ESAM: Endocrine inspired Sensor Activation Mechanism for multi-target tracking in WSNs

NASA Astrophysics Data System (ADS)

Adil Mahdi, Omar; Wahab, Ainuddin Wahid Abdul; Idris, Mohd Yamani Idna; Znaid, Ammar Abu; Khan, Suleman; Al-Mayouf, Yusor Rafid Bahar

2016-10-01

Target tracking is a significant application of wireless sensor networks (WSNs) in which deployment of self-organizing and energy efficient algorithms is required. The tracking accuracy increases as more sensor nodes are activated around the target but more energy is consumed. Thus, in this study, we focus on limiting the number of sensors by forming an ad-hoc network that operates autonomously. This will reduce the energy consumption and prolong the sensor network lifetime. In this paper, we propose a fully distributed algorithm, an Endocrine inspired Sensor Activation Mechanism for multi target-tracking (ESAM) which reflecting the properties of real life sensor activation system based on the information circulating principle in the endocrine system of the human body. Sensor nodes in our network are secreting different hormones according to certain rules. The hormone level enables the nodes to regulate an efficient sleep and wake up cycle of nodes to reduce the energy consumption. It is evident from the simulation results that the proposed ESAM in autonomous sensor network exhibits a stable performance without the need of commands from a central controller. Moreover, the proposed ESAM generates more efficient and persistent results as compared to other algorithms for tracking an invading object.

Organizing and Typing Persistent Objects Within an Object-Oriented Framework

NASA Technical Reports Server (NTRS)

Madany, Peter W.; Campbell, Roy H.

1991-01-01

Conventional operating systems provide little or no direct support for the services required for an efficient persistent object system implementation. We have built a persistent object scheme using a customization and extension of an object-oriented operating system called Choices. Choices includes a framework for the storage of persistent data that is suited to the construction of both conventional file system and persistent object system. In this paper we describe three areas in which persistent object support differs from file system support: storage organization, storage management, and typing. Persistent object systems must support various sizes of objects efficiently. Customizable containers, which are themselves persistent objects and can be nested, support a wide range of object sizes in Choices. Collections of persistent objects that are accessed as an aggregate and collections of light-weight persistent objects can be clustered in containers that are nested within containers for larger objects. Automated garbage collection schemes are added to storage management and have a major impact on persistent object applications. The Choices persistent object store provides extensible sets of persistent object types. The store contains not only the data for persistent objects but also the names of the classes to which they belong and the code for the operation of the classes. Besides presenting persistent object storage organization, storage management, and typing, this paper discusses how persistent objects are named and used within the Choices persistent data/file system framework.

Comparative Persistence of Subgroups of F-Specific RNA Phages in River Water

PubMed Central

Yang, Yongheng

2013-01-01

F-specific (F+) RNA phages are widely used as indicators for the presence of fecal contamination and/or enteric viruses in water, and identifying subgroups of F+ RNA phages provides an approach for microbial source tracking. Different survival characteristics of the F+ RNA phage subgroups result in a misinterpretation of their original proportion in water, thus giving misleading information when they are used for microbial source tracking. This study investigated the comparative persistence of subgroups of F+ RNA phages in river water under different conditions. Results suggested that temperature and pH are the major factors affecting the persistence of F+ RNA phages in river water, and organic substances promote phage survival. The comparative persistence patterns of subgroups of F+ RNA phages varied and may bias extrapolation of their initial proportions in surface water. Thus, the characteristics of water should be taken into consideration and the results should be carefully interpreted when F+ RNA phages are used for microbial source tracking. PMID:23686274

Interactive target tracking for persistent wide-area surveillance

NASA Astrophysics Data System (ADS)

Ersoy, Ilker; Palaniappan, Kannappan; Seetharaman, Guna S.; Rao, Raghuveer M.

2012-06-01

Persistent aerial surveillance is an emerging technology that can provide continuous, wide-area coverage from an aircraft-based multiple-camera system. Tracking targets in these data sets is challenging for vision algorithms due to large data (several terabytes), very low frame rate, changing viewpoint, strong parallax and other imperfections due to registration and projection. Providing an interactive system for automated target tracking also has additional challenges that require online algorithms that are seamlessly integrated with interactive visualization tools to assist the user. We developed an algorithm that overcomes these challenges and demonstrated it on data obtained from a wide-area imaging platform.

Towards Routine Uncued Surveillance of Small Objects at and near Geostationary Orbit with Small Telescopes

NASA Astrophysics Data System (ADS)

Zimmer, P.; McGraw, J. T.; Ackermann, M. R.

There is considerable interest in the capability to discover and monitor small objects (d 20cm) in geosynchronous (GEO) and near-GEO orbital regimes using small, ground-based optical telescopes (D < 0.5m). The threat of such objects is clear. Small telescopes have an unrivaled cost advantage and, under ideal lighting and sky conditions, have the capability of detecting faint objects. This combination of conditions, however, is relatively rare, making routine and persistent surveillance more challenging. In a truly geostationary orbit, a small object is easy to detect because its apparent rate of motion is nearly zero for a ground-based observer, and signal accumulation occurs as it would for more traditional sidereal-tracked astronomical observations. In this regime, though, small objects are not expected to be in controlled or predictable orbits, thus a range of inclinations and eccentricities is possible. This results in a range of apparent angular rates and directions that must be surveilled. This firmly establishes this task as uncued or blind surveillance. Detections in this case are subject to what is commonly called “trailing loss,” where the signal from the object does not accumulate in a fixed detection element, resulting in far lower sensitivity than for a similar object optimally tracked. We review some of the limits of detecting these objects under less than ideal observing conditions, subject further to the current limitations based on technological and operational realities. We demonstrate progress towards this goal using telescopes much smaller than normally considered viable for this task using novel detection and analysis techniques.

Decoding information about dynamically occluded objects in visual cortex

PubMed Central

Erlikhman, Gennady; Caplovitz, Gideon P.

2016-01-01

During dynamic occlusion, an object passes behind an occluding surface and then later reappears. Even when completely occluded from view, such objects are experienced as continuing to exist or persist behind the occluder, even though they are no longer visible. The contents and neural basis of this persistent representation remain poorly understood. Questions remain as to whether there is information maintained about the object itself (i.e. its shape or identity) or, non-object-specific information such as its position or velocity as it is tracked behind an occluder as well as which areas of visual cortex represent such information. Recent studies have found that early visual cortex is activated by “invisible” objects during visual imagery and by unstimulated regions along the path of apparent motion, suggesting that some properties of dynamically occluded objects may also be neurally represented in early visual cortex. We applied functional magnetic resonance imaging in human subjects to examine the representation of information within visual cortex during dynamic occlusion. For gradually occluded, but not for instantly disappearing objects, there was an increase in activity in early visual cortex (V1, V2, and V3). This activity was spatially-specific, corresponding to the occluded location in the visual field. However, the activity did not encode enough information about object identity to discriminate between different kinds of occluded objects (circles vs. stars) using MVPA. In contrast, object identity could be decoded in spatially-specific subregions of higher-order, topographically organized areas such as ventral, lateral, and temporal occipital areas (VO, LO, and TO) as well as the functionally defined LOC and hMT+. These results suggest that early visual cortex may represent the dynamically occluded object’s position or motion path, while later visual areas represent object-specific information. PMID:27663987

Twitter web-service for soft agent reporting in persistent surveillance systems

NASA Astrophysics Data System (ADS)

Rababaah, Haroun; Shirkhodaie, Amir

2010-04-01

Persistent surveillance is an intricate process requiring monitoring, gathering, processing, tracking, and characterization of many spatiotemporal events occurring concurrently. Data associated with events can be readily attained by networking of hard (physical) sensors. Sensors may have homogeneous or heterogeneous (hybrid) sensing modalities with different communication bandwidth requirements. Complimentary to hard sensors are human observers or "soft sensors" that can report occurrences of evolving events via different communication devices (e.g., texting, cell phones, emails, instant messaging, etc.) to the command control center. However, networking of human observers in ad-hoc way is rather a difficult task. In this paper, we present a Twitter web-service for soft agent reporting in persistent surveillance systems (called Web-STARS). The objective of this web-service is to aggregate multi-source human observations in hybrid sensor networks rapidly. With availability of Twitter social network, such a human networking concept can not only be realized for large scale persistent surveillance systems (PSS), but also, it can be employed with proper interfaces to expedite rapid events reporting by human observers. The proposed technique is particularly suitable for large-scale persistent surveillance systems with distributed soft and hard sensor networks. The efficiency and effectiveness of the proposed technique is measured experimentally by conducting several simulated persistent surveillance scenarios. It is demonstrated that by fusion of information from hard and soft agents improves understanding of common operating picture and enhances situational awareness.

The effect of occlusion therapy on motion perception deficits in amblyopia.

PubMed

Giaschi, Deborah; Chapman, Christine; Meier, Kimberly; Narasimhan, Sathyasri; Regan, David

2015-09-01

There is growing evidence for deficits in motion perception in amblyopia, but these are rarely assessed clinically. In this prospective study we examined the effect of occlusion therapy on motion-defined form perception and multiple-object tracking. Participants included children (3-10years old) with unilateral anisometropic and/or strabismic amblyopia who were currently undergoing occlusion therapy and age-matched control children with normal vision. At the start of the study, deficits in motion-defined form perception were present in at least one eye in 69% of the children with amblyopia. These deficits were still present at the end of the study in 55% of the amblyopia group. For multiple-object tracking, deficits were present initially in 64% and finally in 55% of the children with amblyopia, even after completion of occlusion therapy. Many of these deficits persisted in spite of an improvement in amblyopic eye visual acuity in response to occlusion therapy. The prevalence of motion perception deficits in amblyopia as well as their resistance to occlusion therapy, support the need for new approaches to amblyopia treatment. Copyright © 2015 Elsevier Ltd. All rights reserved.

