characteristics is important to predict the target discrimination capability. Two different systems were used to investigate polarisation properties and range resolution information from targets including e.g. road signs, optical reflexes, rifle sights and optical references. The experimental results and implications on target discrimination will be discussed. If autonomous operation is required target discrimination becomes critical in order to reduce the number of false alarms.

Time-of-flight-assisted Kinect camera-based people detection for intuitive human robot cooperation in the surgical operating room.

PubMed

Beyl, Tim; Nicolai, Philip; Comparetti, Mirko D; Raczkowsky, Jörg; De Momi, Elena; Wörn, Heinz

2016-07-01

Scene supervision is a major tool to make medical robots safer and more intuitive. The paper shows an approach to efficiently use 3D cameras within the surgical operating room to enable for safe human robot interaction and action perception. Additionally the presented approach aims to make 3D camera-based scene supervision more reliable and accurate. A camera system composed of multiple Kinect and time-of-flight cameras has been designed, implemented and calibrated. Calibration and object detection as well as people tracking methods have been designed and evaluated. The camera system shows a good registration accuracy of 0.05 m. The tracking of humans is reliable and accurate and has been evaluated in an experimental setup using operating clothing. The robot detection shows an error of around 0.04 m. The robustness and accuracy of the approach allow for an integration into modern operating room. The data output can be used directly for situation and workflow detection as well as collision avoidance.

Fiches pratiques: Domino gastronomique; Ticket de metro; Articles definis et indefinis; Texte en scenes (Practical Ideas: Gastronomic Dominos; Metro Ticket; Definite and Indefinite Articles; Text on Stage).

ERIC Educational Resources Information Center

Grigoriou, Marianthi; And Others

1992-01-01

Four language classroom activities are described, including a food game, a culture and language activity based on a Paris Metro ticket, an exercise in the use of definite and indefinite articles using a film poster, and a classroom adaptation of a fairy tale for dramatic oral presentation. (MSE)

Combined effects of expectations and visual uncertainty upon detection and identification of a target in the fog.

PubMed

Quétard, Boris; Quinton, Jean-Charles; Colomb, Michèle; Pezzulo, Giovanni; Barca, Laura; Izaute, Marie; Appadoo, Owen Kevin; Mermillod, Martial

2015-09-01

Detecting a pedestrian while driving in the fog is one situation where the prior expectation about the target presence is integrated with the noisy visual input. We focus on how these sources of information influence the oculomotor behavior and are integrated within an underlying decision-making process. The participants had to judge whether high-/low-density fog scenes displayed on a computer screen contained a pedestrian or a deer by executing a mouse movement toward the response button (mouse-tracking). A variable road sign was added on the scene to manipulate expectations about target identity. We then analyzed the timing and amplitude of the deviation of mouse trajectories toward the incorrect response and, using an eye tracker, the detection time (before fixating the target) and the identification time (fixations on the target). Results revealed that expectation of the correct target results in earlier decisions with less deviation toward the alternative response, this effect being partially explained by the facilitation of target identification.

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).

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

Autonomous landing and ingress of micro-air-vehicles in urban environments based on monocular vision

NASA Astrophysics Data System (ADS)

Brockers, Roland; Bouffard, Patrick; Ma, Jeremy; Matthies, Larry; Tomlin, Claire

2011-06-01

Unmanned micro air vehicles (MAVs) will play an important role in future reconnaissance and search and rescue applications. In order to conduct persistent surveillance and to conserve energy, MAVs need the ability to land, and they need the ability to enter (ingress) buildings and other structures to conduct reconnaissance. To be safe and practical under a wide range of environmental conditions, landing and ingress maneuvers must be autonomous, using real-time, onboard sensor feedback. To address these key behaviors, we present a novel method for vision-based autonomous MAV landing and ingress using a single camera for two urban scenarios: landing on an elevated surface, representative of a rooftop, and ingress through a rectangular opening, representative of a door or window. Real-world scenarios will not include special navigation markers, so we rely on tracking arbitrary scene features; however, we do currently exploit planarity of the scene. Our vision system uses a planar homography decomposition to detect navigation targets and to produce approach waypoints as inputs to the vehicle control algorithm. Scene perception, planning, and control run onboard in real-time; at present we obtain aircraft position knowledge from an external motion capture system, but we expect to replace this in the near future with a fully self-contained, onboard, vision-aided state estimation algorithm. We demonstrate autonomous vision-based landing and ingress target detection with two different quadrotor MAV platforms. To our knowledge, this is the first demonstration of onboard, vision-based autonomous landing and ingress algorithms that do not use special purpose scene markers to identify the destination.

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.

Autonomous Landing and Ingress of Micro-Air-Vehicles in Urban Environments Based on Monocular Vision

NASA Technical Reports Server (NTRS)

Brockers, Roland; Bouffard, Patrick; Ma, Jeremy; Matthies, Larry; Tomlin, Claire

2011-01-01

Unmanned micro air vehicles (MAVs) will play an important role in future reconnaissance and search and rescue applications. In order to conduct persistent surveillance and to conserve energy, MAVs need the ability to land, and they need the ability to enter (ingress) buildings and other structures to conduct reconnaissance. To be safe and practical under a wide range of environmental conditions, landing and ingress maneuvers must be autonomous, using real-time, onboard sensor feedback. To address these key behaviors, we present a novel method for vision-based autonomous MAV landing and ingress using a single camera for two urban scenarios: landing on an elevated surface, representative of a rooftop, and ingress through a rectangular opening, representative of a door or window. Real-world scenarios will not include special navigation markers, so we rely on tracking arbitrary scene features; however, we do currently exploit planarity of the scene. Our vision system uses a planar homography decomposition to detect navigation targets and to produce approach waypoints as inputs to the vehicle control algorithm. Scene perception, planning, and control run onboard in real-time; at present we obtain aircraft position knowledge from an external motion capture system, but we expect to replace this in the near future with a fully self-contained, onboard, vision-aided state estimation algorithm. We demonstrate autonomous vision-based landing and ingress target detection with two different quadrotor MAV platforms. To our knowledge, this is the first demonstration of onboard, vision-based autonomous landing and ingress algorithms that do not use special purpose scene markers to identify the destination.

VR Lab ISS Graphics Models Data Package

NASA Technical Reports Server (NTRS)

Paddock, Eddie; Homan, Dave; Bell, Brad; Miralles, Evely; Hoblit, Jeff

2016-01-01

All the ISS models are saved in AC3D model format which is a text based format that can be loaded into blender and exported to other formats from there including FBX. The models are saved in two different levels of detail, one being labeled "LOWRES" and the other labeled "HIRES". There are two ".str" files (HIRES _ scene _ load.str and LOWRES _ scene _ load.str) that give the hierarchical relationship of the different nodes and the models associated with each node for both the "HIRES" and "LOWRES" model sets. All the images used for texturing are stored in Windows ".bmp" format for easy importing.

Infrared imaging of the crime scene: possibilities and pitfalls.

PubMed

Edelman, Gerda J; Hoveling, Richelle J M; Roos, Martin; van Leeuwen, Ton G; Aalders, Maurice C G

2013-09-01

All objects radiate infrared energy invisible to the human eye, which can be imaged by infrared cameras, visualizing differences in temperature and/or emissivity of objects. Infrared imaging is an emerging technique for forensic investigators. The rapid, nondestructive, and noncontact features of infrared imaging indicate its suitability for many forensic applications, ranging from the estimation of time of death to the detection of blood stains on dark backgrounds. This paper provides an overview of the principles and instrumentation involved in infrared imaging. Difficulties concerning the image interpretation due to different radiation sources and different emissivity values within a scene are addressed. Finally, reported forensic applications are reviewed and supported by practical illustrations. When introduced in forensic casework, infrared imaging can help investigators to detect, to visualize, and to identify useful evidence nondestructively. © 2013 American Academy of Forensic Sciences.

Animal Detection in Natural Images: Effects of Color and Image Database

PubMed Central

Zhu, Weina; Drewes, Jan; Gegenfurtner, Karl R.

2013-01-01

The visual system has a remarkable ability to extract categorical information from complex natural scenes. In order to elucidate the role of low-level image features for the recognition of objects in natural scenes, we recorded saccadic eye movements and event-related potentials (ERPs) in two experiments, in which human subjects had to detect animals in previously unseen natural images. We used a new natural image database (ANID) that is free of some of the potential artifacts that have plagued the widely used COREL images. Color and grayscale images picked from the ANID and COREL databases were used. In all experiments, color images induced a greater N1 EEG component at earlier time points than grayscale images. We suggest that this influence of color in animal detection may be masked by later processes when measuring reation times. The ERP results of go/nogo and forced choice tasks were similar to those reported earlier. The non-animal stimuli induced bigger N1 than animal stimuli both in the COREL and ANID databases. This result indicates ultra-fast processing of animal images is possible irrespective of the particular database. With the ANID images, the difference between color and grayscale images is more pronounced than with the COREL images. The earlier use of the COREL images might have led to an underestimation of the contribution of color. Therefore, we conclude that the ANID image database is better suited for the investigation of the processing of natural scenes than other databases commonly used. PMID:24130744

Infrared hyperspectral imaging for chemical vapour detection

NASA Astrophysics Data System (ADS)

Ruxton, K.; Robertson, G.; Miller, W.; Malcolm, G. P. A.; Maker, G. T.; Howle, C. R.

2012-10-01

Active hyperspectral imaging is a valuable tool in a wide range of applications. One such area is the detection and identification of chemicals, especially toxic chemical warfare agents, through analysis of the resulting absorption spectrum. This work presents a selection of results from a prototype midwave infrared (MWIR) hyperspectral imaging instrument that has successfully been used for compound detection at a range of standoff distances. Active hyperspectral imaging utilises a broadly tunable laser source to illuminate the scene with light at a range of wavelengths. While there are a number of illumination methods, the chosen configuration illuminates the scene by raster scanning the laser beam using a pair of galvanometric mirrors. The resulting backscattered light from the scene is collected by the same mirrors and focussed onto a suitable single-point detector, where the image is constructed pixel by pixel. The imaging instrument that was developed in this work is based around an IR optical parametric oscillator (OPO) source with broad tunability, operating in the 2.6 to 3.7 μm (MWIR) and 1.5 to 1.8 μm (shortwave IR, SWIR) spectral regions. The MWIR beam was primarily used as it addressed the fundamental absorption features of the target compounds compared to the overtone and combination bands in the SWIR region, which can be less intense by more than an order of magnitude. We show that a prototype NCI instrument was able to locate hydrocarbon materials at distances up to 15 metres.

Category search speeds up face-selective fMRI responses in a non-hierarchical cortical face network.

PubMed

Jiang, Fang; Badler, Jeremy B; Righi, Giulia; Rossion, Bruno

2015-05-01

The human brain is extremely efficient at detecting faces in complex visual scenes, but the spatio-temporal dynamics of this remarkable ability, and how it is influenced by category-search, remain largely unknown. In the present study, human subjects were shown gradually-emerging images of faces or cars in visual scenes, while neural activity was recorded using functional magnetic resonance imaging (fMRI). Category search was manipulated by the instruction to indicate the presence of either a face or a car, in different blocks, as soon as an exemplar of the target category was detected in the visual scene. The category selectivity of most face-selective areas was enhanced when participants were instructed to report the presence of faces in gradually decreasing noise stimuli. Conversely, the same regions showed much less selectivity when participants were instructed instead to detect cars. When "face" was the target category, the fusiform face area (FFA) showed consistently earlier differentiation of face versus car stimuli than did the "occipital face area" (OFA). When "car" was the target category, only the FFA showed differentiation of face versus car stimuli. These observations provide further challenges for hierarchical models of cortical face processing and show that during gradual revealing of information, selective category-search may decrease the required amount of information, enhancing and speeding up category-selective responses in the human brain. Copyright © 2015 Elsevier Ltd. All rights reserved.

Three-dimensional tracking for efficient fire fighting in complex situations

NASA Astrophysics Data System (ADS)

Akhloufi, Moulay; Rossi, Lucile

2009-05-01

Each year, hundred millions hectares of forests burn causing human and economic losses. For efficient fire fighting, the personnel in the ground need tools permitting the prediction of fire front propagation. In this work, we present a new technique for automatically tracking fire spread in three-dimensional space. The proposed approach uses a stereo system to extract a 3D shape from fire images. A new segmentation technique is proposed and permits the extraction of fire regions in complex unstructured scenes. It works in the visible spectrum and combines information extracted from YUV and RGB color spaces. Unlike other techniques, our algorithm does not require previous knowledge about the scene. The resulting fire regions are classified into different homogenous zones using clustering techniques. Contours are then extracted and a feature detection algorithm is used to detect interest points like local maxima and corners. Extracted points from stereo images are then used to compute the 3D shape of the fire front. The resulting data permits to build the fire volume. The final model is used to compute important spatial and temporal fire characteristics like: spread dynamics, local orientation, heading direction, etc. Tests conducted on the ground show the efficiency of the proposed scheme. This scheme is being integrated with a fire spread mathematical model in order to predict and anticipate the fire behaviour during fire fighting. Also of interest to fire-fighters, is the proposed automatic segmentation technique that can be used in early detection of fire in complex scenes.

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.

Applications of Quantum Cascade Laser Scanners for Remote Detection of Chemical and Biological Threats and Weapons of Mass Destruction

DTIC Science & Technology

2014-07-09

Rivera. Highly Sensitive Filter Paper Substrate for SERS Trace Explosives Detection , International Journal of Spectroscopy, (09 2012): 0. doi: 10.1155...Highly Sensitive Filter Paper Substrate for SERS Field Detection of Trace Threat Chemicals”, PITTCON-2013: Forensic Analysis in the Lab and Crime Scene...the surface. In addition, built-in algorithms were used for nearly real-time sample detection . Trace and bulk concentrations of the other substances

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

An optical systems analysis approach to image resampling

NASA Technical Reports Server (NTRS)

Lyon, Richard G.

1997-01-01

All types of image registration require some type of resampling, either during the registration or as a final step in the registration process. Thus the image(s) must be regridded into a spatially uniform, or angularly uniform, coordinate system with some pre-defined resolution. Frequently the ending resolution is not the resolution at which the data was observed with. The registration algorithm designer and end product user are presented with a multitude of possible resampling methods each of which modify the spatial frequency content of the data in some way. The purpose of this paper is threefold: (1) to show how an imaging system modifies the scene from an end to end optical systems analysis approach, (2) to develop a generalized resampling model, and (3) empirically apply the model to simulated radiometric scene data and tabulate the results. A Hanning windowed sinc interpolator method will be developed based upon the optical characterization of the system. It will be discussed in terms of the effects and limitations of sampling, aliasing, spectral leakage, and computational complexity. Simulated radiometric scene data will be used to demonstrate each of the algorithms. A high resolution scene will be "grown" using a fractal growth algorithm based on mid-point recursion techniques. The result scene data will be convolved with a point spread function representing the optical response. The resultant scene will be convolved with the detection systems response and subsampled to the desired resolution. The resultant data product will be subsequently resampled to the correct grid using the Hanning windowed sinc interpolator and the results and errors tabulated and discussed.

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

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.

Chromatic information and feature detection in fast visual analysis

DOE PAGES

Del Viva, Maria M.; Punzi, Giovanni; Shevell, Steven K.; ...

2016-08-01

The visual system is able to recognize a scene based on a sketch made of very simple features. This ability is likely crucial for survival, when fast image recognition is necessary, and it is believed that a primal sketch is extracted very early in the visual processing. Such highly simplified representations can be sufficient for accurate object discrimination, but an open question is the role played by color in this process. Rich color information is available in natural scenes, yet artist's sketches are usually monochromatic; and, black-andwhite movies provide compelling representations of real world scenes. Also, the contrast sensitivity ofmore » color is low at fine spatial scales. We approach the question from the perspective of optimal information processing by a system endowed with limited computational resources. We show that when such limitations are taken into account, the intrinsic statistical properties of natural scenes imply that the most effective strategy is to ignore fine-scale color features and devote most of the bandwidth to gray-scale information. We find confirmation of these information-based predictions from psychophysics measurements of fast-viewing discrimination of natural scenes. As a result, we conclude that the lack of colored features in our visual representation, and our overall low sensitivity to high-frequency color components, are a consequence of an adaptation process, optimizing the size and power consumption of our brain for the visual world we live in.« less

Chromatic information and feature detection in fast visual analysis

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

Del Viva, Maria M.; Punzi, Giovanni; Shevell, Steven K.

The visual system is able to recognize a scene based on a sketch made of very simple features. This ability is likely crucial for survival, when fast image recognition is necessary, and it is believed that a primal sketch is extracted very early in the visual processing. Such highly simplified representations can be sufficient for accurate object discrimination, but an open question is the role played by color in this process. Rich color information is available in natural scenes, yet artist's sketches are usually monochromatic; and, black-andwhite movies provide compelling representations of real world scenes. Also, the contrast sensitivity ofmore » color is low at fine spatial scales. We approach the question from the perspective of optimal information processing by a system endowed with limited computational resources. We show that when such limitations are taken into account, the intrinsic statistical properties of natural scenes imply that the most effective strategy is to ignore fine-scale color features and devote most of the bandwidth to gray-scale information. We find confirmation of these information-based predictions from psychophysics measurements of fast-viewing discrimination of natural scenes. As a result, we conclude that the lack of colored features in our visual representation, and our overall low sensitivity to high-frequency color components, are a consequence of an adaptation process, optimizing the size and power consumption of our brain for the visual world we live in.« less

Leading-edge forensic DNA analyses and the necessity of including crime scene investigators, police officers and technicians in a DNA elimination database.