Tracking multiple objects is limited only by object spacing, not by speed, time, or capacity.

PubMed

Franconeri, S L; Jonathan, S V; Scimeca, J M

2010-07-01

In dealing with a dynamic world, people have the ability to maintain selective attention on a subset of moving objects in the environment. Performance in such multiple-object tracking is limited by three primary factors-the number of objects that one can track, the speed at which one can track them, and how close together they can be. We argue that this last limit, of object spacing, is the root cause of all performance constraints in multiple-object tracking. In two experiments, we found that as long as the distribution of object spacing is held constant, tracking performance is unaffected by large changes in object speed and tracking time. These results suggest that barring object-spacing constraints, people could reliably track an unlimited number of objects as fast as they could track a single object.

Did Humans Live with Dinosaurs? Excavating "Man Tracks" along the Paluxy River

ERIC Educational Resources Information Center

Moore, Randy

2014-01-01

The alleged "man tracks" beside dinosaur tracks near Glen Rose, Texas, are among the most enduring pieces of evidence used by young-Earth creationists to reject evolution. Despite the tracks' fame, their most persistent advocate--that is, Carl Baugh of the Creation Evidence Museum--has published neither (1) peer-reviewed papers in…

A Cortical Network for the Encoding of Object Change

PubMed Central

Hindy, Nicholas C.; Solomon, Sarah H.; Altmann, Gerry T.M.; Thompson-Schill, Sharon L.

2015-01-01

Understanding events often requires recognizing unique stimuli as alternative, mutually exclusive states of the same persisting object. Using fMRI, we examined the neural mechanisms underlying the representation of object states and object-state changes. We found that subjective ratings of visual dissimilarity between a depicted object and an unseen alternative state of that object predicted the corresponding multivoxel pattern dissimilarity in early visual cortex during an imagery task, while late visual cortex patterns tracked dissimilarity among distinct objects. Early visual cortex pattern dissimilarity for object states in turn predicted the level of activation in an area of left posterior ventrolateral prefrontal cortex (pVLPFC) most responsive to conflict in a separate Stroop color-word interference task, and an area of left ventral posterior parietal cortex (vPPC) implicated in the relational binding of semantic features. We suggest that when visualizing object states, representational content instantiated across early and late visual cortex is modulated by processes in left pVLPFC and left vPPC that support selection and binding, and ultimately event comprehension. PMID:24127425

Radar Detection of Marine Mammals

DTIC Science & Technology

2011-09-30

BFT-BPT algorithm for use with our radar data. This track - before - detect algorithm had been effective in enhancing small but persistent signatures in...will be possible with the detect before track algorithm. 4 We next evaluated the track before detect algorithm, the BFT-BPT, on the CEDAR data

Predictors of Academic Success between On Track and Off Track Students in a Mexican University

ERIC Educational Resources Information Center

Hinojos, Jesus Francisco

2013-01-01

The main purpose of this study was to assess how predictors of quality of academic effort relate to academic success and student persistence of on-track and off-track students in a higher education institution in Northern Mexico; to investigate the relationship of pre-entry attributes, family background and academic success as expressed by GPA…

An automated data exploitation system for airborne sensors

NASA Astrophysics Data System (ADS)

Chen, Hai-Wen; McGurr, Mike

2014-06-01

Advanced wide area persistent surveillance (WAPS) sensor systems on manned or unmanned airborne vehicles are essential for wide-area urban security monitoring in order to protect our people and our warfighter from terrorist attacks. Currently, human (imagery) analysts process huge data collections from full motion video (FMV) for data exploitation and analysis (real-time and forensic), providing slow and inaccurate results. An Automated Data Exploitation System (ADES) is urgently needed. In this paper, we present a recently developed ADES for airborne vehicles under heavy urban background clutter conditions. This system includes four processes: (1) fast image registration, stabilization, and mosaicking; (2) advanced non-linear morphological moving target detection; (3) robust multiple target (vehicles, dismounts, and human) tracking (up to 100 target tracks); and (4) moving or static target/object recognition (super-resolution). Test results with real FMV data indicate that our ADES can reliably detect, track, and recognize multiple vehicles under heavy urban background clutters. Furthermore, our example shows that ADES as a baseline platform can provide capability for vehicle abnormal behavior detection to help imagery analysts quickly trace down potential threats and crimes.

Creating Mathematical Futures through an Equitable Teaching Approach: The Case of Railside School

ERIC Educational Resources Information Center

Boaler, Jo; Staples, Megan

2008-01-01

Background/Context: School tracking practices have been documented repeatedly as having negative effects on students' identity development and attainment, particularly for those students placed in lower tracks. Despite this documentation, tracking persists as a normative practice in American high schools, perhaps in part because we have few models…

Self-motion impairs multiple-object tracking.

PubMed

Thomas, Laura E; Seiffert, Adriane E

2010-10-01

Investigations of multiple-object tracking aim to further our understanding of how people perform common activities such as driving in traffic. However, tracking tasks in the laboratory have overlooked a crucial component of much real-world object tracking: self-motion. We investigated the hypothesis that keeping track of one's own movement impairs the ability to keep track of other moving objects. Participants attempted to track multiple targets while either moving around the tracking area or remaining in a fixed location. Participants' tracking performance was impaired when they moved to a new location during tracking, even when they were passively moved and when they did not see a shift in viewpoint. Self-motion impaired multiple-object tracking in both an immersive virtual environment and a real-world analog, but did not interfere with a difficult non-spatial tracking task. These results suggest that people use a common mechanism to track changes both to the location of moving objects around them and to keep track of their own location. Copyright 2010 Elsevier B.V. All rights reserved.

Isolating the incentive salience of reward-associated stimuli: value, choice, and persistence

PubMed Central

Chow, Jonathan J.

2015-01-01

Sign- and goal-tracking are differentially associated with drug abuse-related behavior. Recently, it has been hypothesized that sign- and goal-tracking behavior are mediated by different neurobehavioral valuation systems, including differential incentive salience attribution. Herein, we used different conditioned stimuli to preferentially elicit different response types to study the different incentive valuation characteristics of stimuli associated with sign- and goal-tracking within individuals. The results demonstrate that all stimuli used were equally effective conditioned stimuli; however, only a lever stimulus associated with sign-tracking behavior served as a robust conditioned reinforcer and was preferred over a tone associated with goal-tracking. Moreover, the incentive value attributed to the lever stimulus was capable of promoting suboptimal choice, leading to a significant reduction in reinforcers (food) earned. Furthermore, sign-tracking to a lever was more persistent than goal-tracking to a tone under omission and extinction contingencies. Finally, a conditional discrimination procedure demonstrated that sign-tracking to a lever and goal-tracking to a tone were dependent on learned stimulus–reinforcer relations. Collectively, these results suggest that the different neurobehavioral valuation processes proposed to govern sign- and goal-tracking behavior are independent but parallel processes within individuals. Examining these systems within individuals will provide a better understanding of how one system comes to dominate stimulus–reward learning, thus leading to the differential role these systems play in abuse-related behavior. PMID:25593298

Track Everything: Limiting Prior Knowledge in Online Multi-Object Recognition.

PubMed

Wong, Sebastien C; Stamatescu, Victor; Gatt, Adam; Kearney, David; Lee, Ivan; McDonnell, Mark D

2017-10-01

This paper addresses the problem of online tracking and classification of multiple objects in an image sequence. Our proposed solution is to first track all objects in the scene without relying on object-specific prior knowledge, which in other systems can take the form of hand-crafted features or user-based track initialization. We then classify the tracked objects with a fast-learning image classifier, that is based on a shallow convolutional neural network architecture and demonstrate that object recognition improves when this is combined with object state information from the tracking algorithm. We argue that by transferring the use of prior knowledge from the detection and tracking stages to the classification stage, we can design a robust, general purpose object recognition system with the ability to detect and track a variety of object types. We describe our biologically inspired implementation, which adaptively learns the shape and motion of tracked objects, and apply it to the Neovision2 Tower benchmark data set, which contains multiple object types. An experimental evaluation demonstrates that our approach is competitive with the state-of-the-art video object recognition systems that do make use of object-specific prior knowledge in detection and tracking, while providing additional practical advantages by virtue of its generality.

The Role of Visual Working Memory in Attentive Tracking of Unique Objects

ERIC Educational Resources Information Center

Makovski, Tal; Jiang, Yuhong V.

2009-01-01

When tracking moving objects in space humans usually attend to the objects' spatial locations and update this information over time. To what extent do surface features assist attentive tracking? In this study we asked participants to track identical or uniquely colored objects. Tracking was enhanced when objects were unique in color. The benefit…

Visual attention is required for multiple object tracking.

PubMed

Tran, Annie; Hoffman, James E

2016-12-01

In the multiple object tracking task, participants attempt to keep track of a moving set of target objects embedded in an identical set of moving distractors. Depending on several display parameters, observers are usually only able to accurately track 3 to 4 objects. Various proposals attribute this limit to a fixed number of discrete indexes (Pylyshyn, 1989), limits in visual attention (Cavanagh & Alvarez, 2005), or "architectural limits" in visual cortical areas (Franconeri, 2013). The present set of experiments examined the specific role of visual attention in tracking using a dual-task methodology in which participants tracked objects while identifying letter probes appearing on the tracked objects and distractors. As predicted by the visual attention model, probe identification was faster and/or more accurate when probes appeared on tracked objects. This was the case even when probes were more than twice as likely to appear on distractors suggesting that some minimum amount of attention is required to maintain accurate tracking performance. When the need to protect tracking accuracy was relaxed, participants were able to allocate more attention to distractors when probes were likely to appear there but only at the expense of large reductions in tracking accuracy. A final experiment showed that people attend to tracked objects even when letters appearing on them are task-irrelevant, suggesting that allocation of attention to tracked objects is an obligatory process. These results support the claim that visual attention is required for tracking objects. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Imaging Polarimeter for a Sub-MeV Gamma-Ray All-sky Survey Using an Electron-tracking Compton Camera

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

Komura, S.; Takada, A.; Mizumura, Y.