PubMed

Lapointe, Martine; Rogic, Anita; Bourgoin, Sarah; Jolicoeur, Christine; Séguin, Diane

2015-11-01

In recent years, sophisticated technology has significantly increased the sensitivity and analytical power of genetic analyses so that very little starting material may now produce viable genetic profiles. This sensitivity however, has also increased the risk of detecting unknown genetic profiles assumed to be that of the perpetrator, yet originate from extraneous sources such as from crime scene workers. These contaminants may mislead investigations, keeping criminal cases active and unresolved for long spans of time. Voluntary submission of DNA samples from crime scene workers is fairly low, therefore we have created a promotional method for our staff elimination database that has resulted in a significant increase in voluntary samples since 2011. Our database enforces privacy safeguards and allows for optional anonymity to all staff members. We also offer information sessions at various police precincts to advise crime scene workers of the importance and success of our staff elimination database. This study, a pioneer in its field, has obtained 327 voluntary submissions from crime scene workers to date, of which 46 individual profiles (14%) have been matched to 58 criminal cases. By implementing our methods and respect for individual privacy, forensic laboratories everywhere may see similar growth and success in explaining unidentified genetic profiles in stagnate criminal cases. Crown Copyright © 2015. Published by Elsevier Ireland Ltd. All rights reserved.

Attentional Differences in a Driving Hazard Perception Task in Adults with Autism Spectrum Disorders

ERIC Educational Resources Information Center

Sheppard, Elizabeth; van Loon, Editha; Underwood, Geoffrey; Ropar, Danielle

2017-01-01

The current study explored attentional processing of social and non-social stimuli in ASD within the context of a driving hazard perception task. Participants watched videos of road scenes and detected hazards while their eye movements were recorded. Although individuals with ASD demonstrated relatively good detection of driving hazards, they were…

Multiple feature extraction by using simultaneous wavelet transforms

NASA Astrophysics Data System (ADS)

Mazzaferri, Javier; Ledesma, Silvia; Iemmi, Claudio

2003-07-01

We propose here a method to optically perform multiple feature extraction by using wavelet transforms. The method is based on obtaining the optical correlation by means of a Vander Lugt architecture, where the scene and the filter are displayed on spatial light modulators (SLMs). Multiple phase filters containing the information about the features that we are interested in extracting are designed and then displayed on an SLM working in phase mostly mode. We have designed filters to simultaneously detect edges and corners or different characteristic frequencies contained in the input scene. Simulated and experimental results are shown.

Traffic Signs in Complex Visual Environments

DOT National Transportation Integrated Search

1982-11-01

The effects of sign luminance on detection and recognition of traffic control devices is mediated through contrast with the immediate surround. Additionally, complex visual scenes are known to degrade visual performance with targets well above visual...

Detection of differential viewing patterns to erotic and non-erotic stimuli using eye-tracking methodology.

PubMed

Lykins, Amy D; Meana, Marta; Kambe, Gretchen

2006-10-01

As a first step in the investigation of the role of visual attention in the processing of erotic stimuli, eye-tracking methodology was employed to measure eye movements during erotic scene presentation. Because eye-tracking is a novel methodology in sexuality research, we attempted to determine whether the eye-tracker could detect differences (should they exist) in visual attention to erotic and non-erotic scenes. A total of 20 men and 20 women were presented with a series of erotic and non-erotic images and tracked their eye movements during image presentation. Comparisons between erotic and non-erotic image groups showed significant differences on two of three dependent measures of visual attention (number of fixations and total time) in both men and women. As hypothesized, there was a significant Stimulus x Scene Region interaction, indicating that participants visually attended to the body more in the erotic stimuli than in the non-erotic stimuli, as evidenced by a greater number of fixations and longer total time devoted to that region. These findings provide support for the application of eye-tracking methodology as a measure of visual attentional capture in sexuality research. Future applications of this methodology to expand our knowledge of the role of cognition in sexuality are suggested.

Salient target detection based on pseudo-Wigner-Ville distribution and Rényi entropy.

PubMed

Xu, Yuannan; Zhao, Yuan; Jin, Chenfei; Qu, Zengfeng; Liu, Liping; Sun, Xiudong

2010-02-15

We present what we believe to be a novel method based on pseudo-Wigner-Ville distribution (PWVD) and Rényi entropy for salient targets detection. In the foundation of studying the statistical property of Rényi entropy via PWVD, the residual entropy-based saliency map of an input image can be obtained. From the saliency map, target detection is completed by the simple and convenient threshold segmentation. Experimental results demonstrate the proposed method can detect targets effectively in complex ground scenes.

Analysis of reflectance spectra of UV-absorbing aerosol scenes measured by SCIAMACHY

NASA Astrophysics Data System (ADS)

de Graaf, M.; Stammes, P.; Aben, E. A. A.

2007-01-01

Reflectance spectra from 280-1750 nm of typical desert dust aerosol (DDA) and biomass burning aerosol (BBA) scenes over oceans are presented, measured by the space-borne spectrometer Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY). DDA and BBA are both UV-absorbing aerosols, but their effect on the top-of-atmosphere (TOA) reflectance is different due to differences in the way mineral aerosols and smoke reflect and absorb radiation. Mineral aerosols are typically large, inert particles, found in warm, dry continental air. Smoke particles, on the other hand, are usually small particles, although often clustered, chemically very active and highly variable in composition. Moreover, BBA are hygroscopic and over oceans BBA were invariably found in cloudy scenes. TOA reflectance spectra of typical DDA and BBA scenes were analyzed, using radiative transfer simulations, and compared. The DDA spectrum was successfully simulated using a layer with a bimodal size distribution of mineral aerosols in a clear sky. The spectrum of the BBA scene, however, was determined by the interaction between cloud droplets and smoke particles, as is shown by simulations with a model of separate aerosol and cloud layers and models with internally and externally mixed aerosol/cloud layers. The occurrence of clouds in smoke scenes when sufficient water vapor is present usually prevents the detection of optical properties of these aerosol plumes using space-borne sensors. However, the Absorbing Aerosol Index (AAI), a UV color index, is not sensitive to scattering aerosols and clouds and can be used to detect these otherwise obscured aerosol plumes over clouds. The amount of absorption of radiation can be expressed using the absorption optical thickness. The absorption optical thickness in the DDA case was 0.42 (340 nm) and 0.14 (550 nm) for an aerosol layer of optical thickness 1.74 (550 nm). In the BBA case the absorption optical thickness was 0.18 (340 nm) and 0.10 (550 nm) for an aerosol/cloud layer of optical thickness 20.0 (550 nm). However, this reduced the cloud albedo by about 0.2 (340 nm) and 0.15 (550 nm). This method can be an important tool to estimate the global impact of absorption of shortwave radiation by smoke and industrial aerosols inside clouds.

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.

Long-Term Memories Bias Sensitivity and Target Selection in Complex Scenes

PubMed Central

Patai, Eva Zita; Doallo, Sonia; Nobre, Anna Christina

2014-01-01

In everyday situations we often rely on our memories to find what we are looking for in our cluttered environment. Recently, we developed a new experimental paradigm to investigate how long-term memory (LTM) can guide attention, and showed how the pre-exposure to a complex scene in which a target location had been learned facilitated the detection of the transient appearance of the target at the remembered location (Summerfield, Lepsien, Gitelman, Mesulam, & Nobre, 2006; Summerfield, Rao, Garside, & Nobre, 2011). The present study extends these findings by investigating whether and how LTM can enhance perceptual sensitivity to identify targets occurring within their complex scene context. Behavioral measures showed superior perceptual sensitivity (d′) for targets located in remembered spatial contexts. We used the N2pc event-related potential to test whether LTM modulated the process of selecting the target from its scene context. Surprisingly, in contrast to effects of visual spatial cues or implicit contextual cueing, LTM for target locations significantly attenuated the N2pc potential. We propose that the mechanism by which these explicitly available LTMs facilitate perceptual identification of targets may differ from mechanisms triggered by other types of top-down sources of information. PMID:23016670

Automatic Ship Detection in Remote Sensing Images from Google Earth of Complex Scenes Based on Multiscale Rotation Dense Feature Pyramid Networks

NASA Astrophysics Data System (ADS)

Yang, Xue; Sun, Hao; Fu, Kun; Yang, Jirui; Sun, Xian; Yan, Menglong; Guo, Zhi

2018-01-01

Ship detection has been playing a significant role in the field of remote sensing for a long time but it is still full of challenges. The main limitations of traditional ship detection methods usually lie in the complexity of application scenarios, the difficulty of intensive object detection and the redundancy of detection region. In order to solve such problems above, we propose a framework called Rotation Dense Feature Pyramid Networks (R-DFPN) which can effectively detect ship in different scenes including ocean and port. Specifically, we put forward the Dense Feature Pyramid Network (DFPN), which is aimed at solving the problem resulted from the narrow width of the ship. Compared with previous multi-scale detectors such as Feature Pyramid Network (FPN), DFPN builds the high-level semantic feature-maps for all scales by means of dense connections, through which enhances the feature propagation and encourages the feature reuse. Additionally, in the case of ship rotation and dense arrangement, we design a rotation anchor strategy to predict the minimum circumscribed rectangle of the object so as to reduce the redundant detection region and improve the recall. Furthermore, we also propose multi-scale ROI Align for the purpose of maintaining the completeness of semantic and spatial information. Experiments based on remote sensing images from Google Earth for ship detection show that our detection method based on R-DFPN representation has a state-of-the-art performance.

A novel framework for intelligent surveillance system based on abnormal human activity detection in academic environments.

PubMed

Al-Nawashi, Malek; Al-Hazaimeh, Obaida M; Saraee, Mohamad

2017-01-01

Abnormal activity detection plays a crucial role in surveillance applications, and a surveillance system that can perform robustly in an academic environment has become an urgent need. In this paper, we propose a novel framework for an automatic real-time video-based surveillance system which can simultaneously perform the tracking, semantic scene learning, and abnormality detection in an academic environment. To develop our system, we have divided the work into three phases: preprocessing phase, abnormal human activity detection phase, and content-based image retrieval phase. For motion object detection, we used the temporal-differencing algorithm and then located the motions region using the Gaussian function. Furthermore, the shape model based on OMEGA equation was used as a filter for the detected objects (i.e., human and non-human). For object activities analysis, we evaluated and analyzed the human activities of the detected objects. We classified the human activities into two groups: normal activities and abnormal activities based on the support vector machine. The machine then provides an automatic warning in case of abnormal human activities. It also embeds a method to retrieve the detected object from the database for object recognition and identification using content-based image retrieval. Finally, a software-based simulation using MATLAB was performed and the results of the conducted experiments showed an excellent surveillance system that can simultaneously perform the tracking, semantic scene learning, and abnormality detection in an academic environment with no human intervention.

Predicting Boat-Generated Wave Heights: A Quantitative Analysis through Video Observations of Vessel Wakes

DTIC Science & Technology

2012-05-18

by the AWAC. It is a surface- penetrating device that measures continuous changes in the water elevations over time at much higher sampling rates of...background subtraction, a technique based on detecting change from a background scene. Their study highlights the difficulty in object detection and tracking...movements (Zhang et al. 2009) Alternatively, another common object detection method , known as Optical Flow Analysis , may be utilized for vessel

Hyperspectral imaging for differentiation of foreign materials from pinto beans

NASA Astrophysics Data System (ADS)

Mehrubeoglu, Mehrube; Zemlan, Michael; Henry, Sam

2015-09-01

Food safety and quality in packaged products are paramount in the food processing industry. To ensure that packaged products are free of foreign materials, such as debris and pests, unwanted materials mixed with the targeted products must be detected before packaging. A portable hyperspectral imaging system in the visible-to-NIR range has been used to acquire hyperspectral data cubes from pinto beans that have been mixed with foreign matter. Bands and band ratios have been identified as effective features to develop a classification scheme for detection of foreign materials in pinto beans. A support vector machine has been implemented with a quadratic kernel to separate pinto beans and background (Class 1) from all other materials (Class 2) in each scene. After creating a binary classification map for the scene, further analysis of these binary images allows separation of false positives from true positives for proper removal action during packaging.

Infrared polarimetric sensing of oil on water

NASA Astrophysics Data System (ADS)

Chenault, David B.; Vaden, Justin P.; Mitchell, Douglas A.; DeMicco, Erik D.

2016-10-01

Infrared polarimetry is an emerging sensing modality that offers the potential for significantly enhanced contrast in situations where conventional thermal imaging falls short. Polarimetric imagery leverages the different polarization signatures that result from material differences, surface roughness quality, and geometry that are frequently different from those features that lead to thermal signatures. Imaging of the polarization in a scene can lead to enhanced understanding, particularly when materials in a scene are at thermal equilibrium. Polaris Sensor Technologies has measured the polarization signatures of oil on water in a number of different scenarios and has shown significant improvement in detection through the contrast improvement offered by polarimetry. The sensing improvement offers the promise of automated detection of oil spills and leaks for routine monitoring and accidents with the added benefit of being able to continue monitoring at night. In this paper, we describe the instrumentation, and the results of several measurement exercises in both controlled and uncontrolled conditions.

A Method for Counting Moving People in Video Surveillance Videos

NASA Astrophysics Data System (ADS)

Conte, Donatello; Foggia, Pasquale; Percannella, Gennaro; Tufano, Francesco; Vento, Mario

2010-12-01

People counting is an important problem in video surveillance applications. This problem has been faced either by trying to detect people in the scene and then counting them or by establishing a mapping between some scene feature and the number of people (avoiding the complex detection problem). This paper presents a novel method, following this second approach, that is based on the use of SURF features and of an [InlineEquation not available: see fulltext.]-SVR regressor provide an estimate of this count. The algorithm takes specifically into account problems due to partial occlusions and to perspective. In the experimental evaluation, the proposed method has been compared with the algorithm by Albiol et al., winner of the PETS 2009 contest on people counting, using the same PETS 2009 database. The provided results confirm that the proposed method yields an improved accuracy, while retaining the robustness of Albiol's algorithm.

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.

Vehicle-network defensive aids suite

NASA Astrophysics Data System (ADS)

Rapanotti, John

2005-05-01

Defensive Aids Suites (DAS) developed for vehicles can be extended to the vehicle network level. The vehicle network, typically comprising four platoon vehicles, will benefit from improved communications and automation based on low latency response to threats from a flexible, dynamic, self-healing network environment. Improved DAS performance and reliability relies on four complementary sensor technologies including: acoustics, visible and infrared optics, laser detection and radar. Long-range passive threat detection and avoidance is based on dual-purpose optics, primarily designed for manoeuvring, targeting and surveillance, combined with dazzling, obscuration and countermanoeuvres. Short-range active armour is based on search and track radar and intercepting grenades to defeat the threat. Acoustic threat detection increases the overall robustness of the DAS and extends the detection range to include small calibers. Finally, detection of active targeting systems is carried out with laser and radar warning receivers. Synthetic scene generation will provide the integrated environment needed to investigate, develop and validate these new capabilities. Computer generated imagery, based on validated models and an acceptable set of benchmark vignettes, can be used to investigate and develop fieldable sensors driven by real-time algorithms and countermeasure strategies. The synthetic scene environment will be suitable for sensor and countermeasure development in hardware-in-the-loop simulation. The research effort focuses on two key technical areas: a) computing aspects of the synthetic scene generation and b) and development of adapted models and databases. OneSAF is being developed for research and development, in addition to the original requirement of Simulation and Modelling for Acquisition, Rehearsal, Requirements and Training (SMARRT), and is becoming useful as a means for transferring technology to other users, researchers and contractors. This procedure eliminates the need to construct ad hoc models and databases. The vehicle network can be modelled phenomenologically until more information is available. These concepts and approach will be discussed in the paper.

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.

Mathematics of Sensing, Exploitation, and Execution (MSEE) Hierarchical Representations for the Evaluation of Sensed Data

DTIC Science & Technology

2016-06-01

theories of the mammalian visual system, and exploiting descriptive text that may accompany a still image for improved inference. The focus of the Brown...test, computer vision, semantic description , street scenes, belief propagation, generative models, nonlinear filtering, sufficient statistics 16...visual system, and exploiting descriptive text that may accompany a still image for improved inference. The focus of the Brown team was on single images

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.

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…

Autonomous Science on the EO-1 Mission

NASA Technical Reports Server (NTRS)

Chien, S.; Sherwood, R.; Tran, D.; Castano, R.; Cichy, B.; Davies, A.; Rabideau, G.; Tang, N.; Burl, M.; Mandl, D.;

Railway clearance intrusion detection method with binocular stereo vision

NASA Astrophysics Data System (ADS)

Zhou, Xingfang; Guo, Baoqing; Wei, Wei

2018-03-01

In the stage of railway construction and operation, objects intruding railway clearance greatly threaten the safety of railway operation. Real-time intrusion detection is of great importance. For the shortcomings of depth insensitive and shadow interference of single image method, an intrusion detection method with binocular stereo vision is proposed to reconstruct the 3D scene for locating the objects and judging clearance intrusion. The binocular cameras are calibrated with Zhang Zhengyou's method. In order to improve the 3D reconstruction speed, a suspicious region is firstly determined by background difference method of a single camera's image sequences. The image rectification, stereo matching and 3D reconstruction process are only executed when there is a suspicious region. A transformation matrix from Camera Coordinate System(CCS) to Track Coordinate System(TCS) is computed with gauge constant and used to transfer the 3D point clouds into the TCS, then the 3D point clouds are used to calculate the object position and intrusion in TCS. The experiments in railway scene show that the position precision is better than 10mm. It is an effective way for clearance intrusion detection and can satisfy the requirement of railway application.

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

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.

Electronic aroma detection technology for forensic and law enforcement applications

NASA Astrophysics Data System (ADS)

Barshick, Stacy-Ann; Griest, Wayne H.; Vass, Arpad A.

1997-02-01

A major problem hindering criminal investigations is the lack of appropriate tools for proper crime scene investigations. Often locating important pieces of evidence means relying on the ability of trained detection canines. Development of analytical technology to uncover and analyze evidence, potentially at the scene, could serve to expedite criminal investigations, searches, and court proceedings. To address this problem, a new technology based on gas sensor arrays was investigated for its applicability to forensic and law enforcement problems. The technology employs an array of sensors that respond to volatile chemical components yielding a characteristic 'fingerprint' pattern representative of the vapor-phase composition of a sample. Sample aromas can be analyzed and identified using artificial neural networks that are trained on known aroma patterns. Several candidate applications based on known technological needs of the forensic and law enforcement communities have been investigated. These applications have included the detection of aromas emanating from cadavers to aid in determining time since death, drug detection for deterring the manufacture, sale, and use of drugs of abuse, and the analysis of fire debris for accelerant identification. The result to date for these applications have been extremely promising and demonstrate the potential applicability of this technology for forensic use.

Hyperspectral target detection using manifold learning and multiple target spectra

DOE PAGES

Ziemann, Amanda K.; Theiler, James; Messinger, David W.

2016-03-31

Imagery collected from satellites and airborne platforms provides an important tool for remotely analyzing the content of a scene. In particular, the ability to remotely detect a specific material within a scene is of critical importance in nonproliferation and other applications. The sensor systems that process hyperspectral images collect the high-dimensional spectral information necessary to perform these detection analyses. For a d-dimensional hyperspectral image, however, where d is the number of spectral bands, it is common for the data to inherently occupy an m-dimensional space with m << d. In the remote sensing community, this has led to recent interestmore » in the use of manifold learning, which seeks to characterize the embedded lower-dimensional, nonlinear manifold that the data discretely approximate. The research presented in this paper focuses on a graph theory and manifold learning approach to target detection, using an adaptive version of locally linear embedding that is biased to separate target pixels from background pixels. Finally, this approach incorporates multiple target signatures for a particular material, accounting for the spectral variability that is often present within a solid material of interest.« less

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.

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

Anomaly Detection Based on Local Nearest Neighbor Distance Descriptor in Crowded Scenes

PubMed Central

Hu, Shiqiang; Zhang, Huanlong; Luo, Lingkun

2014-01-01

We propose a novel local nearest neighbor distance (LNND) descriptor for anomaly detection in crowded scenes. Comparing with the commonly used low-level feature descriptors in previous works, LNND descriptor has two major advantages. First, LNND descriptor efficiently incorporates spatial and temporal contextual information around the video event that is important for detecting anomalous interaction among multiple events, while most existing feature descriptors only contain the information of single event. Second, LNND descriptor is a compact representation and its dimensionality is typically much lower than the low-level feature descriptor. Therefore, not only the computation time and storage requirement can be accordingly saved by using LNND descriptor for the anomaly detection method with offline training fashion, but also the negative aspects caused by using high-dimensional feature descriptor can be avoided. We validate the effectiveness of LNND descriptor by conducting extensive experiments on different benchmark datasets. Experimental results show the promising performance of LNND-based method against the state-of-the-art methods. It is worthwhile to notice that the LNND-based approach requires less intermediate processing steps without any subsequent processing such as smoothing but achieves comparable event better performance. PMID:25105164

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.

Bringing color to emotion: The influence of color on attentional bias to briefly presented emotional images.

PubMed

Bekhtereva, Valeria; Müller, Matthias M

2017-10-01

Is color a critical feature in emotional content extraction and involuntary attentional orienting toward affective stimuli? Here we used briefly presented emotional distractors to investigate the extent to which color information can influence the time course of attentional bias in early visual cortex. While participants performed a demanding visual foreground task, complex unpleasant and neutral background images were displayed in color or grayscale format for a short period of 133 ms and were immediately masked. Such a short presentation poses a challenge for visual processing. In the visual detection task, participants attended to flickering squares that elicited the steady-state visual evoked potential (SSVEP), allowing us to analyze the temporal dynamics of the competition for processing resources in early visual cortex. Concurrently we measured the visual event-related potentials (ERPs) evoked by the unpleasant and neutral background scenes. The results showed (a) that the distraction effect was greater with color than with grayscale images and (b) that it lasted longer with colored unpleasant distractor images. Furthermore, classical and mass-univariate ERP analyses indicated that, when presented in color, emotional scenes elicited more pronounced early negativities (N1-EPN) relative to neutral scenes, than when the scenes were presented in grayscale. Consistent with neural data, unpleasant scenes were rated as being more emotionally negative and received slightly higher arousal values when they were shown in color than when they were presented in grayscale. Taken together, these findings provide evidence for the modulatory role of picture color on a cascade of coordinated perceptual processes: by facilitating the higher-level extraction of emotional content, color influences the duration of the attentional bias to briefly presented affective scenes in lower-tier visual areas.

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/.

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.

Deep-cascade: Cascading 3D Deep Neural Networks for Fast Anomaly Detection and Localization in Crowded Scenes.

PubMed

Sabokrou, Mohammad; Fayyaz, Mohsen; Fathy, Mahmood; Klette, Reinhard

2017-02-17

This paper proposes a fast and reliable method for anomaly detection and localization in video data showing crowded scenes. Time-efficient anomaly localization is an ongoing challenge and subject of this paper. We propose a cubicpatch- based method, characterised by a cascade of classifiers, which makes use of an advanced feature-learning approach. Our cascade of classifiers has two main stages. First, a light but deep 3D auto-encoder is used for early identification of "many" normal cubic patches. This deep network operates on small cubic patches as being the first stage, before carefully resizing remaining candidates of interest, and evaluating those at the second stage using a more complex and deeper 3D convolutional neural network (CNN). We divide the deep autoencoder and the CNN into multiple sub-stages which operate as cascaded classifiers. Shallow layers of the cascaded deep networks (designed as Gaussian classifiers, acting as weak single-class classifiers) detect "simple" normal patches such as background patches, and more complex normal patches are detected at deeper layers. It is shown that the proposed novel technique (a cascade of two cascaded classifiers) performs comparable to current top-performing detection and localization methods on standard benchmarks, but outperforms those in general with respect to required computation time.

Feedforward and recurrent processing in scene segmentation: electroencephalography and functional magnetic resonance imaging.

PubMed

Scholte, H Steven; Jolij, Jacob; Fahrenfort, Johannes J; Lamme, Victor A F

2008-11-01

In texture segregation, an example of scene segmentation, we can discern two different processes: texture boundary detection and subsequent surface segregation [Lamme, V. A. F., Rodriguez-Rodriguez, V., & Spekreijse, H. Separate processing dynamics for texture elements, boundaries and surfaces in primary visual cortex of the macaque monkey. Cerebral Cortex, 9, 406-413, 1999]. Neural correlates of texture boundary detection have been found in monkey V1 [Sillito, A. M., Grieve, K. L., Jones, H. E., Cudeiro, J., & Davis, J. Visual cortical mechanisms detecting focal orientation discontinuities. Nature, 378, 492-496, 1995; Grosof, D. H., Shapley, R. M., & Hawken, M. J. Macaque-V1 neurons can signal illusory contours. Nature, 365, 550-552, 1993], but whether surface segregation occurs in monkey V1 [Rossi, A. F., Desimone, R., & Ungerleider, L. G. Contextual modulation in primary visual cortex of macaques. Journal of Neuroscience, 21, 1698-1709, 2001; Lamme, V. A. F. The neurophysiology of figure ground segregation in primary visual-cortex. Journal of Neuroscience, 15, 1605-1615, 1995], and whether boundary detection or surface segregation signals can also be measured in human V1, is more controversial [Kastner, S., De Weerd, P., & Ungerleider, L. G. Texture segregation in the human visual cortex: A functional MRI study. Journal of Neurophysiology, 83, 2453-2457, 2000]. Here we present electroencephalography (EEG) and functional magnetic resonance imaging data that have been recorded with a paradigm that makes it possible to differentiate between boundary detection and scene segmentation in humans. In this way, we were able to show with EEG that neural correlates of texture boundary detection are first present in the early visual cortex around 92 msec and then spread toward the parietal and temporal lobes. Correlates of surface segregation first appear in temporal areas (around 112 msec) and from there appear to spread to parietal, and back to occipital areas. After 208 msec, correlates of surface segregation and boundary detection also appear in more frontal areas. Blood oxygenation level-dependent magnetic resonance imaging results show correlates of boundary detection and surface segregation in all early visual areas including V1. We conclude that texture boundaries are detected in a feedforward fashion and are represented at increasing latencies in higher visual areas. Surface segregation, on the other hand, is represented in "reverse hierarchical" fashion and seems to arise from feedback signals toward early visual areas such as V1.

Dancing with Words: Transference and Countertransference in Biblio/Poetry Therapy.

ERIC Educational Resources Information Center

Ihanus, Juhani

1998-01-01

Argues that within biblio/poetry therapy, self and others are invented through expressive resources inherent in language. Shows how poetic communication conveys, through texts, "transformative" transferences and countertransferences that foster creative imagination. Sees biblio/poetry therapy as a performance scene where co-tellings,…

The Administration of Outdoor Education Programs.

ERIC Educational Resources Information Center

Lewis, Charles A., Jr.

Designed for those interested in the mechanics of establishing outdoor education programs, this text is basically a guide to program development and includes examples of procedures, forms, conceptualizations, etc. Chapters deal with: (1) the contemporary education scene (an overview); (2) the basic concepts of outdoor education (17 concept…

Unlocking the Mysteries of Ancient Egypt.

ERIC Educational Resources Information Center

Riechers, Maggie

1995-01-01

Describes the work of Egyptologist William Murnane who is recording the ritual scenes and inscriptions of a great columned hall from the days of the pharaohs. The 134 columns, covered with divine imagery and hieroglyphic inscriptions represent an unpublished religious text. Briefly discusses ancient Egyptian culture. Includes several photographs…

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.

Search by photo methodology for signature properties assessment by human observers

NASA Astrophysics Data System (ADS)

Selj, Gorm K.; Heinrich, Daniela H.

2015-05-01

Reliable, low-cost and simple methods for assessment of signature properties for military purposes are very important. In this paper we present such an approach that uses human observers in a search by photo assessment of signature properties of generic test targets. The method was carried out by logging a large number of detection times of targets recorded in relevant terrain backgrounds. The detection times were harvested by using human observers searching for targets in scene images shown by a high definition pc screen. All targets were identically located in each "search image", allowing relative comparisons (and not just rank by order) of targets. To avoid biased detections, each observer only searched for one target per scene. Statistical analyses were carried out for the detection times data. Analysis of variance was chosen if detection times distribution associated with all targets satisfied normality, and non-parametric tests, such as Wilcoxon's rank test, if otherwise. The new methodology allows assessment of signature properties in a reproducible, rapid and reliable setting. Such assessments are very complex as they must sort out what is of relevance in a signature test, but not loose information of value. We believe that choosing detection times as the primary variable for a comparison of signature properties, allows a careful and necessary inspection of observer data as the variable is continuous rather than discrete. Our method thus stands in opposition to approaches based on detections by subsequent, stepwise reductions in distance to target, or based on probability of detection.

"IREP EN KEMET" Wine of Ancient Egypt: Documenting the Viticulture and Winemaking Scenes in the Egyptian Tombs

NASA Astrophysics Data System (ADS)

Guasch-Jané, M. R.; Fonseca, S.; Ibrahim, M.

2013-07-01

Presented are the research objectives of the project "Irep en Kemet", Wine of Ancient Egypt, and the content of the project's website. This research aims at documenting the complete corpus of wine in ancient Egypt and analysing the data (iconography, textual sources and artefacts) to unveil the importance of the ancient Egyptian wine culture legacy in the Mediterranean region. At this stage, a bibliographical researchable database relevant to wine, viticulture and winemaking in the ancient Egypt has been completed, with 197 entries including articles, books, chapters in book, academic thesis (PhD and MA), essay, abstracts, on-line articles and websites. Moreover, a scene-detail database for the viticulture and winemaking scenes in the Egyptian private tombs has been recorded with 97 entries, some of them unpublished, and the collected data is under study. The titles of the tombs' owners and the texts related to the scenes will be also recorded. A photographic survey of the graves containing images related with viticulture and winemaking will be carried out in order to have the most accurate information on the location and stage of conservation of those images. Our main goal is to provide scholars with a complete, comprehensive archaeological and bibliographical database for the scenes of viticulture and winemaking depicted in the Egyptian private tombs throughout the ancient Egyptian history. The project's website (http://www.wineofancientegypt.com) will include all the collected data, the study and analysis, the project's history and team members, publications as well as the results of our research.

Science and Criminal Investigation.

ERIC Educational Resources Information Center

Johnson, Ronald

1997-01-01

Presents a science activity that integrates the disciplines of anatomy, physiology, genetics, and forensics in which students act as detectives unraveling evidence at a murder crime scene. This project is designed to enhance student interest by providing immediate application of these disciplines. (DKM)

Deep learning based hand gesture recognition in complex scenes

NASA Astrophysics Data System (ADS)

Ni, Zihan; Sang, Nong; Tan, Cheng

2018-03-01

Recently, region-based convolutional neural networks(R-CNNs) have achieved significant success in the field of object detection, but their accuracy is not too high for small objects and similar objects, such as the gestures. To solve this problem, we present an online hard example testing(OHET) technology to evaluate the confidence of the R-CNNs' outputs, and regard those outputs with low confidence as hard examples. In this paper, we proposed a cascaded networks to recognize the gestures. Firstly, we use the region-based fully convolutional neural network(R-FCN), which is capable of the detection for small object, to detect the gestures, and then use the OHET to select the hard examples. To enhance the accuracy of the gesture recognition, we re-classify the hard examples through VGG-19 classification network to obtain the final output of the gesture recognition system. Through the contrast experiments with other methods, we can see that the cascaded networks combined with the OHET reached to the state-of-the-art results of 99.3% mAP on small and similar gestures in complex scenes.

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.

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.

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.

Attribution of Spear Phishing Attacks: A Literature Survey

DTIC Science & Technology

2013-08-01

header of an email, verbally informed by another person, or easily ascertained via the handwriting of the text. In a few specific cases, this...scene would be scrutinised, based on both the handwriting and the content of the letter, to identify a suspect. The goal of this phase is to establish

Spatial Updating of Environments Described in Texts

ERIC Educational Resources Information Center

Avraamides, Marios N.

2003-01-01

People update egocentric spatial relations in an effortless and on-line manner when they move in the environment, but not when they only imagine themselves moving. In contrast to previous studies, the present experiments examined egocentric updating with spatial scenes that were encoded linguistically instead of perceived directly. Experiment 1…

Internet-Accessible Scholarly Resources for the Humanities and Social Sciences.

ERIC Educational Resources Information Center

ACLS Newsletter, 1997

1997-01-01

This newsletter focuses on the presentations of a program session on Internet-accessible scholarly resources, held at the 1996 ACLS Annual Meeting. Articles in the newsletter include: "Building the Scene: Words, Images, Data, and Beyond" (David Green); "Electronic Texts: The Promise and the Reality" (Susan Hockey); "Images…

Archiving Derrida

ERIC Educational Resources Information Center

Morris, Marla

2003-01-01

Derrida's archive, broadly speaking, is brilliantly mad, for he digs exegetically into the most difficult textual material and combines the most unlikely texts--from Socrates to Freud, from postcards to encyclopedias, from madness(es) to the archive, from primal scenes to death. In this paper, the author would like to do a brief study of the…

Detection and Identification of Acoustic Signatures

DTIC Science & Technology

2011-08-01

represent complex scenarios such as urban scenes with multiple sources in the soundscape and significant amount of reverberation and diffraction effects... soundscape . In either case it is necessary to understand that the probability of detection is a function of both the vehicle acoustic signature and...the acoustic masking component, or soundscape . And that both signals must be defined in greater depth than overall level, or average frequency

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.

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.

Effects of threshold on single-target detection by using modified amplitude-modulated joint transform correlator

NASA Astrophysics Data System (ADS)

Kaewkasi, Pitchaya; Widjaja, Joewono; Uozumi, Jun

2007-03-01

Effects of threshold value on detection performance of the modified amplitude-modulated joint transform correlator are quantitatively studied using computer simulation. Fingerprint and human face images are used as test scenes in the presence of noise and a contrast difference. Simulation results demonstrate that this correlator improves detection performance for both types of image used, but moreso for human face images. Optimal detection of low-contrast human face images obscured by strong noise can be obtained by selecting an appropriate threshold value.

Ultrafast scene detection and recognition with limited visual information

PubMed Central

Hagmann, Carl Erick; Potter, Mary C.

2016-01-01

Humans can detect target color pictures of scenes depicting concepts like picnic or harbor in sequences of six or twelve pictures presented as briefly as 13 ms, even when the target is named after the sequence (Potter, Wyble, Hagmann, & McCourt, 2014). Such rapid detection suggests that feedforward processing alone enabled detection without recurrent cortical feedback. There is debate about whether coarse, global, low spatial frequencies (LSFs) provide predictive information to high cortical levels through the rapid magnocellular (M) projection of the visual path, enabling top-down prediction of possible object identities. To test the “Fast M” hypothesis, we compared detection of a named target across five stimulus conditions: unaltered color, blurred color, grayscale, thresholded monochrome, and LSF pictures. The pictures were presented for 13–80 ms in six-picture rapid serial visual presentation (RSVP) sequences. Blurred, monochrome, and LSF pictures were detected less accurately than normal color or grayscale pictures. When the target was named before the sequence, all picture types except LSF resulted in above-chance detection at all durations. Crucially, when the name was given only after the sequence, performance dropped and the monochrome and LSF pictures (but not the blurred pictures) were at or near chance. Thus, without advance information, monochrome and LSF pictures were rarely understood. The results offer only limited support for the Fast M hypothesis, suggesting instead that feedforward processing is able to activate conceptual representations without complementary reentrant processing. PMID:28255263

Visual-Vestibular Conflict Detection Depends on Fixation.