2017-04-10

X-ray and gamma-ray polarimetry is a promising tool to study the geometry and the magnetic configuration of various celestial objects, such as binary black holes or gamma-ray bursts (GRBs). However, statistically significant polarizations have been detected in few of the brightest objects. Even though future polarimeters using X-ray telescopes are expected to observe weak persistent sources, there are no effective approaches to survey transient and serendipitous sources with a wide field of view (FoV). Here we present an electron-tracking Compton camera (ETCC) as a highly sensitive gamma-ray imaging polarimeter. The ETCC provides powerful background rejection and a high modulation factormore » over an FoV of up to 2 π sr thanks to its excellent imaging based on a well-defined point-spread function. Importantly, we demonstrated for the first time the stability of the modulation factor under realistic conditions of off-axis incidence and huge backgrounds using the SPring-8 polarized X-ray beam. The measured modulation factor of the ETCC was 0.65 ± 0.01 at 150 keV for an off-axis incidence with an oblique angle of 30° and was not degraded compared to the 0.58 ± 0.02 at 130 keV for on-axis incidence. These measured results are consistent with the simulation results. Consequently, we found that the satellite-ETCC proposed in Tanimori et al. would provide all-sky surveys of weak persistent sources of 13 mCrab with 10% polarization for a 10{sup 7} s exposure and over 20 GRBs down to a 6 × 10{sup −6} erg cm{sup −2} fluence and 10% polarization during a one-year observation.« less

Imaging Polarimeter for a Sub-MeV Gamma-Ray All-sky Survey Using an Electron-tracking Compton Camera

NASA Astrophysics Data System (ADS)

Komura, S.; Takada, A.; Mizumura, Y.; Miyamoto, S.; Takemura, T.; Kishimoto, T.; Kubo, H.; Kurosawa, S.; Matsuoka, Y.; Miuchi, K.; Mizumoto, T.; Nakamasu, Y.; Nakamura, K.; Oda, M.; Parker, J. D.; Sawano, T.; Sonoda, S.; Tanimori, T.; Tomono, D.; Yoshikawa, K.

2017-04-01

X-ray and gamma-ray polarimetry is a promising tool to study the geometry and the magnetic configuration of various celestial objects, such as binary black holes or gamma-ray bursts (GRBs). However, statistically significant polarizations have been detected in few of the brightest objects. Even though future polarimeters using X-ray telescopes are expected to observe weak persistent sources, there are no effective approaches to survey transient and serendipitous sources with a wide field of view (FoV). Here we present an electron-tracking Compton camera (ETCC) as a highly sensitive gamma-ray imaging polarimeter. The ETCC provides powerful background rejection and a high modulation factor over an FoV of up to 2π sr thanks to its excellent imaging based on a well-defined point-spread function. Importantly, we demonstrated for the first time the stability of the modulation factor under realistic conditions of off-axis incidence and huge backgrounds using the SPring-8 polarized X-ray beam. The measured modulation factor of the ETCC was 0.65 ± 0.01 at 150 keV for an off-axis incidence with an oblique angle of 30° and was not degraded compared to the 0.58 ± 0.02 at 130 keV for on-axis incidence. These measured results are consistent with the simulation results. Consequently, we found that the satellite-ETCC proposed in Tanimori et al. would provide all-sky surveys of weak persistent sources of 13 mCrab with 10% polarization for a 107 s exposure and over 20 GRBs down to a 6 × 10-6 erg cm-2 fluence and 10% polarization during a one-year observation.

Automated recognition and tracking of aerosol threat plumes with an IR camera pod

NASA Astrophysics Data System (ADS)

Fauth, Ryan; Powell, Christopher; Gruber, Thomas; Clapp, Dan

2012-06-01

Protection of fixed sites from chemical, biological, or radiological aerosol plume attacks depends on early warning so that there is time to take mitigating actions. Early warning requires continuous, autonomous, and rapid coverage of large surrounding areas; however, this must be done at an affordable cost. Once a potential threat plume is detected though, a different type of sensor (e.g., a more expensive, slower sensor) may be cued for identification purposes, but the problem is to quickly identify all of the potential threats around the fixed site of interest. To address this problem of low cost, persistent, wide area surveillance, an IR camera pod and multi-image stitching and processing algorithms have been developed for automatic recognition and tracking of aerosol plumes. A rugged, modular, static pod design, which accommodates as many as four micro-bolometer IR cameras for 45deg to 180deg of azimuth coverage, is presented. Various OpenCV1 based image-processing algorithms, including stitching of multiple adjacent FOVs, recognition of aerosol plume objects, and the tracking of aerosol plumes, are presented using process block diagrams and sample field test results, including chemical and biological simulant plumes. Methods for dealing with the background removal, brightness equalization between images, and focus quality for optimal plume tracking are also discussed.

Super-resolution imaging applied to moving object tracking

NASA Astrophysics Data System (ADS)

Swalaganata, Galandaru; Ratna Sulistyaningrum, Dwi; Setiyono, Budi

2017-10-01

Moving object tracking in a video is a method used to detect and analyze changes that occur in an object that being observed. Visual quality and the precision of the tracked target are highly wished in modern tracking system. The fact that the tracked object does not always seem clear causes the tracking result less precise. The reasons are low quality video, system noise, small object, and other factors. In order to improve the precision of the tracked object especially for small object, we propose a two step solution that integrates a super-resolution technique into tracking approach. First step is super-resolution imaging applied into frame sequences. This step was done by cropping the frame in several frame or all of frame. Second step is tracking the result of super-resolution images. Super-resolution image is a technique to obtain high-resolution images from low-resolution images. In this research single frame super-resolution technique is proposed for tracking approach. Single frame super-resolution was a kind of super-resolution that it has the advantage of fast computation time. The method used for tracking is Camshift. The advantages of Camshift was simple calculation based on HSV color that use its histogram for some condition and color of the object varies. The computational complexity and large memory requirements required for the implementation of super-resolution and tracking were reduced and the precision of the tracked target was good. Experiment showed that integrate a super-resolution imaging into tracking technique can track the object precisely with various background, shape changes of the object, and in a good light conditions.

Persistence of F-specific RNA phages in surface waters from a produce production region along the central coast of California

USDA-ARS?s Scientific Manuscript database

F+ RNA coliphages (FRNA) are used to source-track fecal contamination and as surrogates for enteric pathogen persistence in the environment. However, the environmental persistence of FRNA is not clearly understood and thus we evaluated the survival of prototype and environmental isolates of FRNA rep...

Object tracking with stereo vision

NASA Technical Reports Server (NTRS)

Huber, Eric

1994-01-01

A real-time active stereo vision system incorporating gaze control and task directed vision is described. Emphasis is placed on object tracking and object size and shape determination. Techniques include motion-centroid tracking, depth tracking, and contour tracking.

Adaptive object tracking via both positive and negative models matching

NASA Astrophysics Data System (ADS)

Li, Shaomei; Gao, Chao; Wang, Yawen

2015-03-01

To improve tracking drift which often occurs in adaptive tracking, an algorithm based on the fusion of tracking and detection is proposed in this paper. Firstly, object tracking is posed as abinary classification problem and is modeled by partial least squares (PLS) analysis. Secondly, tracking object frame by frame via particle filtering. Thirdly, validating the tracking reliability based on both positive and negative models matching. Finally, relocating the object based on SIFT features matching and voting when drift occurs. Object appearance model is updated at the same time. The algorithm can not only sense tracking drift but also relocate the object whenever needed. Experimental results demonstrate that this algorithm outperforms state-of-the-art algorithms on many challenging sequences.

Considerations of persistence and security in CHOICES, an object-oriented operating system

NASA Technical Reports Server (NTRS)

Campbell, Roy H.; Madany, Peter W.

1990-01-01

The current design of the CHOICES persistent object implementation is summarized, and research in progress is outlined. CHOICES is implemented as an object-oriented system, and persistent objects appear to simplify and unify many functions of the system. It is demonstrated that persistent data can be accessed through an object-oriented file system model as efficiently as by an existing optimized commercial file system. The object-oriented file system can be specialized to provide an object store for persistent objects. The problems that arise in building an efficient persistent object scheme in a 32-bit virtual address space that only uses paging are described. Despite its limitations, the solution presented allows quite large numbers of objects to be active simultaneously, and permits sharing and efficient method calls.

How Many Objects are You Worth? Quantification of the Self-Motion Load on Multiple Object Tracking

PubMed Central

Thomas, Laura E.; Seiffert, Adriane E.

2011-01-01

Perhaps walking and chewing gum is effortless, but walking and tracking moving objects is not. Multiple object tracking is impaired by walking from one location to another, suggesting that updating location of the self puts demands on object tracking processes. Here, we quantified the cost of self-motion in terms of the tracking load. Participants in a virtual environment tracked a variable number of targets (1–5) among distractors while either staying in one place or moving along a path that was similar to the objects’ motion. At the end of each trial, participants decided whether a probed dot was a target or distractor. As in our previous work, self-motion significantly impaired performance in tracking multiple targets. Quantifying tracking capacity for each individual under move versus stay conditions further revealed that self-motion during tracking produced a cost to capacity of about 0.8 (±0.2) objects. Tracking your own motion is worth about one object, suggesting that updating the location of the self is similar, but perhaps slightly easier, than updating locations of objects. PMID:21991259

Unsupervised learning in persistent sensing for target recognition by wireless ad hoc networks of ground-based sensors

NASA Astrophysics Data System (ADS)

Hortos, William S.