PubMed

Garzorz, Isabelle T; MacNeilage, Paul R

2017-09-25

Visual and vestibular signals are the primary sources of sensory information for self-motion. Conflict among these signals can be seriously debilitating, resulting in vertigo [1], inappropriate postural responses [2], and motion, simulator, or cyber sickness [3-8]. Despite this significance, the mechanisms mediating conflict detection are poorly understood. Here we model conflict detection simply as crossmodal discrimination with benchmark performance limited by variabilities of the signals being compared. In a series of psychophysical experiments conducted in a virtual reality motion simulator, we measure these variabilities and assess conflict detection relative to this benchmark. We also examine the impact of eye movements on visual-vestibular conflict detection. In one condition, observers fixate a point that is stationary in the simulated visual environment by rotating the eyes opposite head rotation, thereby nulling retinal image motion. In another condition, eye movement is artificially minimized via fixation of a head-fixed fixation point, thereby maximizing retinal image motion. Visual-vestibular integration performance is also measured, similar to previous studies [9-12]. We observe that there is a tradeoff between integration and conflict detection that is mediated by eye movements. Minimizing eye movements by fixating a head-fixed target leads to optimal integration but highly impaired conflict detection. Minimizing retinal motion by fixating a scene-fixed target improves conflict detection at the cost of impaired integration performance. The common tendency to fixate scene-fixed targets during self-motion [13] may indicate that conflict detection is typically a higher priority than the increase in precision of self-motion estimation that is obtained through integration. Copyright © 2017 Elsevier Ltd. All rights reserved.

Effect of Clouds on Apertures of Space-based Air Fluorescence Detectors

NASA Technical Reports Server (NTRS)

Sokolsky, P.; Krizmanic, J.

2003-01-01

Space-based ultra-high-energy cosmic ray detectors observe fluorescence light from extensive air showers produced by these particles in the troposphere. Clouds can scatter and absorb this light and produce systematic errors in energy determination and spectrum normalization. We study the possibility of using IR remote sensing data from MODIS and GOES satellites to delimit clear areas of the atmosphere. The efficiency for detecting ultra-high-energy cosmic rays whose showers do not intersect clouds is determined for real, night-time cloud scenes. We use the MODIS SST cloud mask product to define clear pixels for cloud scenes along the equator and use the OWL Monte Carlo to generate showers in the cloud scenes. We find the efficiency for cloud-free showers with closest approach of three pixels to a cloudy pixel is 6.5% exclusive of other factors. We conclude that defining a totally cloud-free aperture reduces the sensitivity of space-based fluorescence detectors to unacceptably small levels.

Large Capacity of Conscious Access for Incidental Memories in Natural Scenes.

PubMed

Kaunitz, Lisandro N; Rowe, Elise G; Tsuchiya, Naotsugu

2016-09-01

When searching a crowd, people can detect a target face only by direct fixation and attention. Once the target is found, it is consciously experienced and remembered, but what is the perceptual fate of the fixated nontarget faces? Whereas introspection suggests that one may remember nontargets, previous studies have proposed that almost no memory should be retained. Using a gaze-contingent paradigm, we asked subjects to visually search for a target face within a crowded natural scene and then tested their memory for nontarget faces, as well as their confidence in those memories. Subjects remembered up to seven fixated, nontarget faces with more than 70% accuracy. Memory accuracy was correlated with trial-by-trial confidence ratings, which implies that the memory was consciously maintained and accessed. When the search scene was inverted, no more than three nontarget faces were remembered. These findings imply that incidental memory for faces, such as those recalled by eyewitnesses, is more reliable than is usually assumed. © The Author(s) 2016.

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.

4D light-field sensing system for people counting

NASA Astrophysics Data System (ADS)

Hou, Guangqi; Zhang, Chi; Wang, Yunlong; Sun, Zhenan

2016-03-01

Counting the number of people is still an important task in social security applications, and a few methods based on video surveillance have been proposed in recent years. In this paper, we design a novel optical sensing system to directly acquire the depth map of the scene from one light-field camera. The light-field sensing system can count the number of people crossing the passageway, and record the direction and intensity of rays at a snapshot without any assistant light devices. Depth maps are extracted from the raw light-ray sensing data. Our smart sensing system is equipped with a passive imaging sensor, which is able to naturally discern the depth difference between the head and shoulders for each person. Then a human model is built. Through detecting the human model from light-field images, the number of people passing the scene can be counted rapidly. We verify the feasibility of the sensing system as well as the accuracy by capturing real-world scenes passing single and multiple people under natural illumination.

Thematic mapper data quality and performance assessment in renewable resource/agricultural remote sensing

NASA Technical Reports Server (NTRS)

Erickson, J. D.; Macdonald, R. B. (Principal Investigator)

1982-01-01

A "quick look" investigation of the initial LANDSAT-4, thematic mapper (TM) scene received from Goddard Space Flight Center was performed to gain early insight into the characteristics of TM data. The initial scene, containing only the first four bands of the seven bands recorded by the TM, was acquired over the Detroit, Michigan, area on July 20, 1982. It yielded abundant information for scientific investigation. A wide variety of studies were conducted to assess all aspects of TM data. They ranged from manual analyses of image products to detect obvious optical, electronic, or mechanical defects to detailed machine analyses of the digital data content for evaluation of spectral separability of vegetative/nonvegetative classes. These studies were applied to several segments extracted from the full scene. No attempt was made to perform end-to-end statistical evaluations. However, the output of these studies do identify a degree of positive performance from the TM and its potential for advancing state-of-the-art crop inventory and condition assessment technology.

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.

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.

A particle filter for multi-target tracking in track before detect context

NASA Astrophysics Data System (ADS)

Amrouche, Naima; Khenchaf, Ali; Berkani, Daoud

2016-10-01

The track-before-detect (TBD) approach can be used to track a single target in a highly noisy radar scene. This is because it makes use of unthresholded observations and incorporates a binary target existence variable into its target state estimation process when implemented as a particle filter (PF). This paper proposes the recursive PF-TBD approach to detect multiple targets in low-signal-to noise ratios (SNR). The algorithm's successful performance is demonstrated using a simulated two target example.

Finding and recognizing objects in natural scenes: complementary computations in the dorsal and ventral visual systems

PubMed Central

Rolls, Edmund T.; Webb, Tristan J.

2014-01-01

Searching for and recognizing objects in complex natural scenes is implemented by multiple saccades until the eyes reach within the reduced receptive field sizes of inferior temporal cortex (IT) neurons. We analyze and model how the dorsal and ventral visual streams both contribute to this. Saliency detection in the dorsal visual system including area LIP is modeled by graph-based visual saliency, and allows the eyes to fixate potential objects within several degrees. Visual information at the fixated location subtending approximately 9° corresponding to the receptive fields of IT neurons is then passed through a four layer hierarchical model of the ventral cortical visual system, VisNet. We show that VisNet can be trained using a synaptic modification rule with a short-term memory trace of recent neuronal activity to capture both the required view and translation invariances to allow in the model approximately 90% correct object recognition for 4 objects shown in any view across a range of 135° anywhere in a scene. The model was able to generalize correctly within the four trained views and the 25 trained translations. This approach analyses the principles by which complementary computations in the dorsal and ventral visual cortical streams enable objects to be located and recognized in complex natural scenes. PMID:25161619

The ToMenovela – A Photograph-Based Stimulus Set for the Study of Social Cognition with High Ecological Validity

PubMed Central

Herbort, Maike C.; Iseev, Jenny; Stolz, Christopher; Roeser, Benedict; Großkopf, Nora; Wüstenberg, Torsten; Hellweg, Rainer; Walter, Henrik; Dziobek, Isabel; Schott, Björn H.

2016-01-01

We present the ToMenovela, a stimulus set that has been developed to provide a set of normatively rated socio-emotional stimuli showing varying amount of characters in emotionally laden interactions for experimental investigations of (i) cognitive and (ii) affective Theory of Mind (ToM), (iii) emotional reactivity, and (iv) complex emotion judgment with respect to Ekman’s basic emotions (happiness, anger, disgust, fear, sadness, surprise, Ekman and Friesen, 1975). Stimuli were generated with focus on ecological validity and consist of 190 scenes depicting daily-life situations. Two or more of eight main characters with distinct biographies and personalities are depicted on each scene picture. To obtain an initial evaluation of the stimulus set and to pave the way for future studies in clinical populations, normative data on each stimulus of the set was obtained from a sample of 61 neurologically and psychiatrically healthy participants (31 female, 30 male; mean age 26.74 ± 5.84), including a visual analog scale rating of Ekman’s basic emotions (happiness, anger, disgust, fear, sadness, surprise) and free-text descriptions of the content of each scene. The ToMenovela is being developed to provide standardized material of social scenes that are available to researchers in the study of social cognition. It should facilitate experimental control while keeping ecological validity high. PMID:27994562

The Cuban Missile Crisis: Considering Its Place in Cold War History. Teacher's Resource Book [and Student Text]. Public Policy Debate in the Classroom. Choices for the 21st Century Education Project. 4th Edition.

ERIC Educational Resources Information Center

Soukup, Nancy, Ed.

Like no other region on the globe, the Caribbean Basin has served as a testing ground for U.S. foreign policy. Of all the countries in the region, Cuba has been the scene of many of the United States' most riveting foreign policy dramas. The teacher resource book and student text probe the complex, often troubled, relationship between the United…

The Effect of Illustration on Improving Text Comprehension in Dyslexic Adults

PubMed Central

Wennås Brante, Eva; Nyström, Marcus

2016-01-01

This study analyses the effect of pictures in reading materials on the viewing patterns of dyslexic adults. By analysing viewing patterns using eye‐tracking, we captured differences in eye movements between young adults with dyslexia and controls based on the influence of reading skill as a continuous variable of the total sample. Both types of participants were assigned randomly to view either text‐only or a text + picture stimuli. The results show that the controls made an early global overview of the material and (when a picture was present) rapid transitions between text and picture. Having text illustrated with a picture decreased scores on questions about the learning material among participants with dyslexia. Controls spent 1.7% and dyslexic participants 1% of their time on the picture. Controls had 24% fewer total fixations; however, 29% more of the control group's fixations than the dyslexic group's fixations were on the picture. We also looked for effects of different types of pictures. Dyslexic subjects exhibited a comparable viewing pattern to controls when scenes were complex, but fewer fixations when scenes were neutral/simple. Individual scan paths are presented as examples of atypical viewing patterns for individuals with dyslexia as compared with controls. © 2016 The Authors. Dyslexia published by John Wiley & Sons Ltd. PMID:27892641

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

Larson, Richard; Branch, Darren; Edwards, Thayne

The acoustic wave biosensor is innovative device that is a handheld, battery-powered, portable detection system capable of multiplex identification of a wide range of medically relevant pathogens and their biomolecular signatures — viruses, bacteria, proteins, and DNA — at clinically relevant levels. This detection occurs within minutes — not hours — at the point of care, whether that care is in a physician's office, a hospital bed, or at the scene of a biodefense or biomedical emergency.

Perceptual load in different regions of the visual scene and its relevance for driving.

PubMed

Marciano, Hadas; Yeshurun, Yaffa

2015-06-01

The aim of this study was to better understand the role played by perceptual load, at both central and peripheral regions of the visual scene, in driving safety. Attention is a crucial factor in driving safety, and previous laboratory studies suggest that perceptual load is an important factor determining the efficiency of attentional selectivity. Yet, the effects of perceptual load on driving were never studied systematically. Using a driving simulator, we orthogonally manipulated the load levels at the road (central load) and its sides (peripheral load), while occasionally introducing critical events at one of these regions. Perceptual load affected driving performance at both regions of the visual scene. Critically, the effect was different for central versus peripheral load: Whereas load levels on the road mainly affected driving speed, load levels on its sides mainly affected the ability to detect critical events initiating from the roadsides. Moreover, higher levels of peripheral load impaired performance but mainly with low levels of central load, replicating findings with simple letter stimuli. Perceptual load has a considerable effect on driving, but the nature of this effect depends on the region of the visual scene at which the load is introduced. Given the observed importance of perceptual load, authors of future studies of driving safety should take it into account. Specifically, these findings suggest that our understanding of factors that may be relevant for driving safety would benefit from studying these factors under different levels of load at different regions of the visual scene. © 2014, Human Factors and Ergonomics Society.

Neural Correlates of Divided Attention in Natural Scenes.

PubMed

Fagioli, Sabrina; Macaluso, Emiliano

2016-09-01

Individuals are able to split attention between separate locations, but divided spatial attention incurs the additional requirement of monitoring multiple streams of information. Here, we investigated divided attention using photos of natural scenes, where the rapid categorization of familiar objects and prior knowledge about the likely positions of objects in the real world might affect the interplay between these spatial and nonspatial factors. Sixteen participants underwent fMRI during an object detection task. They were presented with scenes containing either a person or a car, located on the left or right side of the photo. Participants monitored either one or both object categories, in one or both visual hemifields. First, we investigated the interplay between spatial and nonspatial attention by comparing conditions of divided attention between categories and/or locations. We then assessed the contribution of top-down processes versus stimulus-driven signals by separately testing the effects of divided attention in target and nontarget trials. The results revealed activation of a bilateral frontoparietal network when dividing attention between the two object categories versus attending to a single category but no main effect of dividing attention between spatial locations. Within this network, the left dorsal premotor cortex and the left intraparietal sulcus were found to combine task- and stimulus-related signals. These regions showed maximal activation when participants monitored two categories at spatially separate locations and the scene included a nontarget object. We conclude that the dorsal frontoparietal cortex integrates top-down and bottom-up signals in the presence of distractors during divided attention in real-world scenes.

Hard Lines and Soft Scenes: Constituting Masculinities in the Prospectuses of All-Boys Elite Private Schools

ERIC Educational Resources Information Center

Gottschall, Kristina; Wardman, Natasha; Edgeworth, Kathryn; Hutchesson, Rachael; Saltmarsh, Sue

2010-01-01

Over the last decade, education researchers have been concerned with the "impression management" activities of schools in the current climate of school corporatisation. Among these activities is the dissemination of school prospectuses that, far from being merely arbitrary sources of information, are seen as strategic texts that…

Applications of multi-spectral imaging: failsafe industrial flame detector

NASA Astrophysics Data System (ADS)

Wing Au, Kwong; Larsen, Christopher; Cole, Barry; Venkatesha, Sharath

2016-05-01

Industrial and petrochemical facilities present unique challenges for fire protection and safety. Typical scenarios include detection of an unintended fire in a scene, wherein the scene also includes a flare stack in the background. Maintaining a high level of process and plant safety is a critical concern. In this paper, we present a failsafe industrial flame detector which has significant performance benefits compared to current flame detectors. The design involves use of microbolometer in the MWIR and LWIR spectrum and a dual band filter. This novel flame detector can help industrial facilities to meet their plant safety and critical infrastructure protection requirements while ensuring operational and business readiness at project start-up.

[Development of a wearable electrocardiogram monitor with recognition of physical activity scene].

PubMed

Wang, Zihong; Wu, Baoming; Yin, Jian; Gong, Yushun

2012-10-01

To overcome the problems of current electrocardiogram (ECG) tele-monitoring devices used for daily life, according to information fusion thought and by means of wearable technology, we developed a new type of wearable ECG monitor with the capability of physical activity recognition in this paper. The ECG monitor synchronously detected electrocardiogram signal and body acceleration signal, and recognized the scene information of physical activity, and finally determined the health status of the heart. With the advantages of accuracy for measurement, easy to use, comfort to wear, private feelings and long-term continuous in monitoring, this ECG monitor is quite fit for the heart-health monitoring in daily life.

Predicting Good Features for Image Geo-Localization Using Per-Bundle VLAD (Open Access)

DTIC Science & Technology

2016-02-18

transient scene elements (pedestrians, cars, billboards) and ubiquitous objects (trees, fences, signage ) can introduce obfuscating cues into the geo...windows, charac- teristic wall patterns, and letters on signage are detected as positive elements, while features from trees, people, car wheels

Automatic markerless registration of point clouds with semantic-keypoint-based 4-points congruent sets

NASA Astrophysics Data System (ADS)

Ge, Xuming

2017-08-01

The coarse registration of point clouds from urban building scenes has become a key topic in applications of terrestrial laser scanning technology. Sampling-based algorithms in the random sample consensus (RANSAC) model have emerged as mainstream solutions to address coarse registration problems. In this paper, we propose a novel combined solution to automatically align two markerless point clouds from building scenes. Firstly, the method segments non-ground points from ground points. Secondly, the proposed method detects feature points from each cross section and then obtains semantic keypoints by connecting feature points with specific rules. Finally, the detected semantic keypoints from two point clouds act as inputs to a modified 4PCS algorithm. Examples are presented and the results compared with those of K-4PCS to demonstrate the main contributions of the proposed method, which are the extension of the original 4PCS to handle heavy datasets and the use of semantic keypoints to improve K-4PCS in relation to registration accuracy and computational efficiency.

Three-camera stereo vision for intelligent transportation systems

NASA Astrophysics Data System (ADS)

Bergendahl, Jason; Masaki, Ichiro; Horn, Berthold K. P.

1997-02-01

A major obstacle in the application of stereo vision to intelligent transportation system is high computational cost. In this paper, a PC based three-camera stereo vision system constructed with off-the-shelf components is described. The system serves as a tool for developing and testing robust algorithms which approach real-time performance. We present an edge based, subpixel stereo algorithm which is adapted to permit accurate distance measurements to objects in the field of view using a compact camera assembly. Once computed, the 3D scene information may be directly applied to a number of in-vehicle applications, such as adaptive cruise control, obstacle detection, and lane tracking. Moreover, since the largest computational costs is incurred in generating the 3D scene information, multiple applications that leverage this information can be implemented in a single system with minimal cost. On-road applications, such as vehicle counting and incident detection, are also possible. Preliminary in-vehicle road trial results are presented.

Space Subdivision in Indoor Mobile Laser Scanning Point Clouds Based on Scanline Analysis.

PubMed

Zheng, Yi; Peter, Michael; Zhong, Ruofei; Oude Elberink, Sander; Zhou, Quan

2018-06-05

Indoor space subdivision is an important aspect of scene analysis that provides essential information for many applications, such as indoor navigation and evacuation route planning. Until now, most proposed scene understanding algorithms have been based on whole point clouds, which has led to complicated operations, high computational loads and low processing speed. This paper presents novel methods to efficiently extract the location of openings (e.g., doors and windows) and to subdivide space by analyzing scanlines. An opening detection method is demonstrated that analyses the local geometric regularity in scanlines to refine the extracted opening. Moreover, a space subdivision method based on the extracted openings and the scanning system trajectory is described. Finally, the opening detection and space subdivision results are saved as point cloud labels which will be used for further investigations. The method has been tested on a real dataset collected by ZEB-REVO. The experimental results validate the completeness and correctness of the proposed method for different indoor environment and scanning paths.

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.

DNA methylation: the future of crime scene investigation?

PubMed

Gršković, Branka; Zrnec, Dario; Vicković, Sanja; Popović, Maja; Mršić, Gordan

2013-07-01

Proper detection and subsequent analysis of biological evidence is crucial for crime scene reconstruction. The number of different criminal acts is increasing rapidly. Therefore, forensic geneticists are constantly on the battlefield, trying hard to find solutions how to solve them. One of the essential defensive lines in the fight against the invasion of crime is relying on DNA methylation. In this review, the role of DNA methylation in body fluid identification and other DNA methylation applications are discussed. Among other applications of DNA methylation, age determination of the donor of biological evidence, analysis of the parent-of-origin specific DNA methylation markers at imprinted loci for parentage testing and personal identification, differentiation between monozygotic twins due to their different DNA methylation patterns, artificial DNA detection and analyses of DNA methylation patterns in the promoter regions of circadian clock genes are the most important ones. Nevertheless, there are still a lot of open chapters in DNA methylation research that need to be closed before its final implementation in routine forensic casework.

Distributed Scene Analysis For Autonomous Road Vehicle Guidance

NASA Astrophysics Data System (ADS)

Mysliwetz, Birger D.; Dickmanns, E. D.

1987-01-01

An efficient distributed processing scheme has been developed for visual road boundary tracking by 'VaMoRs', a testbed vehicle for autonomous mobility and computer vision. Ongoing work described here is directed to improving the robustness of the road boundary detection process in the presence of shadows, ill-defined edges and other disturbing real world effects. The system structure and the techniques applied for real-time scene analysis are presented along with experimental results. All subfunctions of road boundary detection for vehicle guidance, such as edge extraction, feature aggregation and camera pointing control, are executed in parallel by an onboard multiprocessor system. On the image processing level local oriented edge extraction is performed in multiple 'windows', tighly controlled from a hierarchically higher, modelbased level. The interpretation process involving a geometric road model and the observer's relative position to the road boundaries is capable of coping with ambiguity in measurement data. By using only selected measurements to update the model parameters even high noise levels can be dealt with and misleading edges be rejected.

Guest Editor's introduction: Special issue on distributed virtual environments

NASA Astrophysics Data System (ADS)

Lea, Rodger

1998-09-01

Distributed virtual environments (DVEs) combine technology from 3D graphics, virtual reality and distributed systems to provide an interactive 3D scene that supports multiple participants. Each participant has a representation in the scene, often known as an avatar, and is free to navigate through the scene and interact with both the scene and other viewers of the scene. Changes to the scene, for example, position changes of one avatar as the associated viewer navigates through the scene, or changes to objects in the scene via manipulation, are propagated in real time to all viewers. This ensures that all viewers of a shared scene `see' the same representation of it, allowing sensible reasoning about the scene. Early work on such environments was restricted to their use in simulation, in particular in military simulation. However, over recent years a number of interesting and potentially far-reaching attempts have been made to exploit the technology for a range of other uses, including: Social spaces. Such spaces can be seen as logical extensions of the familiar text chat space. In 3D social spaces avatars, representing participants, can meet in shared 3D scenes and in addition to text chat can use visual cues and even in some cases spatial audio. Collaborative working. A number of recent projects have attempted to explore the use of DVEs to facilitate computer-supported collaborative working (CSCW), where the 3D space provides a context and work space for collaboration. Gaming. The shared 3D space is already familiar, albeit in a constrained manner, to the gaming community. DVEs are a logical superset of existing 3D games and can provide a rich framework for advanced gaming applications. e-commerce. The ability to navigate through a virtual shopping mall and to look at, and even interact with, 3D representations of articles has appealed to the e-commerce community as it searches for the best method of presenting merchandise to electronic consumers. The technology needed to support these systems crosses a number of disciplines in computer science. These include, but are certainly not limited to, real-time graphics for the accurate and realistic representation of scenes, group communications for the efficient update of shared consistent scene data, user interface modelling to exploit the use of the 3D representation and multimedia systems technology for the delivery of streamed graphics and audio-visual data into the shared scene. It is this intersection of technologies and the overriding need to provide visual realism that places such high demands on the underlying distributed systems infrastructure and makes DVEs such fertile ground for distributed systems research. Two examples serve to show how DVE developers have exploited the unique aspects of their domain. Communications. The usual tension between latency and throughput is particularly noticeable within DVEs. To ensure the timely update of multiple viewers of a particular scene requires that such updates be propagated quickly. However, the sheer volume of changes to any one scene calls for techniques that minimize the number of distinct updates that are sent to the network. Several techniques have been used to address this tension; these include the use of multicast communications, and in particular multicast in wide-area networks to reduce actual message traffic. Multicast has been combined with general group communications to partition updates to related objects or users of a scene. A less traditional approach has been the use of dead reckoning whereby a client application that visualizes the scene calculates position updates by extrapolating movement based on previous information. This allows the system to reduce the number of communications needed to update objects that move in a stable manner within the scene. Scaling. DVEs, especially those used for social spaces, are required to support large numbers of simultaneous users in potentially large shared scenes. The desire for scalability has driven different architectural designs, for example, the use of fully distributed architectures which scale well but often suffer performance costs versus centralized and hierarchical architectures in which the inverse is true. However, DVEs have also exploited the spatial nature of their domain to address scalability and have pioneered techniques that exploit the semantics of the shared space to reduce data updates and so allow greater scalability. Several of the systems reported in this special issue apply a notion of area of interest to partition the scene and so reduce the participants in any data updates. The specification of area of interest differs between systems. One approach has been to exploit a geographical notion, i.e. a regular portion of a scene, or a semantic unit, such as a room or building. Another approach has been to define the area of interest as a spatial area associated with an avatar in the scene. The five papers in this special issue have been chosen to highlight the distributed systems aspects of the DVE domain. The first paper, on the DIVE system, described by Emmanuel Frécon and Mårten Stenius explores the use of multicast and group communication in a fully peer-to-peer architecture. The developers of DIVE have focused on its use as the basis for collaborative work environments and have explored the issues associated with maintaining and updating large complicated scenes. The second paper, by Hiroaki Harada et al, describes the AGORA system, a DVE concentrating on social spaces and employing a novel communication technique that incorporates position update and vector information to support dead reckoning. The paper by Simon Powers et al explores the application of DVEs to the gaming domain. They propose a novel architecture that separates out higher-level game semantics - the conceptual model - from the lower-level scene attributes - the dynamic model, both running on servers, from the actual visual representation - the visual model - running on the client. They claim a number of benefits from this approach, including better predictability and consistency. Wolfgang Broll discusses the SmallView system which is an attempt to provide a toolkit for DVEs. One of the key features of SmallView is a sophisticated application level protocol, DWTP, that provides support for a variety of communication models. The final paper, by Chris Greenhalgh, discusses the MASSIVE system which has been used to explore the notion of awareness in the 3D space via the concept of `auras'. These auras define an area of interest for users and support a mapping between what a user is aware of, and what data update rate the communications infrastructure can support. We hope that this selection of papers will serve to provide a clear introduction to the distributed system issues faced by the DVE community and the approaches they have taken in solving them. Finally, we wish to thank Hubert Le Van Gong for his tireless efforts in pulling together all these papers and both the referees and the authors of the papers for the time and effort in ensuring that their contributions teased out the interesting distributed systems issues for this special issue. † E-mail address: rodger@arch.sel.sony.com

Effects of Resolution, Range, and Image Contrast on Target Acquisition Performance.

PubMed

Hollands, Justin G; Terhaar, Phil; Pavlovic, Nada J

2018-05-01

We sought to determine the joint influence of resolution, target range, and image contrast on the detection and identification of targets in simulated naturalistic scenes. Resolution requirements for target acquisition have been developed based on threshold values obtained using imaging systems, when target range was fixed, and image characteristics were determined by the system. Subsequent work has examined the influence of factors like target range and image contrast on target acquisition. We varied the resolution and contrast of static images in two experiments. Participants (soldiers) decided whether a human target was located in the scene (detection task) or whether a target was friendly or hostile (identification task). Target range was also varied (50-400 m). In Experiment 1, 30 participants saw color images with a single target exemplar. In Experiment 2, another 30 participants saw monochrome images containing different target exemplars. The effects of target range and image contrast were qualitatively different above and below 6 pixels per meter of target for both tasks in both experiments. Target detection and identification performance were a joint function of image resolution, range, and contrast for both color and monochrome images. The beneficial effects of increasing resolution for target acquisition performance are greater for closer (larger) targets.

Information theoretic analysis of linear shift-invariant edge-detection operators

NASA Astrophysics Data System (ADS)

Jiang, Bo; Rahman, Zia-ur

2012-06-01

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 influences by the image gathering process. However, experiments show that the image gathering process has a profound impact on 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. We perform an end-to-end information theory based system analysis to assess linear shift-invariant edge-detection algorithms. 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 as having high performance only if the information rate from the scene to the edge image approaches its maximum possible. This goal can be achieved only by jointly optimizing all processes. Our information-theoretic assessment provides a new tool that allows us to compare different linear shift-invariant edge detectors in a common environment.

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.

Unsupervised iterative detection of land mines in highly cluttered environments.

PubMed

Batman, Sinan; Goutsias, John

2003-01-01

An unsupervised iterative scheme is proposed for land mine detection in heavily cluttered scenes. This scheme is based on iterating hybrid multispectral filters that consist of a decorrelating linear transform coupled with a nonlinear morphological detector. Detections extracted from the first pass are used to improve results in subsequent iterations. The procedure stops after a predetermined number of iterations. The proposed scheme addresses several weaknesses associated with previous adaptations of morphological approaches to land mine detection. Improvement in detection performance, robustness with respect to clutter inhomogeneities, a completely unsupervised operation, and computational efficiency are the main highlights of the method. Experimental results reveal excellent performance.

Enhanced Algorithms for EO/IR Electronic Stabilization, Clutter Suppression, and Track-Before-Detect for Multiple Low Observable Targets

NASA Astrophysics Data System (ADS)

Tartakovsky, A.; Brown, A.; Brown, J.

The paper describes the development and evaluation of a suite of advanced algorithms which provide significantly-improved capabilities for finding, fixing, and tracking multiple ballistic and flying low observable objects in highly stressing cluttered environments. The algorithms have been developed for use in satellite-based staring and scanning optical surveillance suites for applications including theatre and intercontinental ballistic missile early warning, trajectory prediction, and multi-sensor track handoff for midcourse discrimination and intercept. The functions performed by the algorithms include electronic sensor motion compensation providing sub-pixel stabilization (to 1/100 of a pixel), as well as advanced temporal-spatial clutter estimation and suppression to below sensor noise levels, followed by statistical background modeling and Bayesian multiple-target track-before-detect filtering. The multiple-target tracking is performed in physical world coordinates to allow for multi-sensor fusion, trajectory prediction, and intercept. Output of detected object cues and data visualization are also provided. The algorithms are designed to handle a wide variety of real-world challenges. Imaged scenes may be highly complex and infinitely varied -- the scene background may contain significant celestial, earth limb, or terrestrial clutter. For example, when viewing combined earth limb and terrestrial scenes, a combination of stationary and non-stationary clutter may be present, including cloud formations, varying atmospheric transmittance and reflectance of sunlight and other celestial light sources, aurora, glint off sea surfaces, and varied natural and man-made terrain features. The targets of interest may also appear to be dim, relative to the scene background, rendering much of the existing deployed software useless for optical target detection and tracking. Additionally, it may be necessary to detect and track a large number of objects in the threat cloud, and these objects may not always be resolvable in individual data frames. In the present paper, the performance of the developed algorithms is demonstrated using real-world data containing resident space objects observed from the MSX platform, with backgrounds varying from celestial to combined celestial and earth limb, with instances of extremely bright aurora clutter. Simulation results are also presented for parameterized variations in signal-to-clutter levels (down to 1/1000) and signal-to-noise levels (down to 1/6) for simulated targets against real-world terrestrial clutter backgrounds. We also discuss algorithm processing requirements and C++ software processing capabilities from our on-going MDA- and AFRL-sponsored development of an image processing toolkit (iPTK). In the current effort, the iPTK is being developed to a Technology Readiness Level (TRL) of 6 by mid-2010, in preparation for possible integration with STSS-like, SBIRS high-like and SBSS-like surveillance suites.

Detecting Planar Surfaces in Outdoor Urban Environments

DTIC Science & Technology

2008-09-01

coplanar or parallel scene points and lines. Sturm and Maybank (18) perform 3D reconstruction given user-provided coplanarity, perpendicularity, and... Maybank , S. J. A method for intactive 3d reconstruction of piercewise planar objects from single images. in BMVC, 1999, 265–274 [19] Schaffalitzky, F

A Multispectral Bidirectional Reflectance Distribution Function Study of Human Skin for Improved Dismount Detection

DTIC Science & Technology

2011-03-01

electromagnetic spectrum. With the availability of multispectral and hyperspectral systems, both spatial and spectral information for a scene are...an image. The boundary conditions for NDGRI and NDSI are set from diffuse spectral reflectance values for the range of skin types determined in [28...wearing no standard uniform and blending into the urban population. To assist with enemy detection and tracking, imaging systems that acquire spectral

Improving Visual Threat Detection: Research to Validate the Threat Detection Skills Trainer

DTIC Science & Technology

2013-08-01

potential threats present in this scene and explain the meaning and implications of these threats. You have two minutes to write a response...could be due to the nature of the tasks or to fatigue. Requiring Soldiers to write answers on multiple trials, and across similar tasks, might have...tasks will likely be significantly different from those experienced in the trainer. This would remove the writing requirement over multiple trials

Background characterization techniques for target detection using scene metrics and pattern recognition

NASA Astrophysics Data System (ADS)

Noah, Paul V.; Noah, Meg A.; Schroeder, John W.; Chernick, Julian A.

1990-09-01

The U.S. Army has a requirement to develop systems for the detection and identification of ground targets in a clutter environment. Autonomous Homing Munitions (AHM) using infrared, visible, millimeter wave and other sensors are being investigated for this application. Advanced signal processing and computational approaches using pattern recognition and artificial intelligence techniques combined with multisensor data fusion have the potential to meet the Army's requirements for next generation ARM.

Human matching performance of genuine crime scene latent fingerprints.

PubMed

Thompson, Matthew B; Tangen, Jason M; McCarthy, Duncan J

2014-02-01

There has been very little research into the nature and development of fingerprint matching expertise. Here we present the results of an experiment testing the claimed matching expertise of fingerprint examiners. Expert (n = 37), intermediate trainee (n = 8), new trainee (n = 9), and novice (n = 37) participants performed a fingerprint discrimination task involving genuine crime scene latent fingerprints, their matches, and highly similar distractors, in a signal detection paradigm. Results show that qualified, court-practicing fingerprint experts were exceedingly accurate compared with novices. Experts showed a conservative response bias, tending to err on the side of caution by making more errors of the sort that could allow a guilty person to escape detection than errors of the sort that could falsely incriminate an innocent person. The superior performance of experts was not simply a function of their ability to match prints, per se, but a result of their ability to identify the highly similar, but nonmatching fingerprints as such. Comparing these results with previous experiments, experts were even more conservative in their decision making when dealing with these genuine crime scene prints than when dealing with simulated crime scene prints, and this conservatism made them relatively less accurate overall. Intermediate trainees-despite their lack of qualification and average 3.5 years experience-performed about as accurately as qualified experts who had an average 17.5 years experience. New trainees-despite their 5-week, full-time training course or their 6 months experience-were not any better than novices at discriminating matching and similar nonmatching prints, they were just more conservative. Further research is required to determine the precise nature of fingerprint matching expertise and the factors that influence performance. The findings of this representative, lab-based experiment may have implications for the way fingerprint examiners testify in court, but what the findings mean for reasoning about expert performance in the wild is an open, empirical, and epistemological question.

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.

Modified-hybrid optical neural network filter for multiple object recognition within cluttered scenes

NASA Astrophysics Data System (ADS)

Kypraios, Ioannis; Young, Rupert C. D.; Chatwin, Chris R.