2008-04-01

In previous work by the author, effective persistent and pervasive sensing for recognition and tracking of battlefield targets were seen to be achieved, using intelligent algorithms implemented by distributed mobile agents over a composite system of unmanned aerial vehicles (UAVs) for persistence and a wireless network of unattended ground sensors for pervasive coverage of the mission environment. While simulated performance results for the supervised algorithms of the composite system are shown to provide satisfactory target recognition over relatively brief periods of system operation, this performance can degrade by as much as 50% as target dynamics in the environment evolve beyond the period of system operation in which the training data are representative. To overcome this limitation, this paper applies the distributed approach using mobile agents to the network of ground-based wireless sensors alone, without the UAV subsystem, to provide persistent as well as pervasive sensing for target recognition and tracking. The supervised algorithms used in the earlier work are supplanted by unsupervised routines, including competitive-learning neural networks (CLNNs) and new versions of support vector machines (SVMs) for characterization of an unknown target environment. To capture the same physical phenomena from battlefield targets as the composite system, the suite of ground-based sensors can be expanded to include imaging and video capabilities. The spatial density of deployed sensor nodes is increased to allow more precise ground-based location and tracking of detected targets by active nodes. The "swarm" mobile agents enabling WSN intelligence are organized in a three processing stages: detection, recognition and sustained tracking of ground targets. Features formed from the compressed sensor data are down-selected according to an information-theoretic algorithm that reduces redundancy within the feature set, reducing the dimension of samples used in the target recognition and tracking routines. Target tracking is based on simplified versions of Kalman filtration. Accuracy of recognition and tracking of implemented versions of the proposed suite of unsupervised algorithms is somewhat degraded from the ideal. Target recognition and tracking by supervised routines and by unsupervised SVM and CLNN routines in the ground-based WSN is evaluated in simulations using published system values and sensor data from vehicular targets in ground-surveillance scenarios. Results are compared with previously published performance for the system of the ground-based sensor network (GSN) and UAV swarm.

Tracking planets and moons: mechanisms of object tracking revealed with a new paradigm.

PubMed

Tombu, Michael; Seiffert, Adriane E

2011-04-01

People can attend to and track multiple moving objects over time. Cognitive theories of this ability emphasize location information and differ on the importance of motion information. Results from several experiments have shown that increasing object speed impairs performance, although speed was confounded with other properties such as proximity of objects to one another. Here, we introduce a new paradigm to study multiple object tracking in which object speed and object proximity were manipulated independently. Like the motion of a planet and moon, each target-distractor pair rotated about both a common local point as well as the center of the screen. Tracking performance was strongly affected by object speed even when proximity was controlled. Additional results suggest that two different mechanisms are used in object tracking--one sensitive to speed and proximity and the other sensitive to the number of distractors. These observations support models of object tracking that include information about object motion and reject models that use location alone.

Upside-down: Perceived space affects object-based attention.

PubMed

Papenmeier, Frank; Meyerhoff, Hauke S; Brockhoff, Alisa; Jahn, Georg; Huff, Markus

2017-07-01

Object-based attention influences the subjective metrics of surrounding space. However, does perceived space influence object-based attention, as well? We used an attentive tracking task that required sustained object-based attention while objects moved within a tracking space. We manipulated perceived space through the availability of depth cues and varied the orientation of the tracking space. When rich depth cues were available (appearance of a voluminous tracking space), the upside-down orientation of the tracking space (objects appeared to move high on a ceiling) caused a pronounced impairment of tracking performance compared with an upright orientation of the tracking space (objects appeared to move on a floor plane). In contrast, this was not the case when reduced depth cues were available (appearance of a flat tracking space). With a preregistered second experiment, we showed that those effects were driven by scene-based depth cues and not object-based depth cues. We conclude that perceived space affects object-based attention and that object-based attention and perceived space are closely interlinked. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Single and multiple object tracking using log-euclidean Riemannian subspace and block-division appearance model.

PubMed

Hu, Weiming; Li, Xi; Luo, Wenhan; Zhang, Xiaoqin; Maybank, Stephen; Zhang, Zhongfei

2012-12-01

Object appearance modeling is crucial for tracking objects, especially in videos captured by nonstationary cameras and for reasoning about occlusions between multiple moving objects. Based on the log-euclidean Riemannian metric on symmetric positive definite matrices, we propose an incremental log-euclidean Riemannian subspace learning algorithm in which covariance matrices of image features are mapped into a vector space with the log-euclidean Riemannian metric. Based on the subspace learning algorithm, we develop a log-euclidean block-division appearance model which captures both the global and local spatial layout information about object appearances. Single object tracking and multi-object tracking with occlusion reasoning are then achieved by particle filtering-based Bayesian state inference. During tracking, incremental updating of the log-euclidean block-division appearance model captures changes in object appearance. For multi-object tracking, the appearance models of the objects can be updated even in the presence of occlusions. Experimental results demonstrate that the proposed tracking algorithm obtains more accurate results than six state-of-the-art tracking algorithms.

An object correlation and maneuver detection approach for space surveillance

NASA Astrophysics Data System (ADS)

Huang, Jian; Hu, Wei-Dong; Xin, Qin; Du, Xiao-Yong

2012-10-01

Object correlation and maneuver detection are persistent problems in space surveillance and maintenance of a space object catalog. We integrate these two problems into one interrelated problem, and consider them simultaneously under a scenario where space objects only perform a single in-track orbital maneuver during the time intervals between observations. We mathematically formulate this integrated scenario as a maximum a posteriori (MAP) estimation. In this work, we propose a novel approach to solve the MAP estimation. More precisely, the corresponding posterior probability of an orbital maneuver and a joint association event can be approximated by the Joint Probabilistic Data Association (JPDA) algorithm. Subsequently, the maneuvering parameters are estimated by optimally solving the constrained non-linear least squares iterative process based on the second-order cone programming (SOCP) algorithm. The desired solution is derived according to the MAP criterions. The performance and advantages of the proposed approach have been shown by both theoretical analysis and simulation results. We hope that our work will stimulate future work on space surveillance and maintenance of a space object catalog.

Initial uncertainty in Pavlovian reward prediction persistently elevates incentive salience and extends sign-tracking to normally unattractive cues.

PubMed

Robinson, Mike J F; Anselme, Patrick; Fischer, Adam M; Berridge, Kent C

2014-06-01

Uncertainty is a component of many gambling games and may play a role in incentive motivation and cue attraction. Uncertainty can increase the attractiveness for predictors of reward in the Pavlovian procedure of autoshaping, visible as enhanced sign-tracking (or approach and nibbles) by rats of a metal lever whose sudden appearance acts as a conditioned stimulus (CS+) to predict sucrose pellets as an unconditioned stimulus (UCS). Here we examined how reward uncertainty might enhance incentive salience as sign-tracking both in intensity and by broadening the range of attractive CS+s. We also examined whether initially induced uncertainty enhancements of CS+ attraction can endure beyond uncertainty itself, and persist even when Pavlovian prediction becomes 100% certain. Our results show that uncertainty can broaden incentive salience attribution to make CS cues attractive that would otherwise not be (either because they are too distal from reward or too risky to normally attract sign-tracking). In addition, uncertainty enhancement of CS+ incentive salience, once induced by initial exposure, persisted even when Pavlovian CS-UCS correlations later rose toward 100% certainty in prediction. Persistence suggests an enduring incentive motivation enhancement potentially relevant to gambling, which in some ways resembles incentive-sensitization. Higher motivation to uncertain CS+s leads to more potent attraction to these cues when they predict the delivery of uncertain rewards. In humans, those cues might possibly include the sights and sounds associated with gambling, which contribute a major component of the play immersion experienced by problematic gamblers. Copyright © 2014 Elsevier B.V. All rights reserved.

Initial uncertainty in Pavlovian reward prediction persistently elevates incentive salience and extends sign-tracking to normally unattractive cues

PubMed Central

Robinson, Mike J. F.; Anselme, Patrick; Fischer, Adam M.; Berridge, Kent C.

2014-01-01

Uncertainty is a component of many gambling games and may play a role in incentive motivation and cue attraction. Uncertainty can increase the attractiveness for predictors of reward in the Pavlovian procedure of autoshaping, visible as enhanced sign-tracking (or approach and nibbles) by rats of a metal lever whose sudden appearance acts as a conditioned stimulus (CS+) to predict sucrose pellets as an unconditioned stimulus (UCS). Here we examined how reward uncertainty might enhance incentive salience as sign-tracking both in intensity and by broadening the range of attractive CS+s. We also examined whether initially-induced uncertainty enhancements of CS+ attraction can endure beyond uncertainty itself, and persist even when Pavlovian prediction becomes 100% certain. Our results show that uncertainty can broaden incentive salience attribution to make CS cues attractive that would otherwise not be (either because they are too distal from reward or too risky to normally attract sign-tracking). In addition, uncertainty enhancement of CS+ incentive salience, once induced by initial exposure, persisted even when Pavlovian CS-UCS correlations later rose toward 100% certainty in prediction. Persistence suggests an enduring incentive motivation enhancement potentially relevant to gambling, which in some ways resembles incentive-sensitization. Higher motivation to uncertain CS+s leads to more potent attraction to these cues when they predict the delivery of uncertain rewards. In humans, those cues might possibly include the sights and sounds associated with gambling, which contribute a major component of the play immersion experienced by problematic gamblers. PMID:24631397

Multi-Object Tracking with Correlation Filter for Autonomous Vehicle.