2009-08-01

Motivated by the non-linear interpolation and generalization abilities of the hybrid optical neural network filter between the reference and non-reference images of the true-class object we designed the modifiedhybrid optical neural network filter. We applied an optical mask to the hybrid optical neural network's filter input. The mask was built with the constant weight connections of a randomly chosen image included in the training set. The resulted design of the modified-hybrid optical neural network filter is optimized for performing best in cluttered scenes of the true-class object. Due to the shift invariance properties inherited by its correlator unit the filter can accommodate multiple objects of the same class to be detected within an input cluttered image. Additionally, the architecture of the neural network unit of the general hybrid optical neural network filter allows the recognition of multiple objects of different classes within the input cluttered image by modifying the output layer of the unit. We test the modified-hybrid optical neural network filter for multiple objects of the same and of different classes' recognition within cluttered input images and video sequences of cluttered scenes. The filter is shown to exhibit with a single pass over the input data simultaneously out-of-plane rotation, shift invariance and good clutter tolerance. It is able to successfully detect and classify correctly the true-class objects within background clutter for which there has been no previous training.

Smoking scenes in popular Japanese serial television dramas: descriptive analysis during the same 3-month period in two consecutive years.

PubMed

Kanda, Hideyuki; Okamura, Tomonori; Turin, Tanvir Chowdhury; Hayakawa, Takehito; Kadowaki, Takashi; Ueshima, Hirotsugu

2006-06-01

Japanese serial television dramas are becoming very popular overseas, particularly in other Asian countries. Exposure to smoking scenes in movies and television dramas has been known to trigger initiation of habitual smoking in young people. Smoking scenes in Japanese dramas may affect the smoking behavior of many young Asians. We examined smoking scenes and smoking-related items in serial television dramas targeting young audiences in Japan during the same season in two consecutive years. Fourteen television dramas targeting the young audience broadcast between July and September in 2001 and 2002 were analyzed. A total of 136 h 42 min of television programs were divided into unit scenes of 3 min (a total of 2734 unit scenes). All the unit scenes were reviewed for smoking scenes and smoking-related items. Of the 2734 3-min unit scenes, 205 (7.5%) were actual smoking scenes and 387 (14.2%) depicted smoking environments with the presence of smoking-related items, such as ash trays. In 185 unit scenes (90.2% of total smoking scenes), actors were shown smoking. Actresses were less frequently shown smoking (9.8% of total smoking scenes). Smoking characters in dramas were in the 20-49 age group in 193 unit scenes (94.1% of total smoking scenes). In 96 unit scenes (46.8% of total smoking scenes), at least one non-smoker was present in the smoking scenes. The smoking locations were mainly indoors, including offices, restaurants and homes (122 unit scenes, 59.6%). The most common smoking-related items shown were ash trays (in 45.5% of smoking-item-related scenes) and cigarettes (in 30.2% of smoking-item-related scenes). Only 3 unit scenes (0.1 % of all scenes) promoted smoking prohibition. This was a descriptive study to examine the nature of smoking scenes observed in Japanese television dramas from a public health perspective.

History and Evolution of the Johnson Criteria.

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

Sjaardema, Tracy A.; Smith, Collin S.; Birch, Gabriel Carisle

The Johnson Criteria metric calculates probability of detection of an object imaged by an optical system, and was created in 1958 by John Johnson. As understanding of target detection has improved, detection models have evolved to better model additional factors such as weather, scene content, and object placement. The initial Johnson Criteria, while sufficient for technology and understanding at the time, does not accurately reflect current research into target acquisition and technology. Even though current research shows a dependence on human factors, there appears to be a lack of testing and modeling of human variability.

Best-next-view algorithm for three-dimensional scene reconstruction using range images

NASA Astrophysics Data System (ADS)

Banta, J. E.; Zhien, Yu; Wang, X. Z.; Zhang, G.; Smith, M. T.; Abidi, Mongi A.

1995-10-01

The primary focus of the research detailed in this paper is to develop an intelligent sensing module capable of automatically determining the optimal next sensor position and orientation during scene reconstruction. To facilitate a solution to this problem, we have assembled a system for reconstructing a 3D model of an object or scene from a sequence of range images. Candidates for the best-next-view position are determined by detecting and measuring occlusions to the range camera's view in an image. Ultimately, the candidate which will reveal the greatest amount of unknown scene information is selected as the best-next-view position. Our algorithm uses ray tracing to determine how much new information a given sensor perspective will reveal. We have tested our algorithm successfully on several synthetic range data streams, and found the system's results to be consistent with an intuitive human search. The models recovered by our system from range data compared well with the ideal models. Essentially, we have proven that range information of physical objects can be employed to automatically reconstruct a satisfactory dynamic 3D computer model at a minimal computational expense. This has obvious implications in the contexts of robot navigation, manufacturing, and hazardous materials handling. The algorithm we developed takes advantage of no a priori information in finding the best-next-view position.

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.

Orson Scott Card's "Ender and Bean": The Exceptional Child as Hero

ERIC Educational Resources Information Center

Doyle, Christine

2004-01-01

Orson Scott Card's school stories in outer space, "Ender's Game" and "Ender's Shadow," purportedly occur at the same time and tell the "same" story, but from the perspectives of two different child protagonists. Scenes in "Ender's Shadow" even reproduce text from "Ender's Game." Nevertheless, 14 years elapsed between the publications of the two…

Changes in Situation Models Modulate Processes of Event Perception in Audiovisual Narratives

ERIC Educational Resources Information Center

Huff, Markus; Meitz, Tino G. K.; Papenmeier, Frank

2014-01-01

Humans understand text and film by mentally representing their contents in situation models. These describe situations using dimensions like time, location, protagonist, and action. Changes in 1 or more dimensions (e.g., a new character enters the scene) cause discontinuities in the story line and are often perceived as boundaries between 2…

Exploring the Aesthetics of Rape in the Work of Juan de Moncayo y Gurrea

ERIC Educational Resources Information Center

McVay, Ted E., Jr.

2009-01-01

Interpreting the occurrence of sexual violation in seventeenth-century Spanish literary works necessitates for modem scholars the difficult task of understanding prevailing contemporary attitudes toward rape. Studies by Higgins and Silver, Casas, and Welles discuss how literary texts with rape scenes as narrative material often use the act or its…

Eye tracking to evaluate evidence recognition in crime scene investigations.

PubMed

Watalingam, Renuka Devi; Richetelli, Nicole; Pelz, Jeff B; Speir, Jacqueline A

2017-11-01

Crime scene analysts are the core of criminal investigations; decisions made at the scene greatly affect the speed of analysis and the quality of conclusions, thereby directly impacting the successful resolution of a case. If an examiner fails to recognize the pertinence of an item on scene, the analyst's theory regarding the crime will be limited. Conversely, unselective evidence collection will most likely include irrelevant material, thus increasing a forensic laboratory's backlog and potentially sending the investigation into an unproductive and costly direction. Therefore, it is critical that analysts recognize and properly evaluate forensic evidence that can assess the relative support of differing hypotheses related to event reconstruction. With this in mind, the aim of this study was to determine if quantitative eye tracking data and qualitative reconstruction accuracy could be used to distinguish investigator expertise. In order to assess this, 32 participants were successfully recruited and categorized as experts or trained novices based on their practical experiences and educational backgrounds. Each volunteer then processed a mock crime scene while wearing a mobile eye tracker, wherein visual fixations, durations, search patterns, and reconstruction accuracy were evaluated. The eye tracking data (dwell time and task percentage on areas of interest or AOIs) were compared using Earth Mover's Distance (EMD) and the Needleman-Wunsch (N-W) algorithm, revealing significant group differences for both search duration (EMD), as well as search sequence (N-W). More specifically, experts exhibited greater dissimilarity in search duration, but greater similarity in search sequences than their novice counterparts. In addition to the quantitative visual assessment of examiner variability, each participant's reconstruction skill was assessed using a 22-point binary scoring system, in which significant group differences were detected as a function of total reconstruction accuracy. This result, coupled with the fact that the study failed to detect a significant difference between the groups when evaluating the total time needed to complete the investigation, indicates that experts are more efficient and effective. Finally, the results presented here provide a basis for continued research in the use of eye trackers to assess expertise in complex and distributed environments, including suggestions for future work, and cautions regarding the degree to which visual attention can infer cognitive understanding. Copyright © 2017 Elsevier B.V. All rights reserved.

The fundamentals of average local variance--Part I: Detecting regular patterns.

PubMed

Bøcher, Peder Klith; McCloy, Keith R

2006-02-01

The method of average local variance (ALV) computes the mean of the standard deviation values derived for a 3 x 3 moving window on a successively coarsened image to produce a function of ALV versus spatial resolution. In developing ALV, the authors used approximately a doubling of the pixel size at each coarsening of the image. They hypothesized that ALV is low when the pixel size is smaller than the size of scene objects because the pixels on the object will have similar response values. When the pixel and objects are of similar size, they will tend to vary in response and the ALV values will increase. As the size of pixels increase further, more objects will be contained in a single pixel and ALV will decrease. The authors showed that various cover types produced single peak ALV functions that inexplicitly peaked when the pixel size was 1/2 to 3/4 of the object size. This paper reports on work done to explore the characteristics of the various forms of the ALV function and to understand the location of the peaks that occur in this function. The work was conducted using synthetically generated image data. The investigation showed that the hypothesis originally proposed in is not adequate. A new hypothesis is proposed that the ALV function has peak locations that are related to the geometric size of pattern structures in the scene. These structures are not always the same as scene objects. Only in cases where the size of and separation between scene objects are equal does the ALV function detect the size of the objects. In situations where the distance between scene objects are larger than their size, the ALV function has a peak at the object separation, not at the object size. This work has also shown that multiple object structures of different sizes and distances in the image provide multiple peaks in the ALV function and that some of these structures are not implicitly recognized as such from our perspective. However, the magnitude of these peaks depends on the response mix in the structures, complicating their interpretation and analysis. The analysis of the ALV Function is, thus, more complex than that generally reported in the literature.

Evaluation methodology for query-based scene understanding systems

NASA Astrophysics Data System (ADS)

Huster, Todd P.; Ross, Timothy D.; Culbertson, Jared L.

2015-05-01

In this paper, we are proposing a method for the principled evaluation of scene understanding systems in a query-based framework. We can think of a query-based scene understanding system as a generalization of typical sensor exploitation systems where instead of performing a narrowly defined task (e.g., detect, track, classify, etc.), the system can perform general user-defined tasks specified in a query language. Examples of this type of system have been developed as part of DARPA's Mathematics of Sensing, Exploitation, and Execution (MSEE) program. There is a body of literature on the evaluation of typical sensor exploitation systems, but the open-ended nature of the query interface introduces new aspects to the evaluation problem that have not been widely considered before. In this paper, we state the evaluation problem and propose an approach to efficiently learn about the quality of the system under test. We consider the objective of the evaluation to be to build a performance model of the system under test, and we rely on the principles of Bayesian experiment design to help construct and select optimal queries for learning about the parameters of that model.

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..

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.

Salient contour extraction from complex natural scene in night vision image

NASA Astrophysics Data System (ADS)

Han, Jing; Yue, Jiang; Zhang, Yi; Bai, Lian-fa

2014-03-01

The theory of center-surround interaction in non-classical receptive field can be applied in night vision information processing. In this work, an optimized compound receptive field modulation method is proposed to extract salient contour from complex natural scene in low-light-level (LLL) and infrared images. The kernel idea is that multi-feature analysis can recognize the inhomogeneity in modulatory coverage more accurately and that center and surround with the grouping structure satisfying Gestalt rule deserves high connection-probability. Computationally, a multi-feature contrast weighted inhibition model is presented to suppress background and lower mutual inhibition among contour elements; a fuzzy connection facilitation model is proposed to achieve the enhancement of contour response, the connection of discontinuous contour and the further elimination of randomly distributed noise and texture; a multi-scale iterative attention method is designed to accomplish dynamic modulation process and extract contours of targets in multi-size. This work provides a series of biologically motivated computational visual models with high-performance for contour detection from cluttered scene in night vision images.

Augmented reality three-dimensional object visualization and recognition with axially distributed sensing.

PubMed

Markman, Adam; Shen, Xin; Hua, Hong; Javidi, Bahram

2016-01-15

An augmented reality (AR) smartglass display combines real-world scenes with digital information enabling the rapid growth of AR-based applications. We present an augmented reality-based approach for three-dimensional (3D) optical visualization and object recognition using axially distributed sensing (ADS). For object recognition, the 3D scene is reconstructed, and feature extraction is performed by calculating the histogram of oriented gradients (HOG) of a sliding window. A support vector machine (SVM) is then used for classification. Once an object has been identified, the 3D reconstructed scene with the detected object is optically displayed in the smartglasses allowing the user to see the object, remove partial occlusions of the object, and provide critical information about the object such as 3D coordinates, which are not possible with conventional AR devices. To the best of our knowledge, this is the first report on combining axially distributed sensing with 3D object visualization and recognition for applications to augmented reality. The proposed approach can have benefits for many applications, including medical, military, transportation, and manufacturing.

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.

Constructing, Perceiving, and Maintaining Scenes: Hippocampal Activity and Connectivity

PubMed Central

Zeidman, Peter; Mullally, Sinéad L.; Maguire, Eleanor A.

2015-01-01

In recent years, evidence has accumulated to suggest the hippocampus plays a role beyond memory. A strong hippocampal response to scenes has been noted, and patients with bilateral hippocampal damage cannot vividly recall scenes from their past or construct scenes in their imagination. There is debate about whether the hippocampus is involved in the online processing of scenes independent of memory. Here, we investigated the hippocampal response to visually perceiving scenes, constructing scenes in the imagination, and maintaining scenes in working memory. We found extensive hippocampal activation for perceiving scenes, and a circumscribed area of anterior medial hippocampus common to perception and construction. There was significantly less hippocampal activity for maintaining scenes in working memory. We also explored the functional connectivity of the anterior medial hippocampus and found significantly stronger connectivity with a distributed set of brain areas during scene construction compared with scene perception. These results increase our knowledge of the hippocampus by identifying a subregion commonly engaged by scenes, whether perceived or constructed, by separating scene construction from working memory, and by revealing the functional network underlying scene construction, offering new insights into why patients with hippocampal lesions cannot construct scenes. PMID:25405941

Temporal and spatial adaptation of transient responses to local features

PubMed Central

O'Carroll, David C.; Barnett, Paul D.; Nordström, Karin

2012-01-01

Interpreting visual motion within the natural environment is a challenging task, particularly considering that natural scenes vary enormously in brightness, contrast and spatial structure. The performance of current models for the detection of self-generated optic flow depends critically on these very parameters, but despite this, animals manage to successfully navigate within a broad range of scenes. Within global scenes local areas with more salient features are common. Recent work has highlighted the influence that local, salient features have on the encoding of optic flow, but it has been difficult to quantify how local transient responses affect responses to subsequent features and thus contribute to the global neural response. To investigate this in more detail we used experimenter-designed stimuli and recorded intracellularly from motion-sensitive neurons. We limited the stimulus to a small vertically elongated strip, to investigate local and global neural responses to pairs of local “doublet” features that were designed to interact with each other in the temporal and spatial domain. We show that the passage of a high-contrast doublet feature produces a complex transient response from local motion detectors consistent with predictions of a simple computational model. In the neuron, the passage of a high-contrast feature induces a local reduction in responses to subsequent low-contrast features. However, this neural contrast gain reduction appears to be recruited only when features stretch vertically (i.e., orthogonal to the direction of motion) across at least several aligned neighboring ommatidia. Horizontal displacement of the components of elongated features abolishes the local adaptation effect. It is thus likely that features in natural scenes with vertically aligned edges, such as tree trunks, recruit the greatest amount of response suppression. This property could emphasize the local responses to such features vs. those in nearby texture within the scene. PMID:23087617

Using drone-mounted cameras for on-site body documentation: 3D mapping and active survey.

PubMed

Urbanová, Petra; Jurda, Mikoláš; Vojtíšek, Tomáš; Krajsa, Jan

2017-12-01

Recent advances in unmanned aerial technology have substantially lowered the cost associated with aerial imagery. As a result, forensic practitioners are today presented with easy low-cost access to aerial photographs at remote locations. The present paper aims to explore boundaries in which the low-end drone technology can operate as professional crime scene equipment, and to test the prospects of aerial 3D modeling in the forensic context. The study was based on recent forensic cases of falls from height admitted for postmortem examinations. Three mock outdoor forensic scenes featuring a dummy, skeletal remains and artificial blood were constructed at an abandoned quarry and subsequently documented using a commercial DJI Phantom 2 drone equipped with a GoPro HERO 4 digital camera. In two of the experiments, the purpose was to conduct aerial and ground-view photography and to process the acquired images with a photogrammetry protocol (using Agisoft PhotoScan ® 1.2.6) in order to generate 3D textured models. The third experiment tested the employment of drone-based video recordings in mapping scattered body parts. The results show that drone-based aerial photography is capable of producing high-quality images, which are appropriate for building accurate large-scale 3D models of a forensic scene. If, however, high-resolution top-down three-dimensional scene documentation featuring details on a corpse or other physical evidence is required, we recommend building a multi-resolution model by processing aerial and ground-view imagery separately. The video survey showed that using an overview recording for seeking out scattered body parts was efficient. In contrast, the less easy-to-spot evidence, such as bloodstains, was detected only after having been marked properly with crime scene equipment. Copyright © 2017 Elsevier B.V. All rights reserved.

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…

Target Acquisition Involving Multiple Unmanned Air Vehicles: Interfaces for Small Unmanned Air Systems (ISUS) Program

DTIC Science & Technology

2009-03-01

model locations, time of day, and video size. The models in the scene consisted of three-dimensional representations of common civilian automobiles in...oats, wheat). Identify automobiles as sedans or station wagons. Identify individual telephone/electric poles in residential neighborhoods. Detect

Adapting Local Features for Face Detection in Thermal Image.