PubMed

Zhao, Dawei; Fu, Hao; Xiao, Liang; Wu, Tao; Dai, Bin

2018-06-22

Multi-object tracking is a crucial problem for autonomous vehicle. Most state-of-the-art approaches adopt the tracking-by-detection strategy, which is a two-step procedure consisting of the detection module and the tracking module. In this paper, we improve both steps. We improve the detection module by incorporating the temporal information, which is beneficial for detecting small objects. For the tracking module, we propose a novel compressed deep Convolutional Neural Network (CNN) feature based Correlation Filter tracker. By carefully integrating these two modules, the proposed multi-object tracking approach has the ability of re-identification (ReID) once the tracked object gets lost. Extensive experiments were performed on the KITTI and MOT2015 tracking benchmarks. Results indicate that our approach outperforms most state-of-the-art tracking approaches.

Tracker Toolkit

NASA Technical Reports Server (NTRS)

Lewis, Steven J.; Palacios, David M.

2013-01-01

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

Adopting ORCID as a unique identifier will benefit all involved in scholarly communication.

PubMed

Arunachalam, Subbiah; Madhan, Muthu

2016-01-01

ORCID, the Open Researcher and Contributor ID, is a non- profit, community-driven effort to create and maintain a registry of unique researcher identifiers and a transparent method of linking research activities and outputs to these identifiers. Together with other persistent identifiers for scholarly works such as digital object identifiers (DOIs) and identifiers for organizations, ORCID makes research more discoverable. It helps ensure that one's grants, publications and outputs are correctly attributed. It helps the research community not just in aggregating publications, but in every stage of research, viz. publishing, reviewing, profiling, metrics, accessing and archiving. Funding agencies in Austria, Australia, Denmark, Portugal, Sweden and the UK, and the world's leading scholarly publishers and associations have integrated their systems with ORCID registry. Among the BRICS countries, China and South Africa are adopting ORCID avidly. India is yet to make a beginning. If research councils and funding agencies in India require researchers to adopt ORCID and link ORCID iDs to funding as well as tracking performance, it will help them keep track of the workflow. Journal editors can also keep track of contributions made by different authors and work assigned to different reviewers through their ORCID iDs.

Human-like object tracking and gaze estimation with PKD android

PubMed Central

Wijayasinghe, Indika B.; Miller, Haylie L.; Das, Sumit K; Bugnariu, Nicoleta L.; Popa, Dan O.

2018-01-01

As the use of robots increases for tasks that require human-robot interactions, it is vital that robots exhibit and understand human-like cues for effective communication. In this paper, we describe the implementation of object tracking capability on Philip K. Dick (PKD) android and a gaze tracking algorithm, both of which further robot capabilities with regard to human communication. PKD's ability to track objects with human-like head postures is achieved with visual feedback from a Kinect system and an eye camera. The goal of object tracking with human-like gestures is twofold : to facilitate better human-robot interactions and to enable PKD as a human gaze emulator for future studies. The gaze tracking system employs a mobile eye tracking system (ETG; SensoMotoric Instruments) and a motion capture system (Cortex; Motion Analysis Corp.) for tracking the head orientations. Objects to be tracked are displayed by a virtual reality system, the Computer Assisted Rehabilitation Environment (CAREN; MotekForce Link). The gaze tracking algorithm converts eye tracking data and head orientations to gaze information facilitating two objectives: to evaluate the performance of the object tracking system for PKD and to use the gaze information to predict the intentions of the user, enabling the robot to understand physical cues by humans. PMID:29416193

Human-like object tracking and gaze estimation with PKD android

NASA Astrophysics Data System (ADS)

Wijayasinghe, Indika B.; Miller, Haylie L.; Das, Sumit K.; Bugnariu, Nicoleta L.; Popa, Dan O.

2016-05-01

As the use of robots increases for tasks that require human-robot interactions, it is vital that robots exhibit and understand human-like cues for effective communication. In this paper, we describe the implementation of object tracking capability on Philip K. Dick (PKD) android and a gaze tracking algorithm, both of which further robot capabilities with regard to human communication. PKD's ability to track objects with human-like head postures is achieved with visual feedback from a Kinect system and an eye camera. The goal of object tracking with human-like gestures is twofold: to facilitate better human-robot interactions and to enable PKD as a human gaze emulator for future studies. The gaze tracking system employs a mobile eye tracking system (ETG; SensoMotoric Instruments) and a motion capture system (Cortex; Motion Analysis Corp.) for tracking the head orientations. Objects to be tracked are displayed by a virtual reality system, the Computer Assisted Rehabilitation Environment (CAREN; MotekForce Link). The gaze tracking algorithm converts eye tracking data and head orientations to gaze information facilitating two objectives: to evaluate the performance of the object tracking system for PKD and to use the gaze information to predict the intentions of the user, enabling the robot to understand physical cues by humans.

A data set for evaluating the performance of multi-class multi-object video tracking

NASA Astrophysics Data System (ADS)

Chakraborty, Avishek; Stamatescu, Victor; Wong, Sebastien C.; Wigley, Grant; Kearney, David

2017-05-01

One of the challenges in evaluating multi-object video detection, tracking and classification systems is having publically available data sets with which to compare different systems. However, the measures of performance for tracking and classification are different. Data sets that are suitable for evaluating tracking systems may not be appropriate for classification. Tracking video data sets typically only have ground truth track IDs, while classification video data sets only have ground truth class-label IDs. The former identifies the same object over multiple frames, while the latter identifies the type of object in individual frames. This paper describes an advancement of the ground truth meta-data for the DARPA Neovision2 Tower data set to allow both the evaluation of tracking and classification. The ground truth data sets presented in this paper contain unique object IDs across 5 different classes of object (Car, Bus, Truck, Person, Cyclist) for 24 videos of 871 image frames each. In addition to the object IDs and class labels, the ground truth data also contains the original bounding box coordinates together with new bounding boxes in instances where un-annotated objects were present. The unique IDs are maintained during occlusions between multiple objects or when objects re-enter the field of view. This will provide: a solid foundation for evaluating the performance of multi-object tracking of different types of objects, a straightforward comparison of tracking system performance using the standard Multi Object Tracking (MOT) framework, and classification performance using the Neovision2 metrics. These data have been hosted publically.

Real-time object detection, tracking and occlusion reasoning

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

Divakaran, Ajay; Yu, Qian; Tamrakar, Amir

A system for object detection and tracking includes technologies to, among other things, detect and track moving objects, such as pedestrians and/or vehicles, in a real-world environment, handle static and dynamic occlusions, and continue tracking moving objects across the fields of view of multiple different cameras.

Self-Motion Impairs Multiple-Object Tracking

ERIC Educational Resources Information Center

Thomas, Laura E.; Seiffert, Adriane E.

2010-01-01

Investigations of multiple-object tracking aim to further our understanding of how people perform common activities such as driving in traffic. However, tracking tasks in the laboratory have overlooked a crucial component of much real-world object tracking: self-motion. We investigated the hypothesis that keeping track of one's own movement…

Visual object recognition and tracking

NASA Technical Reports Server (NTRS)

Chang, Chu-Yin (Inventor); English, James D. (Inventor); Tardella, Neil M. (Inventor)

2010-01-01

This invention describes a method for identifying and tracking an object from two-dimensional data pictorially representing said object by an object-tracking system through processing said two-dimensional data using at least one tracker-identifier belonging to the object-tracking system for providing an output signal containing: a) a type of the object, and/or b) a position or an orientation of the object in three-dimensions, and/or c) an articulation or a shape change of said object in said three dimensions.

Structure preserving clustering-object tracking via subgroup motion pattern segmentation

NASA Astrophysics Data System (ADS)

Fan, Zheyi; Zhu, Yixuan; Jiang, Jiao; Weng, Shuqin; Liu, Zhiwen

2018-01-01

Tracking clustering objects with similar appearances simultaneously in collective scenes is a challenging task in the field of collective motion analysis. Recent work on clustering-object tracking often suffers from poor tracking accuracy and terrible real-time performance due to the neglect or the misjudgment of the motion differences among objects. To address this problem, we propose a subgroup motion pattern segmentation framework based on a multilayer clustering structure and establish spatial constraints only among objects in the same subgroup, which entails having consistent motion direction and close spatial position. In addition, the subgroup segmentation results are updated dynamically because crowd motion patterns are changeable and affected by objects' destinations and scene structures. The spatial structure information combined with the appearance similarity information is used in the structure preserving object tracking framework to track objects. Extensive experiments conducted on several datasets containing multiple real-world crowd scenes validate the accuracy and the robustness of the presented algorithm for tracking objects in collective scenes.

Microbial Community Transplant Results in Increased and Long-Term Oxalate Degradation

PubMed Central

Miller, Aaron W.; Oakeson, Kelly F.; Dale, Colin; Dearing, M. Denise

2016-01-01

Gut microbes are essential for the degradation of dietary oxalate, and this function may play a role in decreasing the incidence of kidney stones. However, many oxalate-degrading bacteria are susceptible to antibiotics and the use of oxalate-degrading probiotics has only led to an ephemeral reduction in urinary oxalate. The objective of the current study was to determine the efficacy of using whole-community microbial transplants from a wild mammalian herbivore, Neotoma albigula, to increase oxalate degradation over the long term in the laboratory rat, Rattus norvegicus. We quantified the change in total oxalate degradation in lab rats immediately after microbial transplants and at 2- and 9-month intervals following microbial transplants. Additionally, we tracked the fecal microbiota of the lab rats, with and without microbial transplants, using high-throughput Illumina sequencing of a hyper-variable region of the 16S rRNA gene. Microbial transplants resulted in a significant increase in oxalate degradation, an effect that persisted 9 months after the initial transplants. Functional persistence was corroborated by the transfer, and persistence of a group of bacteria previously correlated with oxalate consumption in N. albigula, including an anaerobic bacterium from the genus Oxalobacter known for its ability to use oxalate as a sole carbon source. The results of this study indicate that whole-community microbial transplants are an effective means for the persistent colonization of oxalate-degrading bacteria in the mammalian gut. PMID:27312892

Multiple object tracking with non-unique data-to-object association via generalized hypothesis testing. [tracking several aircraft near each other or ships at sea

NASA Technical Reports Server (NTRS)

Porter, D. W.; Lefler, R. M.