PubMed

Ma, Chao; Trung, Ngo Thanh; Uchiyama, Hideaki; Nagahara, Hajime; Shimada, Atsushi; Taniguchi, Rin-Ichiro

2017-11-27

A thermal camera captures the temperature distribution of a scene as a thermal image. In thermal images, facial appearances of different people under different lighting conditions are similar. This is because facial temperature distribution is generally constant and not affected by lighting condition. This similarity in face appearances is advantageous for face detection. To detect faces in thermal images, cascade classifiers with Haar-like features are generally used. However, there are few studies exploring the local features for face detection in thermal images. In this paper, we introduce two approaches relying on local features for face detection in thermal images. First, we create new feature types by extending Multi-Block LBP. We consider a margin around the reference and the generally constant distribution of facial temperature. In this way, we make the features more robust to image noise and more effective for face detection in thermal images. Second, we propose an AdaBoost-based training method to get cascade classifiers with multiple types of local features. These feature types have different advantages. In this way we enhance the description power of local features. We did a hold-out validation experiment and a field experiment. In the hold-out validation experiment, we captured a dataset from 20 participants, comprising 14 males and 6 females. For each participant, we captured 420 images with 10 variations in camera distance, 21 poses, and 2 appearances (participant with/without glasses). We compared the performance of cascade classifiers trained by different sets of the features. The experiment results showed that the proposed approaches effectively improve the performance of face detection in thermal images. In the field experiment, we compared the face detection performance in realistic scenes using thermal and RGB images, and gave discussion based on the results.

A comparison of viewer reactions to outdoor scenes and photographs of those scenes

Treesearch

Elwood, Jr. Shafer; Thomas A. Richards; Thomas A. Richards

1974-01-01

A color-slide projection or photograph can be used to determine reactions to an actual scene if the presentation adequately includes most of the elements in the scene. Eight kinds of scenes were subjected to three different types of presentation: (A) viewing. the actual scenes, (B) viewing color slides of the scenes, and (C) viewing color photographs of the scenes. For...

Complete Scene Recovery and Terrain Classification in Textured Terrain Meshes

PubMed Central

Song, Wei; Cho, Kyungeun; Um, Kyhyun; Won, Chee Sun; Sim, Sungdae

2012-01-01

Terrain classification allows a mobile robot to create an annotated map of its local environment from the three-dimensional (3D) and two-dimensional (2D) datasets collected by its array of sensors, including a GPS receiver, gyroscope, video camera, and range sensor. However, parts of objects that are outside the measurement range of the range sensor will not be detected. To overcome this problem, this paper describes an edge estimation method for complete scene recovery and complete terrain reconstruction. Here, the Gibbs-Markov random field is used to segment the ground from 2D videos and 3D point clouds. Further, a masking method is proposed to classify buildings and trees in a terrain mesh. PMID:23112653

Automatic video segmentation and indexing

NASA Astrophysics Data System (ADS)

Chahir, Youssef; Chen, Liming

1999-08-01

Indexing is an important aspect of video database management. Video indexing involves the analysis of video sequences, which is a computationally intensive process. However, effective management of digital video requires robust indexing techniques. The main purpose of our proposed video segmentation is twofold. Firstly, we develop an algorithm that identifies camera shot boundary. The approach is based on the use of combination of color histograms and block-based technique. Next, each temporal segment is represented by a color reference frame which specifies the shot similarities and which is used in the constitution of scenes. Experimental results using a variety of videos selected in the corpus of the French Audiovisual National Institute are presented to demonstrate the effectiveness of performing shot detection, the content characterization of shots and the scene constitution.

Fractal active contour model for segmenting the boundary of man-made target in nature scenes

NASA Astrophysics Data System (ADS)

Li, Min; Tang, Yandong; Wang, Lidi; Shi, Zelin

2006-02-01

In this paper, a novel geometric active contour model based on the fractal dimension feature to extract the boundary of man-made target in nature scenes is presented. In order to suppress the nature clutters, an adaptive weighting function is defined using the fractal dimension feature. Then the weighting function is introduced into the geodesic active contour model to detect the boundary of man-made target. Curve driven by our proposed model can evolve gradually from the initial position to the boundary of man-made target without being disturbed by nature clutters, even if the initial curve is far away from the true boundary. Experimental results validate the effectiveness and feasibility of our model.

Detecting natural occlusion boundaries using local cues

PubMed Central

DiMattina, Christopher; Fox, Sean A.; Lewicki, Michael S.

2012-01-01

Occlusion boundaries and junctions provide important cues for inferring three-dimensional scene organization from two-dimensional images. Although several investigators in machine vision have developed algorithms for detecting occlusions and other edges in natural images, relatively few psychophysics or neurophysiology studies have investigated what features are used by the visual system to detect natural occlusions. In this study, we addressed this question using a psychophysical experiment where subjects discriminated image patches containing occlusions from patches containing surfaces. Image patches were drawn from a novel occlusion database containing labeled occlusion boundaries and textured surfaces in a variety of natural scenes. Consistent with related previous work, we found that relatively large image patches were needed to attain reliable performance, suggesting that human subjects integrate complex information over a large spatial region to detect natural occlusions. By defining machine observers using a set of previously studied features measured from natural occlusions and surfaces, we demonstrate that simple features defined at the spatial scale of the image patch are insufficient to account for human performance in the task. To define machine observers using a more biologically plausible multiscale feature set, we trained standard linear and neural network classifiers on the rectified outputs of a Gabor filter bank applied to the image patches. We found that simple linear classifiers could not match human performance, while a neural network classifier combining filter information across location and spatial scale compared well. These results demonstrate the importance of combining a variety of cues defined at multiple spatial scales for detecting natural occlusions. PMID:23255731

Image and Sensor Data Processing for Target Acquisition and Recognition.

DTIC Science & Technology

1980-11-01

technological, cost, size and weight constraints. The critical problem seems to be detecting the target with an acceptable false alarm rate, rather than...for its operation, loss of detail can result from adjacent differing pixels being forced into the same displayed grey-level. This may be detected in...a) Enhanced (b) Fig.1 High contrast scene demonstrating loss of detail in a local area of low contrast Luminance T V Black Peak white wavelength 1

A self-adaptive algorithm for traffic sign detection in motion image based on color and shape features

NASA Astrophysics Data System (ADS)

Zhang, Ka; Sheng, Yehua; Gong, Zhijun; Ye, Chun; Li, Yongqiang; Liang, Cheng

2007-06-01

As an important sub-system in intelligent transportation system (ITS), the detection and recognition of traffic signs from mobile images is becoming one of the hot spots in the international research field of ITS. Considering the problem of traffic sign automatic detection in motion images, a new self-adaptive algorithm for traffic sign detection based on color and shape features is proposed in this paper. Firstly, global statistical color features of different images are computed based on statistics theory. Secondly, some self-adaptive thresholds and special segmentation rules for image segmentation are designed according to these global color features. Then, for red, yellow and blue traffic signs, the color image is segmented to three binary images by these thresholds and rules. Thirdly, if the number of white pixels in the segmented binary image exceeds the filtering threshold, the binary image should be further filtered. Fourthly, the method of gray-value projection is used to confirm top, bottom, left and right boundaries for candidate regions of traffic signs in the segmented binary image. Lastly, if the shape feature of candidate region satisfies the need of real traffic sign, this candidate region is confirmed as the detected traffic sign region. The new algorithm is applied to actual motion images of natural scenes taken by a CCD camera of the mobile photogrammetry system in Nanjing at different time. The experimental results show that the algorithm is not only simple, robust and more adaptive to natural scene images, but also reliable and high-speed on real traffic sign detection.

Post-processing for improving hyperspectral anomaly detection accuracy

NASA Astrophysics Data System (ADS)

Wu, Jee-Cheng; Jiang, Chi-Ming; Huang, Chen-Liang

2015-10-01

Anomaly detection is an important topic in the exploitation of hyperspectral data. Based on the Reed-Xiaoli (RX) detector and a morphology operator, this research proposes a novel technique for improving the accuracy of hyperspectral anomaly detection. Firstly, the RX-based detector is used to process a given input scene. Then, a post-processing scheme using morphology operator is employed to detect those pixels around high-scoring anomaly pixels. Tests were conducted using two real hyperspectral images with ground truth information and the results based on receiver operating characteristic curves, illustrated that the proposed method reduced the false alarm rates of the RXbased detector.

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.

Hippocampal Contribution to Implicit Configuration Memory Expressed via Eye Movements During Scene Exploration

PubMed Central

Ryals, Anthony J.; Wang, Jane X.; Polnaszek, Kelly L.; Voss, Joel L.

2015-01-01

Although hippocampus unequivocally supports explicit/ declarative memory, fewer findings have demonstrated its role in implicit expressions of memory. We tested for hippocampal contributions to an implicit expression of configural/relational memory for complex scenes using eye-movement tracking during functional magnetic resonance imaging (fMRI) scanning. Participants studied scenes and were later tested using scenes that resembled study scenes in their overall feature configuration but comprised different elements. These configurally similar scenes were used to limit explicit memory, and were intermixed with new scenes that did not resemble studied scenes. Scene configuration memory was expressed through eye movements reflecting exploration overlap (EO), which is the viewing of the same scene locations at both study and test. EO reliably discriminated similar study-test scene pairs from study-new scene pairs, was reliably greater for similarity-based recognition hits than for misses, and correlated with hippocampal fMRI activity. In contrast, subjects could not reliably discriminate similar from new scenes by overt judgments, although ratings of familiarity were slightly higher for similar than new scenes. Hippocampal fMRI correlates of this weak explicit memory were distinct from EO-related activity. These findings collectively suggest that EO was an implicit expression of scene configuration memory associated with hippocampal activity. Visual exploration can therefore reflect implicit hippocampal-related memory processing that can be observed in eye-movement behavior during naturalistic scene viewing. PMID:25620526

An Analysis of the Max-Min Texture Measure.

DTIC Science & Technology

1982-01-01

PANC 33 D2 Confusion Matrices for Scene A, IR 34 D3 Confusion Matrices for Scene B, PANC 35 D4 Confusion Matrices for Scene B, IR 36 D5 Confusion...Matrices for Scene C, PANC 37 D6 Confusion Matrices for Scene C, IR 38 D7 Confusion Matrices for Scene E, PANC 39 D8 Confusion Matrices for Scene E, IR 40...D9 Confusion Matrices for Scene H, PANC 41 DIO Confusion Matrices for Scene H, JR 42 3 .D 10CnuinMtie o cn ,IR4 AN ANALYSIS OF THE MAX-MIN TEXTURE

Tackling Behaviour in Your Primary School: A Practical Handbook for Teachers

ERIC Educational Resources Information Center

Reid, Ken; Morgan, Nicola S.

2012-01-01

"Tackling Behaviour in the Primary School" provides ready-made advice and support for classroom professionals and can be used, read and adapted to suit the busy everyday lives of teachers working in primary schools today. This valuable text sets the scene for managing behaviour in the primary classroom in the context of the Children Act 2004…

Assessing Top-Down and Bottom-Up Contributions to Auditory Stream Segregation and Integration With Polyphonic Music

PubMed Central

Disbergen, Niels R.; Valente, Giancarlo; Formisano, Elia; Zatorre, Robert J.

2018-01-01

Polyphonic music listening well exemplifies processes typically involved in daily auditory scene analysis situations, relying on an interactive interplay between bottom-up and top-down processes. Most studies investigating scene analysis have used elementary auditory scenes, however real-world scene analysis is far more complex. In particular, music, contrary to most other natural auditory scenes, can be perceived by either integrating or, under attentive control, segregating sound streams, often carried by different instruments. One of the prominent bottom-up cues contributing to multi-instrument music perception is their timbre difference. In this work, we introduce and validate a novel paradigm designed to investigate, within naturalistic musical auditory scenes, attentive modulation as well as its interaction with bottom-up processes. Two psychophysical experiments are described, employing custom-composed two-voice polyphonic music pieces within a framework implementing a behavioral performance metric to validate listener instructions requiring either integration or segregation of scene elements. In Experiment 1, the listeners' locus of attention was switched between individual instruments or the aggregate (i.e., both instruments together), via a task requiring the detection of temporal modulations (i.e., triplets) incorporated within or across instruments. Subjects responded post-stimulus whether triplets were present in the to-be-attended instrument(s). Experiment 2 introduced the bottom-up manipulation by adding a three-level morphing of instrument timbre distance to the attentional framework. The task was designed to be used within neuroimaging paradigms; Experiment 2 was additionally validated behaviorally in the functional Magnetic Resonance Imaging (fMRI) environment. Experiment 1 subjects (N = 29, non-musicians) completed the task at high levels of accuracy, showing no group differences between any experimental conditions. Nineteen listeners also participated in Experiment 2, showing a main effect of instrument timbre distance, even though within attention-condition timbre-distance contrasts did not demonstrate any timbre effect. Correlation of overall scores with morph-distance effects, computed by subtracting the largest from the smallest timbre distance scores, showed an influence of general task difficulty on the timbre distance effect. Comparison of laboratory and fMRI data showed scanner noise had no adverse effect on task performance. These Experimental paradigms enable to study both bottom-up and top-down contributions to auditory stream segregation and integration within psychophysical and neuroimaging experiments. PMID:29563861

Eye movements during information processing tasks: individual differences and cultural effects.

PubMed

Rayner, Keith; Li, Xingshan; Williams, Carrick C; Cave, Kyle R; Well, Arnold D

2007-09-01

The eye movements of native English speakers, native Chinese speakers, and bilingual Chinese/English speakers who were either born in China (and moved to the US at an early age) or in the US were recorded during six tasks: (1) reading, (2) face processing, (3) scene perception, (4) visual search, (5) counting Chinese characters in a passage of text, and (6) visual search for Chinese characters. Across the different groups, there was a strong tendency for consistency in eye movement behavior; if fixation durations of a given viewer were long on one task, they tended to be long on other tasks (and the same tended to be true for saccade size). Some tasks, notably reading, did not conform to this pattern. Furthermore, experience with a given writing system had a large impact on fixation durations and saccade lengths. With respect to cultural differences, there was little evidence that Chinese participants spent more time looking at the background information (and, conversely less time looking at the foreground information) than the American participants. Also, Chinese participants' fixations were more numerous and of shorter duration than those of their American counterparts while viewing faces and scenes, and counting Chinese characters in text.

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.

Crime scene investigation, reporting, and reconstuction (CSIRR)

NASA Astrophysics Data System (ADS)

Booth, John F.; Young, Jeffrey M.; Corrigan, Paul

1997-02-01

Graphic Data Systems Corporation (GDS Corp.) and Intellignet Graphics Solutions, Inc. (IGS) combined talents in 1995 to design and develop a MicroGDSTM application to support field investiations of crime scenes, such as homoicides, bombings, and arsons. IGS and GDS Corp. prepared design documents under the guidance of federal, state, and local crime scene reconstruction experts and with information from the FBI's evidence response team field book. The application was then developed to encompass the key components of crime scene investigaton: staff assigned to the incident, tasks occuring at the scene, visits to the scene location, photogrpahs taken of the crime scene, related documents, involved persons, catalogued evidence, and two- or three- dimensional crime scene reconstruction. Crime scene investigation, reporting, and reconstruction (CSIRR$CPY) provides investigators with a single applicaiton for both capturing all tabular data about the crime scene and quickly renderng a sketch of the scene. Tabular data is captured through ituitive database forms, while MicroGDSTM has been modified to readily allow non-CAD users to sketch the scene.

Vision Based SLAM in Dynamic Scenes

DTIC Science & Technology

2012-12-20

the correct relative poses between cameras at frame F. For this purpose, we detect and match SURF features between cameras in dilierent groups, and...all cameras in s uch a challenging case. For a compa rison, we disabled the ’ inte r-camera pose estimation’ and applied the ’ intra-camera pose esti

Image Understanding Research

DTIC Science & Technology

1991-02-01

investigating the possibility of parallel cutting out - look at the ears of the giraffe ). The recognition implementation. The data structure of a...0.1, 311 model segments -line fit. tol. -super segments/ giraffe 310 l .4,2,3,4,5,6,8 310 (b) Scene (c) Detected Animals panther 298 1.4,2,3.4,5,6,8 282

[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.

Robust multiperson tracking from a mobile platform.

PubMed

Ess, Andreas; Leibe, Bastian; Schindler, Konrad; van Gool, Luc

2009-10-01

In this paper, we address the problem of multiperson tracking in busy pedestrian zones using a stereo rig mounted on a mobile platform. The complexity of the problem calls for an integrated solution that extracts as much visual information as possible and combines it through cognitive feedback cycles. We propose such an approach, which jointly estimates camera position, stereo depth, object detection, and tracking. The interplay between those components is represented by a graphical model. Since the model has to incorporate object-object interactions and temporal links to past frames, direct inference is intractable. We, therefore, propose a two-stage procedure: for each frame, we first solve a simplified version of the model (disregarding interactions and temporal continuity) to estimate the scene geometry and an overcomplete set of object detections. Conditioned on these results, we then address object interactions, tracking, and prediction in a second step. The approach is experimentally evaluated on several long and difficult video sequences from busy inner-city locations. Our results show that the proposed integration makes it possible to deliver robust tracking performance in scenes of realistic complexity.