1979-01-01

A generalized hypothesis testing approach is applied to the problem of tracking several objects where several different associations of data with objects are possible. Such problems occur, for instance, when attempting to distinctly track several aircraft maneuvering near each other or when tracking ships at sea. Conceptually, the problem is solved by first, associating data with objects in a statistically reasonable fashion and then, tracking with a bank of Kalman filters. The objects are assumed to have motion characterized by a fixed but unknown deterministic portion plus a random process portion modeled by a shaping filter. For example, the object might be assumed to have a mean straight line path about which it maneuvers in a random manner. Several hypothesized associations of data with objects are possible because of ambiguity as to which object the data comes from, false alarm/detection errors, and possible uncertainty in the number of objects being tracked. The statistical likelihood function is computed for each possible hypothesized association of data with objects. Then the generalized likelihood is computed by maximizing the likelihood over parameters that define the deterministic motion of the object.

Tracking of multiple targets using online learning for reference model adaptation.

PubMed

Pernkopf, Franz

2008-12-01

Recently, much work has been done in multiple object tracking on the one hand and on reference model adaptation for a single-object tracker on the other side. In this paper, we do both tracking of multiple objects (faces of people) in a meeting scenario and online learning to incrementally update the models of the tracked objects to account for appearance changes during tracking. Additionally, we automatically initialize and terminate tracking of individual objects based on low-level features, i.e., face color, face size, and object movement. Many methods unlike our approach assume that the target region has been initialized by hand in the first frame. For tracking, a particle filter is incorporated to propagate sample distributions over time. We discuss the close relationship between our implemented tracker based on particle filters and genetic algorithms. Numerous experiments on meeting data demonstrate the capabilities of our tracking approach. Additionally, we provide an empirical verification of the reference model learning during tracking of indoor and outdoor scenes which supports a more robust tracking. Therefore, we report the average of the standard deviation of the trajectories over numerous tracking runs depending on the learning rate.

Tracking planets and moons: mechanisms of object tracking revealed with a new paradigm

PubMed Central

Tombu, Michael

2014-01-01

People can attend to and track multiple moving objects over time. Cognitive theories of this ability emphasize location information and differ on the importance of motion information. Results from several experiments have shown that increasing object speed impairs performance, although speed was confounded with other properties such as proximity of objects to one another. Here, we introduce a new paradigm to study multiple object tracking in which object speed and object proximity were manipulated independently. Like the motion of a planet and moon, each target–distractor pair rotated about both a common local point as well as the center of the screen. Tracking performance was strongly affected by object speed even when proximity was controlled. Additional results suggest that two different mechanisms are used in object tracking—one sensitive to speed and proximity and the other sensitive to the number of distractors. These observations support models of object tracking that include information about object motion and reject models that use location alone. PMID:21264704

Predictability of tropical cyclone events on intraseasonal timescales with the ECMWF monthly forecast model

NASA Astrophysics Data System (ADS)

Elsberry, Russell L.; Jordan, Mary S.; Vitart, Frederic

2010-05-01

The objective of this study is to provide evidence of predictability on intraseasonal time scales (10-30 days) for western North Pacific tropical cyclone formation and subsequent tracks using the 51-member ECMWF 32-day forecasts made once a week from 5 June through 25 December 2008. Ensemble storms are defined by grouping ensemble member vortices whose positions are within a specified separation distance that is equal to 180 n mi at the initial forecast time t and increases linearly to 420 n mi at Day 14 and then is constant. The 12-h track segments are calculated with a Weighted-Mean Vector Motion technique in which the weighting factor is inversely proportional to the distance from the endpoint of the previous 12-h motion vector. Seventy-six percent of the ensemble storms had five or fewer member vortices. On average, the ensemble storms begin 2.5 days before the first entry of the Joint Typhoon Warning Center (JTWC) best-track file, tend to translate too slowly in the deep tropics, and persist for longer periods over land. A strict objective matching technique with the JTWC storms is combined with a second subjective procedure that is then applied to identify nearby ensemble storms that would indicate a greater likelihood of a tropical cyclone developing in that region with that track orientation. The ensemble storms identified in the ECMWF 32-day forecasts provided guidance on intraseasonal timescales of the formations and tracks of the three strongest typhoons and two other typhoons, but not for two early season typhoons and the late season Dolphin. Four strong tropical storms were predicted consistently over Week-1 through Week-4, as was one weak tropical storm. Two other weak tropical storms, three tropical cyclones that developed from precursor baroclinic systems, and three other tropical depressions were not predicted on intraseasonal timescales. At least for the strongest tropical cyclones during the peak season, the ECMWF 32-day ensemble provides guidance of formation and tracks on 10-30 day timescales.

Computer-aided target tracking in motion analysis studies

NASA Astrophysics Data System (ADS)

Burdick, Dominic C.; Marcuse, M. L.; Mislan, J. D.

1990-08-01

Motion analysis studies require the precise tracking of reference objects in sequential scenes. In a typical situation, events of interest are captured at high frame rates using special cameras, and selected objects or targets are tracked on a frame by frame basis to provide necessary data for motion reconstruction. Tracking is usually done using manual methods which are slow and prone to error. A computer based image analysis system has been developed that performs tracking automatically. The objective of this work was to eliminate the bottleneck due to manual methods in high volume tracking applications such as the analysis of crash test films for the automotive industry. The system has proven to be successful in tracking standard fiducial targets and other objects in crash test scenes. Over 95 percent of target positions which could be located using manual methods can be tracked by the system, with a significant improvement in throughput over manual methods. Future work will focus on the tracking of clusters of targets and on tracking deformable objects such as airbags.

Persistence in a Two-Dimensional Moving-Habitat Model.

PubMed

Phillips, Austin; Kot, Mark

2015-11-01

Environmental changes are forcing many species to track suitable conditions or face extinction. In this study, we use a two-dimensional integrodifference equation to analyze whether a population can track a habitat that is moving due to climate change. We model habitat as a simple rectangle. Our model quickly leads to an eigenvalue problem that determines whether the population persists or declines. After surveying techniques to solve the eigenvalue problem, we highlight three findings that impact conservation efforts such as reserve design and species risk assessment. First, while other models focus on habitat length (parallel to the direction of habitat movement), we show that ignoring habitat width (perpendicular to habitat movement) can lead to overestimates of persistence. Dispersal barriers and hostile landscapes that constrain habitat width greatly decrease the population's ability to track its habitat. Second, for some long-distance dispersal kernels, increasing habitat length improves persistence without limit; for other kernels, increasing length is of limited help and has diminishing returns. Third, it is not always best to orient the long side of the habitat in the direction of climate change. Evidence suggests that the kurtosis of the dispersal kernel determines whether it is best to have a long, wide, or square habitat. In particular, populations with platykurtic dispersal benefit more from a wide habitat, while those with leptokurtic dispersal benefit more from a long habitat. We apply our model to the Rocky Mountain Apollo butterfly (Parnassius smintheus).

Multiple-object tracking while driving: the multiple-vehicle tracking task.

PubMed

Lochner, Martin J; Trick, Lana M

2014-11-01

Many contend that driving an automobile involves multiple-object tracking. At this point, no one has tested this idea, and it is unclear how multiple-object tracking would coordinate with the other activities involved in driving. To address some of the initial and most basic questions about multiple-object tracking while driving, we modified the tracking task for use in a driving simulator, creating the multiple-vehicle tracking task. In Experiment 1, we employed a dual-task methodology to determine whether there was interference between tracking and driving. Findings suggest that although it is possible to track multiple vehicles while driving, driving reduces tracking performance, and tracking compromises headway and lane position maintenance while driving. Modified change-detection paradigms were used to assess whether there were change localization advantages for tracked targets in multiple-vehicle tracking. When changes occurred during a blanking interval, drivers were more accurate (Experiment 2a) and ~250 ms faster (Experiment 2b) at locating the vehicle that changed when it was a target rather than a distractor in tracking. In a more realistic driving task where drivers had to brake in response to the sudden onset of brake lights in one of the lead vehicles, drivers were more accurate at localizing the vehicle that braked if it was a tracking target, although there was no advantage in terms of braking response time. Overall, results suggest that multiple-object tracking is possible while driving and perhaps even advantageous in some situations, but further research is required to determine whether multiple-object tracking is actually used in day-to-day driving.

Enrollment Factors that Predict Persistence of At-Risk (Low Income and First Generation) Students' Journey towards Completion of a Baccalaureate Degree at Idaho State University

ERIC Educational Resources Information Center

Yizar, James H., Jr.

2010-01-01

The purpose of this study was to explore, track, and predict longitudinal differences (over the course of six years beginning fall semester 2001) between and among ISU low income, first generation, or the combination of low income and first generation freshman students; regarding persistence rate, and associated persistence factors, such as ACT…

Learned filters for object detection in multi-object visual tracking

NASA Astrophysics Data System (ADS)

Stamatescu, Victor; Wong, Sebastien; McDonnell, Mark D.; Kearney, David

2016-05-01

We investigate the application of learned convolutional filters in multi-object visual tracking. The filters were learned in both a supervised and unsupervised manner from image data using artificial neural networks. This work follows recent results in the field of machine learning that demonstrate the use learned filters for enhanced object detection and classification. Here we employ a track-before-detect approach to multi-object tracking, where tracking guides the detection process. The object detection provides a probabilistic input image calculated by selecting from features obtained using banks of generative or discriminative learned filters. We present a systematic evaluation of these convolutional filters using a real-world data set that examines their performance as generic object detectors.