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

Detection of people in military and security context imagery

NASA Astrophysics Data System (ADS)

Shannon, Thomas M. L.; Spier, Emmet H.; Wiltshire, Ben

2014-10-01

A high level of manual visual surveillance of complex scenes is dependent solely on the awareness of human operators whereas an autonomous person detection solution could assist by drawing their attention to potential issues, in order to reduce cognitive burden and achieve more with less manpower. Our research addressed the challenge of the reliable identification of persons in a scene who may be partially obscured by structures or by handling weapons or tools. We tested the efficacy of a recently published computer vision approach based on the construction of cascaded, non-linear classifiers from part-based deformable models by assessing performance using imagery containing infantrymen in the open or when obscured, undertaking low level tactics or acting as civilians using tools. Results were compared with those obtained from published upright pedestrian imagery. The person detector yielded a precision of approximately 65% for a recall rate of 85% for military context imagery as opposed to a precision of 85% for the upright pedestrian image cases. These results compared favorably with those reported by the authors when applied to a range of other on-line imagery databases. Our conclusion is that the deformable part-based model method may be a potentially useful people detection tool in the challenging environment of military and security context imagery.

Joint Attributes and Event Analysis for Multimedia Event Detection.

PubMed

Ma, Zhigang; Chang, Xiaojun; Xu, Zhongwen; Sebe, Nicu; Hauptmann, Alexander G

2017-06-15

Semantic attributes have been increasingly used the past few years for multimedia event detection (MED) with promising results. The motivation is that multimedia events generally consist of lower level components such as objects, scenes, and actions. By characterizing multimedia event videos with semantic attributes, one could exploit more informative cues for improved detection results. Much existing work obtains semantic attributes from images, which may be suboptimal for video analysis since these image-inferred attributes do not carry dynamic information that is essential for videos. To address this issue, we propose to learn semantic attributes from external videos using their semantic labels. We name them video attributes in this paper. In contrast with multimedia event videos, these external videos depict lower level contents such as objects, scenes, and actions. To harness video attributes, we propose an algorithm established on a correlation vector that correlates them to a target event. Consequently, we could incorporate video attributes latently as extra information into the event detector learnt from multimedia event videos in a joint framework. To validate our method, we perform experiments on the real-world large-scale TRECVID MED 2013 and 2014 data sets and compare our method with several state-of-the-art algorithms. The experiments show that our method is advantageous for MED.

Learning-dependent plasticity with and without training in the human brain.

PubMed

Zhang, Jiaxiang; Kourtzi, Zoe

2010-07-27

Long-term experience through development and evolution and shorter-term training in adulthood have both been suggested to contribute to the optimization of visual functions that mediate our ability to interpret complex scenes. However, the brain plasticity mechanisms that mediate the detection of objects in cluttered scenes remain largely unknown. Here, we combine behavioral and functional MRI (fMRI) measurements to investigate the human-brain mechanisms that mediate our ability to learn statistical regularities and detect targets in clutter. We show two different routes to visual learning in clutter with discrete brain plasticity signatures. Specifically, opportunistic learning of regularities typical in natural contours (i.e., collinearity) can occur simply through frequent exposure, generalize across untrained stimulus features, and shape processing in occipitotemporal regions implicated in the representation of global forms. In contrast, learning to integrate discontinuities (i.e., elements orthogonal to contour paths) requires task-specific training (bootstrap-based learning), is stimulus-dependent, and enhances processing in intraparietal regions implicated in attention-gated learning. We propose that long-term experience with statistical regularities may facilitate opportunistic learning of collinear contours, whereas learning to integrate discontinuities entails bootstrap-based training for the detection of contours in clutter. These findings provide insights in understanding how long-term experience and short-term training interact to shape the optimization of visual recognition processes.

Method and apparatus for telemetry adaptive bandwidth compression

NASA Technical Reports Server (NTRS)

Graham, Olin L.

1987-01-01

Methods and apparatus are provided for automatic and/or manual adaptive bandwidth compression of telemetry. An adaptive sampler samples a video signal from a scanning sensor and generates a sequence of sampled fields. Each field and range rate information from the sensor are hence sequentially transmitted to and stored in a multiple and adaptive field storage means. The field storage means then, in response to an automatic or manual control signal, transfers the stored sampled field signals to a video monitor in a form for sequential or simultaneous display of a desired number of stored signal fields. The sampling ratio of the adaptive sample, the relative proportion of available communication bandwidth allocated respectively to transmitted data and video information, and the number of fields simultaneously displayed are manually or automatically selectively adjustable in functional relationship to each other and detected range rate. In one embodiment, when relatively little or no scene motion is detected, the control signal maximizes sampling ratio and causes simultaneous display of all stored fields, thus maximizing resolution and bandwidth available for data transmission. When increased scene motion is detected, the control signal is adjusted accordingly to cause display of fewer fields. If greater resolution is desired, the control signal is adjusted to increase the sampling ratio.

Assessing the impact of background spectral graph construction techniques on the topological anomaly detection algorithm

NASA Astrophysics Data System (ADS)

Ziemann, Amanda K.; Messinger, David W.; Albano, James A.; Basener, William F.

2012-06-01

Anomaly detection algorithms have historically been applied to hyperspectral imagery in order to identify pixels whose material content is incongruous with the background material in the scene. Typically, the application involves extracting man-made objects from natural and agricultural surroundings. A large challenge in designing these algorithms is determining which pixels initially constitute the background material within an image. The topological anomaly detection (TAD) algorithm constructs a graph theory-based, fully non-parametric topological model of the background in the image scene, and uses codensity to measure deviation from this background. In TAD, the initial graph theory structure of the image data is created by connecting an edge between any two pixel vertices x and y if the Euclidean distance between them is less than some resolution r. While this type of proximity graph is among the most well-known approaches to building a geometric graph based on a given set of data, there is a wide variety of dierent geometrically-based techniques. In this paper, we present a comparative test of the performance of TAD across four dierent constructs of the initial graph: mutual k-nearest neighbor graph, sigma-local graph for two different values of σ > 1, and the proximity graph originally implemented in TAD.

Scenes unseen: The parahippocampal cortex intrinsically subserves contextual associations, not scenes or places per se

PubMed Central

Bar, Moshe; Aminoff, Elissa; Schacter, Daniel L.

2009-01-01

The parahippocampal cortex (PHC) has been implicated both in episodic memory and in place/scene processing. We proposed that this region should instead be seen as intrinsically mediating contextual associations, and not place/scene processing or episodic memory exclusively. Given that place/scene processing and episodic memory both rely on associations, this modified framework provides a platform for reconciling what seemed like different roles assigned to the same region. Comparing scenes with scenes, we show here that the PHC responds significantly more strongly to scenes with rich contextual associations compared with scenes of equal visual qualities but less associations. This result provides the strongest support to the view that the PHC mediates contextual associations in general, rather than places or scenes proper, and necessitates a revision of current views such as that the PHC contains a dedicated place/scenes “module.” PMID:18716212

Morphological operators for enhanced polarimetric image target detection

NASA Astrophysics Data System (ADS)

Romano, João. M.; Rosario, Dalton S.

2015-09-01

We introduce an algorithm based on morphological filters with the Stokes parameters that augments the daytime and nighttime detection of weak-signal manmade objects immersed in a predominant natural background scene. The approach features a tailored sequence of signal-enhancing filters, consisting of core morphological operators (dilation, erosion) and higher level morphological operations (e.g., spatial gradient, opening, closing) to achieve a desired overarching goal. Using representative data from the SPICE database, the results show that the approach was able to automatically and persistently detect with a high confidence level the presence of three mobile military howitzer surrogates (targets) in natural clutter.

Application of Data Mining and Knowledge Discovery Techniques to Enhance Binary Target Detection and Decision-Making for Compromised Visual Images

DTIC Science & Technology

2004-11-01

affords exciting opportunities in target detection. The input signal may be a sum of sine waves, it could be an auditory signal, or possibly a visual...rendering of a scene. Since image processing is an area in which the original data are stationary in some sense ( auditory signals suffer from...11 Example 1 of SR - Identification of a Subliminal Signal below a Threshold .......................... 13 Example 2 of SR

Vision-based algorithms for near-host object detection and multilane sensing

NASA Astrophysics Data System (ADS)

Kenue, Surender K.

1995-01-01

Vision-based sensing can be used for lane sensing, adaptive cruise control, collision warning, and driver performance monitoring functions of intelligent vehicles. Current computer vision algorithms are not robust for handling multiple vehicles in highway scenarios. Several new algorithms are proposed for multi-lane sensing, near-host object detection, vehicle cut-in situations, and specifying regions of interest for object tracking. These algorithms were tested successfully on more than 6000 images taken from real-highway scenes under different daytime lighting conditions.

R&D 100 Winner 2010: Acoustic Wave Biosensors

ScienceCinema

Larson, Richard; Branch, Darren; Edwards, Thayne

2018-01-16

The acoustic wave biosensor is innovative device that is a handheld, battery-powered, portable detection system capable of multiplex identification of a wide range of medically relevant pathogens and their biomolecular signatures — viruses, bacteria, proteins, and DNA — at clinically relevant levels. This detection occurs within minutes — not hours — at the point of care, whether that care is in a physician's office, a hospital bed, or at the scene of a biodefense or biomedical emergency.

Mii School: New 3D Technologies Applied in Education to Detect Drug Abuses and Bullying in Adolescents

NASA Astrophysics Data System (ADS)

Carmona, José Alberto; Espínola, Moisés; Cangas, Adolfo J.; Iribarne, Luis

Mii School is a 3D school simulator developed with Blender and used by psychology researchers for the detection of drugs abuses, bullying and mental disorders in adolescents. The school simulator created is an interactive video game where the players, in this case the students, have to choose, along 17 scenes simulated, the options that better define their personalities. In this paper we present a technical characteristics description and the first results obtained in a real school.

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.

Computational Modeling of Age-Differences In a Visually Demanding Driving Task: Vehicle Detection

DTIC Science & Technology

1997-10-07

overall estimate of d’ for each scene was calculated from the two levels using the method described in MacMillan and Creelman [13]. MODELING VEHICLE...Scialfa, "Visual and auditory aging," In J. Birren & K. W. Schaie (Eds.) Handbook of the Psychology of Aging (4th edition), 1996, New York: Academic...Computational models of Visual Processing, 1991, Boston MA: MIT Press. [13] N. A. MacMillan & C. D. Creelman , Detection Theory: A User’s Guide, 1991

Volumetric segmentation of range images for printed circuit board inspection

NASA Astrophysics Data System (ADS)

Van Dop, Erik R.; Regtien, Paul P. L.

1996-10-01

Conventional computer vision approaches towards object recognition and pose estimation employ 2D grey-value or color imaging. As a consequence these images contain information about projections of a 3D scene only. The subsequent image processing will then be difficult, because the object coordinates are represented with just image coordinates. Only complicated low-level vision modules like depth from stereo or depth from shading can recover some of the surface geometry of the scene. Recent advances in fast range imaging have however paved the way towards 3D computer vision, since range data of the scene can now be obtained with sufficient accuracy and speed for object recognition and pose estimation purposes. This article proposes the coded-light range-imaging method together with superquadric segmentation to approach this task. Superquadric segments are volumetric primitives that describe global object properties with 5 parameters, which provide the main features for object recognition. Besides, the principle axes of a superquadric segment determine the phase of an object in the scene. The volumetric segmentation of a range image can be used to detect missing, false or badly placed components on assembled printed circuit boards. Furthermore, this approach will be useful to recognize and extract valuable or toxic electronic components on printed circuit boards scrap that currently burden the environment during electronic waste processing. Results on synthetic range images with errors constructed according to a verified noise model illustrate the capabilities of this approach.

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.

Degraded visual environment image/video quality metrics

NASA Astrophysics Data System (ADS)

Baumgartner, Dustin D.; Brown, Jeremy B.; Jacobs, Eddie L.; Schachter, Bruce J.

2014-06-01

A number of image quality metrics (IQMs) and video quality metrics (VQMs) have been proposed in the literature for evaluating techniques and systems for mitigating degraded visual environments. Some require both pristine and corrupted imagery. Others require patterned target boards in the scene. None of these metrics relates well to the task of landing a helicopter in conditions such as a brownout dust cloud. We have developed and used a variety of IQMs and VQMs related to the pilot's ability to detect hazards in the scene and to maintain situational awareness. Some of these metrics can be made agnostic to sensor type. Not only are the metrics suitable for evaluating algorithm and sensor variation, they are also suitable for choosing the most cost effective solution to improve operating conditions in degraded visual environments.

Field test of optical and electrical fire detectors in simulated fire scenes in a cable tunnel

NASA Astrophysics Data System (ADS)

Fan, Dian; Ding, Hongjun; Wang, Dorothy Y.; Jiang, Desheng

2014-06-01

This paper presents the testing results of three types of fire detectors: electrical heat sensing cable, optical fiber Raman temperature sensing detector, and optical fiber Bragg grating (FBG) temperature sensing detector, in two simulated fire scenes in a cable tunnel. In the small-scale fire with limited thermal radiation and no flame, the fire alarm only comes from the heat sensors which directly contact with the heat source. In the large-scale fire with about 5 °C/min temperature rising speed within a 3-m span, the fire alarm response time of the fiber Raman sensor and FBG sensors was about 30 seconds. The test results can be further used for formulating regulation for early fire detection in cable tunnels.

Machine vision and appearance based learning

NASA Astrophysics Data System (ADS)

Bernstein, Alexander

2017-03-01

Smart algorithms are used in Machine vision to organize or extract high-level information from the available data. The resulted high-level understanding the content of images received from certain visual sensing system and belonged to an appearance space can be only a key first step in solving various specific tasks such as mobile robot navigation in uncertain environments, road detection in autonomous driving systems, etc. Appearance-based learning has become very popular in the field of machine vision. In general, the appearance of a scene is a function of the scene content, the lighting conditions, and the camera position. Mobile robots localization problem in machine learning framework via appearance space analysis is considered. This problem is reduced to certain regression on an appearance manifold problem, and newly regression on manifolds methods are used for its solution.

The wide window of face detection.

PubMed

Hershler, Orit; Golan, Tal; Bentin, Shlomo; Hochstein, Shaul

2010-08-20

Faces are detected more rapidly than other objects in visual scenes and search arrays, but the cause for this face advantage has been contested. In the present study, we found that under conditions of spatial uncertainty, faces were easier to detect than control targets (dog faces, clocks and cars) even in the absence of surrounding stimuli, making an explanation based only on low-level differences unlikely. This advantage improved with eccentricity in the visual field, enabling face detection in wider visual windows, and pointing to selective sparing of face detection at greater eccentricities. This face advantage might be due to perceptual factors favoring face detection. In addition, the relative face advantage is greater under flanked than non-flanked conditions, suggesting an additional, possibly attention-related benefit enabling face detection in groups of distracters.

Global ensemble texture representations are critical to rapid scene perception.

PubMed

Brady, Timothy F; Shafer-Skelton, Anna; Alvarez, George A

2017-06-01

Traditionally, recognizing the objects within a scene has been treated as a prerequisite to recognizing the scene itself. However, research now suggests that the ability to rapidly recognize visual scenes could be supported by global properties of the scene itself rather than the objects within the scene. Here, we argue for a particular instantiation of this view: That scenes are recognized by treating them as a global texture and processing the pattern of orientations and spatial frequencies across different areas of the scene without recognizing any objects. To test this model, we asked whether there is a link between how proficient individuals are at rapid scene perception and how proficiently they represent simple spatial patterns of orientation information (global ensemble texture). We find a significant and selective correlation between these tasks, suggesting a link between scene perception and spatial ensemble tasks but not nonspatial summary statistics In a second and third experiment, we additionally show that global ensemble texture information is not only associated with scene recognition, but that preserving only global ensemble texture information from scenes is sufficient to support rapid scene perception; however, preserving the same information is not sufficient for object recognition. Thus, global ensemble texture alone is sufficient to allow activation of scene representations but not object representations. Together, these results provide evidence for a view of scene recognition based on global ensemble texture rather than a view based purely on objects or on nonspatially localized global properties. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Comparative Analyses of Live-Action and Animated Film Remake Scenes: Finding Alternative Film-Based Teaching Resources

ERIC Educational Resources Information Center

Champoux, Joseph E.

2005-01-01

Live-action and animated film remake scenes can show many topics typically taught in organizational behaviour and management courses. This article discusses, analyses and compares such scenes to identify parallel film scenes useful for teaching. The analysis assesses the scenes to decide which scene type, animated or live-action, more effectively…

SeeCoast: persistent surveillance and automated scene understanding for ports and coastal areas

NASA Astrophysics Data System (ADS)

Rhodes, Bradley J.; Bomberger, Neil A.; Freyman, Todd M.; Kreamer, William; Kirschner, Linda; L'Italien, Adam C.; Mungovan, Wendy; Stauffer, Chris; Stolzar, Lauren; Waxman, Allen M.; Seibert, Michael

2007-04-01

SeeCoast is a prototype US Coast Guard port and coastal area surveillance system that aims to reduce operator workload while maintaining optimal domain awareness by shifting their focus from having to detect events to being able to analyze and act upon the knowledge derived from automatically detected anomalous activities. The automated scene understanding capability provided by the baseline SeeCoast system (as currently installed at the Joint Harbor Operations Center at Hampton Roads, VA) results from the integration of several components. Machine vision technology processes the real-time video streams provided by USCG cameras to generate vessel track and classification (based on vessel length) information. A multi-INT fusion component generates a single, coherent track picture by combining information available from the video processor with that from surface surveillance radars and AIS reports. Based on this track picture, vessel activity is analyzed by SeeCoast to detect user-defined unsafe, illegal, and threatening vessel activities using a rule-based pattern recognizer and to detect anomalous vessel activities on the basis of automatically learned behavior normalcy models. Operators can optionally guide the learning system in the form of examples and counter-examples of activities of interest, and refine the performance of the learning system by confirming alerts or indicating examples of false alarms. The fused track picture also provides a basis for automated control and tasking of cameras to detect vessels in motion. Real-time visualization combining the products of all SeeCoast components in a common operating picture is provided by a thin web-based client.