Reliability of a single objective measure in assessing sleepiness.

PubMed

Sunwoo, Bernie Y; Jackson, Nicholas; Maislin, Greg; Gurubhagavatula, Indira; George, Charles F; Pack, Allan I

2012-01-01

To evaluate reliability of single objective tests in assessing sleepiness. Subjects who completed polysomnography underwent a 4-nap multiple sleep latency test (MSLT) the following day. Prior to each nap opportunity on MSLT, subjects performed the psychomotor vigilance test (PVT) and divided attention driving task (DADT). Results of single versus multiple test administrations were compared using the intraclass correlation coefficient (ICC) and adjusted for test administration order effects to explore time of day effects. Measures were explored as continuous and binary (i.e., impaired or not impaired). Community-based sample evaluated at a tertiary, university-based sleep center. 372 adult commercial vehicle operators oversampled for increased obstructive sleep apnea risk. N/A. AS CONTINUOUS MEASURES, ICC WERE AS FOLLOWS: MSLT 0.45, PVT median response time 0.69, PVT number of lapses 0.51, 10-min DADT tracking error 0.87, 20-min DADT tracking error 0.90. Based on binary outcomes, ICC were: MSLT 0.63, PVT number of lapses 0.85, 10-min DADT 0.95, 20-min DADT 0.96. Statistically significant time of day effects were seen in both the MSLT and PVT but not the DADT. Correlation between ESS and different objective tests was strongest for MSLT, range [-0.270 to -0.195] and persisted across all time points. Single DADT and PVT administrations are reliable measures of sleepiness. A single MSLT administration can reasonably discriminate individuals with MSL < 8 minutes. These results support the use of a single administration of some objective tests of sleepiness when performed under controlled conditions in routine clinical care.

Novel Methods for Analysing Bacterial Tracks Reveal Persistence in Rhodobacter sphaeroides

PubMed Central

Rosser, Gabriel; Fletcher, Alexander G.; Wilkinson, David A.; de Beyer, Jennifer A.; Yates, Christian A.; Armitage, Judith P.; Maini, Philip K.; Baker, Ruth E.

2013-01-01

Tracking bacteria using video microscopy is a powerful experimental approach to probe their motile behaviour. The trajectories obtained contain much information relating to the complex patterns of bacterial motility. However, methods for the quantitative analysis of such data are limited. Most swimming bacteria move in approximately straight lines, interspersed with random reorientation phases. It is therefore necessary to segment observed tracks into swimming and reorientation phases to extract useful statistics. We present novel robust analysis tools to discern these two phases in tracks. Our methods comprise a simple and effective protocol for removing spurious tracks from tracking datasets, followed by analysis based on a two-state hidden Markov model, taking advantage of the availability of mutant strains that exhibit swimming-only or reorientating-only motion to generate an empirical prior distribution. Using simulated tracks with varying levels of added noise, we validate our methods and compare them with an existing heuristic method. To our knowledge this is the first example of a systematic assessment of analysis methods in this field. The new methods are substantially more robust to noise and introduce less systematic bias than the heuristic method. We apply our methods to tracks obtained from the bacterial species Rhodobacter sphaeroides and Escherichia coli. Our results demonstrate that R. sphaeroides exhibits persistence over the course of a tumbling event, which is a novel result with important implications in the study of this and similar species. PMID:24204227

Automated Cloud Observation for Ground Telescope Optimization

NASA Astrophysics Data System (ADS)

Lane, B.; Jeffries, M. W., Jr.; Therien, W.; Nguyen, H.

As the number of man-made objects placed in space each year increases with advancements in commercial, academic and industry, the number of objects required to be detected, tracked, and characterized continues to grow at an exponential rate. Commercial companies, such as ExoAnalytic Solutions, have deployed ground based sensors to maintain track custody of these objects. For the ExoAnalytic Global Telescope Network (EGTN), observation of such objects are collected at the rate of over 10 million unique observations per month (as of September 2017). Currently, the EGTN does not optimally collect data on nights with significant cloud levels. However, a majority of these nights prove to be partially cloudy providing clear portions in the sky for EGTN sensors to observe. It proves useful for a telescope to utilize these clear areas to continue resident space object (RSO) observation. By dynamically updating the tasking with the varying cloud positions, the number of observations could potentially increase dramatically due to increased persistence, cadence, and revisit. This paper will discuss the recent algorithms being implemented within the EGTN, including the motivation, need, and general design. The use of automated image processing as well as various edge detection methods, including Canny, Sobel, and Marching Squares, on real-time large FOV images of the sky enhance the tasking and scheduling of a ground based telescope is discussed in Section 2. Implementations of these algorithms on single and expanding to multiple telescopes, will be explored. Results of applying these algorithms to the EGTN in real-time and comparison to non-optimized EGTN tasking is presented in Section 3. Finally, in Section 4 we explore future work in applying these throughout the EGTN as well as other optical telescopes.

The what-where trade-off in multiple-identity tracking.

PubMed

Cohen, Michael A; Pinto, Yair; Howe, Piers D L; Horowitz, Todd S

2011-07-01

Observers are poor at reporting the identities of objects that they have successfully tracked (Pylyshyn, Visual Cognition, 11, 801-822, 2004; Scholl & Pylyshyn, Cognitive Psychology, 38, 259-290, 1999). Consequently, it has been claimed that objects are tracked in a manner that does not encode their identities (Pylyshyn, 2004). Here, we present evidence that disputes this claim. In a series of experiments, we show that attempting to track the identities of objects can decrease an observer's ability to track the objects' locations. This indicates that the mechanisms that track, respectively, the locations and identities of objects draw upon a common resource. Furthermore, we show that this common resource can be voluntarily distributed between the two mechanisms. This is clear evidence that the location- and identity-tracking mechanisms are not entirely dissociable.

Isolating the Incentive Salience of Reward-Associated Stimuli: Value, Choice, and Persistence

ERIC Educational Resources Information Center

Beckmann, Joshua S.; Chow, Jonathan J.

2015-01-01

Sign- and goal-tracking are differentially associated with drug abuse-related behavior. Recently, it has been hypothesized that sign- and goal-tracking behavior are mediated by different neurobehavioral valuation systems, including differential incentive salience attribution. Herein, we used different conditioned stimuli to preferentially elicit…

Can we track holes?

PubMed Central

Horowitz, Todd S.; Kuzmova, Yoana

2011-01-01

The evidence is mixed as to whether the visual system treats objects and holes differently. We used a multiple object tracking task to test the hypothesis that figural objects are easier to track than holes. Observers tracked four of eight items (holes or objects). We used an adaptive algorithm to estimate the speed allowing 75% tracking accuracy. In Experiments 1–5, the distinction between holes and figures was accomplished by pictorial cues, while red-cyan anaglyphs were used to provide the illusion of depth in Experiment 6. We variously used Gaussian pixel noise, photographic scenes, or synthetic textures as backgrounds. Tracking was more difficult when a complex background was visible, as opposed to a blank background. Tracking was easier when disks carried fixed, unique markings. When these factors were controlled for, tracking holes was no more difficult than tracking figures, suggesting that they are equivalent stimuli for tracking purposes. PMID:21334361

Cortical Circuit for Binding Object Identity and Location During Multiple-Object Tracking

PubMed Central

Nummenmaa, Lauri; Oksama, Lauri; Glerean, Erico; Hyönä, Jukka

2017-01-01

Abstract Sustained multifocal attention for moving targets requires binding object identities with their locations. The brain mechanisms of identity-location binding during attentive tracking have remained unresolved. In 2 functional magnetic resonance imaging experiments, we measured participants’ hemodynamic activity during attentive tracking of multiple objects with equivalent (multiple-object tracking) versus distinct (multiple identity tracking, MIT) identities. Task load was manipulated parametrically. Both tasks activated large frontoparietal circuits. MIT led to significantly increased activity in frontoparietal and temporal systems subserving object recognition and working memory. These effects were replicated when eye movements were prohibited. MIT was associated with significantly increased functional connectivity between lateral temporal and frontal and parietal regions. We propose that coordinated activity of this network subserves identity-location binding during attentive tracking. PMID:27913430

Long-term scale adaptive tracking with kernel correlation filters

NASA Astrophysics Data System (ADS)

Wang, Yueren; Zhang, Hong; Zhang, Lei; Yang, Yifan; Sun, Mingui

2018-04-01

Object tracking in video sequences has broad applications in both military and civilian domains. However, as the length of input video sequence increases, a number of problems arise, such as severe object occlusion, object appearance variation, and object out-of-view (some portion or the entire object leaves the image space). To deal with these problems and identify the object being tracked from cluttered background, we present a robust appearance model using Speeded Up Robust Features (SURF) and advanced integrated features consisting of the Felzenszwalb's Histogram of Oriented Gradients (FHOG) and color attributes. Since re-detection is essential in long-term tracking, we develop an effective object re-detection strategy based on moving area detection. We employ the popular kernel correlation filters in our algorithm design, which facilitates high-speed object tracking. Our evaluation using the CVPR2013 Object Tracking Benchmark (OTB2013) dataset illustrates that the proposed algorithm outperforms reference state-of-the-art trackers in various challenging scenarios.

Real-Time Occlusion Handling in Augmented Reality Based on an Object Tracking Approach

PubMed Central

Tian, Yuan; Guan, Tao; Wang, Cheng

2010-01-01

To produce a realistic augmentation in Augmented Reality, the correct relative positions of real objects and virtual objects are very important. In this paper, we propose a novel real-time occlusion handling method based on an object tracking approach. Our method is divided into three steps: selection of the occluding object, object tracking and occlusion handling. The user selects the occluding object using an interactive segmentation method. The contour of the selected object is then tracked in the subsequent frames in real-time. In the occlusion handling step, all the pixels on the tracked object are redrawn on the unprocessed augmented image to produce a new synthesized image in which the relative position between the real and virtual object is correct. The proposed method has several advantages. First, it is robust and stable, since it remains effective when the camera is moved through large changes of viewing angles and volumes or when the object and the background have similar colors. Second, it is fast, since the real object can be tracked in real-time. Last, a smoothing technique provides seamless merging between the augmented and virtual object. Several experiments are provided to validate the performance of the proposed method. PMID:22319278

Studying visual attention using the multiple object tracking paradigm: A tutorial review.

PubMed

Meyerhoff, Hauke S; Papenmeier, Frank; Huff, Markus

2017-07-01

Human observers are capable of tracking multiple objects among identical distractors based only on their spatiotemporal information. Since the first report of this ability in the seminal work of Pylyshyn and Storm (1988, Spatial Vision, 3, 179-197), multiple object tracking has attracted many researchers. A reason for this is that it is commonly argued that the attentional processes studied with the multiple object paradigm apparently match the attentional processing during real-world tasks such as driving or team sports. We argue that multiple object tracking provides a good mean to study the broader topic of continuous and dynamic visual attention. Indeed, several (partially contradicting) theories of attentive tracking have been proposed within the almost 30 years since its first report, and a large body of research has been conducted to test these theories. With regard to the richness and diversity of this literature, the aim of this tutorial review is to provide researchers who are new in the field of multiple object tracking with an overview over the multiple object tracking paradigm, its basic manipulations, as well as links to other paradigms investigating visual attention and working memory. Further, we aim at reviewing current theories of tracking as well as their empirical evidence. Finally, we review the state of the art in the most prominent research fields of multiple object tracking and how this research has helped to understand visual attention in dynamic settings.

Object tracking using plenoptic image sequences

NASA Astrophysics Data System (ADS)

Kim, Jae Woo; Bae, Seong-Joon; Park, Seongjin; Kim, Do Hyung

2017-05-01

Object tracking is a very important problem in computer vision research. Among the difficulties of object tracking, partial occlusion problem is one of the most serious and challenging problems. To address the problem, we proposed novel approaches to object tracking on plenoptic image sequences. Our approaches take advantage of the refocusing capability that plenoptic images provide. Our approaches input the sequences of focal stacks constructed from plenoptic image sequences. The proposed image selection algorithms select the sequence of optimal images that can maximize the tracking accuracy from the sequence of focal stacks. Focus measure approach and confidence measure approach were proposed for image selection and both of the approaches were validated by the experiments using thirteen plenoptic image sequences that include heavily occluded target objects. The experimental results showed that the proposed approaches were satisfactory comparing to the conventional 2D object tracking algorithms.

A Mobile Service Oriented Multiple Object Tracking Augmented Reality Architecture for Education and Learning Experiences

ERIC Educational Resources Information Center

Rattanarungrot, Sasithorn; White, Martin; Newbury, Paul

2014-01-01

This paper describes the design of our service-oriented architecture to support mobile multiple object tracking augmented reality applications applied to education and learning scenarios. The architecture is composed of a mobile multiple object tracking augmented reality client, a web service framework, and dynamic content providers. Tracking of…

Confidence-Based Data Association and Discriminative Deep Appearance Learning for Robust Online Multi-Object Tracking.

PubMed

Bae, Seung-Hwan; Yoon, Kuk-Jin

2018-03-01

Online multi-object tracking aims at estimating the tracks of multiple objects instantly with each incoming frame and the information provided up to the moment. It still remains a difficult problem in complex scenes, because of the large ambiguity in associating multiple objects in consecutive frames and the low discriminability between objects appearances. In this paper, we propose a robust online multi-object tracking method that can handle these difficulties effectively. We first define the tracklet confidence using the detectability and continuity of a tracklet, and decompose a multi-object tracking problem into small subproblems based on the tracklet confidence. We then solve the online multi-object tracking problem by associating tracklets and detections in different ways according to their confidence values. Based on this strategy, tracklets sequentially grow with online-provided detections, and fragmented tracklets are linked up with others without any iterative and expensive association steps. For more reliable association between tracklets and detections, we also propose a deep appearance learning method to learn a discriminative appearance model from large training datasets, since the conventional appearance learning methods do not provide rich representation that can distinguish multiple objects with large appearance variations. In addition, we combine online transfer learning for improving appearance discriminability by adapting the pre-trained deep model during online tracking. Experiments with challenging public datasets show distinct performance improvement over other state-of-the-arts batch and online tracking methods, and prove the effect and usefulness of the proposed methods for online multi-object tracking.

Language Profiles and Literacy Outcomes of Children with Resolving, Emerging, or Persisting Language Impairments

ERIC Educational Resources Information Center

Snowling, Margaret J.; Duff, Fiona J.; Nash, Hannah M.; Hulme, Charles

2016-01-01

Background: Children with language impairment (LI) show heterogeneity in development. We tracked children from pre-school to middle childhood to characterize three developmental trajectories: resolving, persisting and emerging LI. Methods: We analyzed data from children identified as having preschool LI, or being at family risk of dyslexia,…

Tracking Change in Children with Severe and Persisting Speech Difficulties

ERIC Educational Resources Information Center

Newbold, Elisabeth Joy; Stackhouse, Joy; Wells, Bill

2013-01-01

Standardised tests of whole-word accuracy are popular in the speech pathology and developmental psychology literature as measures of children's speech performance. However, they may not be sensitive enough to measure changes in speech output in children with severe and persisting speech difficulties (SPSD). To identify the best ways of doing this,…

Tracking the Evolution of Cerebral Gadolinium-Enhancing Lesions to Persistent T1 Black Holes in Multiple Sclerosis: Validation of a Semiautomated Pipeline.

PubMed

Andermatt, Simon; Papadopoulou, Athina; Radue, Ernst-Wilhelm; Sprenger, Till; Cattin, Philippe

2017-09-01

Some gadolinium-enhancing multiple sclerosis (MS) lesions remain T1-hypointense over months ("persistent black holes, BHs") and represent areas of pronounced tissue loss. A reduced conversion of enhancing lesions to persistent BHs could suggest a favorable effect of a medication on tissue repair. However, the individual tracking of enhancing lesions can be very time-consuming in large clinical trials. We created a semiautomated workflow for tracking the evolution of individual MS lesions, to calculate the proportion of enhancing lesions becoming persistent BHs at follow-up. Our workflow automatically coregisters, compares, and detects overlaps between lesion masks at different time points. We tested the algorithm in a data set of Magnetic Resonance images (1.5 and 3T; spin-echo T1-sequences) from a phase 3 clinical trial (n = 1,272), in which all enhancing lesions and all BHs had been previously segmented at baseline and year 2. The algorithm analyzed the segmentation masks in a longitudinal fashion to determine which enhancing lesions at baseline turned into BHs at year 2. Images of 50 patients (192 enhancing lesions) were also reviewed by an experienced MRI rater, blinded to the algorithm results. In this MRI data set, there were no cases that could not be processed by the algorithm. At year 2, 417 lesions were classified as persistent BHs (417/1,613 = 25.9%). The agreement between the rater and the algorithm was > 98%. Due to the semiautomated procedure, this algorithm can be of great value in the analysis of large clinical trials, when a rater-based analysis would be time-consuming. Copyright © 2017 by the American Society of Neuroimaging.

Persistent identifiers for CMIP6 data in the Earth System Grid Federation

NASA Astrophysics Data System (ADS)

Buurman, Merret; Weigel, Tobias; Juckes, Martin; Lautenschlager, Michael; Kindermann, Stephan

2016-04-01

The Earth System Grid Federation (ESGF) is a distributed data infrastructure that will provide access to the CMIP6 experiment data. The data consist of thousands of datasets composed of millions of files. Over the course of the CMIP6 operational phase, datasets may be retracted and replaced by newer versions that consist of completely or partly new files. Each dataset is hosted at a single data centre, but can have one or several backups (replicas) at other data centres. To keep track of the different data entities and relationships between them, to ensure their consistency and improve exchange of information about them, Persistent Identifiers (PIDs) are used. These are unique identifiers that are registered at a globally accessible server, along with some metadata (the PID record). While usually providing access to the data object they refer to, as long as it exists, the metadata record will remain available even beyond the object's lifetime. Besides providing access to data and metadata, PIDs will allow scientists to communicate effectively and on a fine granularity about CMIP6 data. The initiative to introduce PIDs in the ESGF infrastructure has been described and agreed upon through a series of white papers governed by the WGCM Infrastructure Panel (WIP). In CMIP6, each dataset and each file is assigned a PID that keeps track of the data object's physical copies throughout the object lifetime. In addition to this, its relationship with other data objects is stored in the PID recordA human-readable version of this information is available on an information page also linked in the PID record. A possible application that exploits the information available from the PID records is a smart information tool, which a scientific user can call to find out if his/her version was replaced by a new one, to view and browse the related datasets and files, and to get access to the various copies or to additional metadata on a dedicated website. The PID registration process is embedded in the ESGF data publication process. During their first publication, the PID records are populated with metadata including the parent dataset(s), other existing versions and physical location. Every subsequent publication, un-publication or replica publication of a dataset or file then updates the PID records to keep track of changing physical locations of the data (or lack thereof) and of reported errors in the data. Assembling the metadata records and registering the PIDs on a central server is a potential performance bottleneck as millions of data objects may be published in a short timeframe when the CMIP6 experiment phase begins. For this reason, the PID registration and metadata update tasks are pushed to a message queueing system facilitating high availability and scalability and then processed asynchronously. This will lead to a slight delay in PID registration but will avoid blocking resources at the data centres and slowing down the publication of the data so eagerly awaited by the scientists.

Adaptive learning compressive tracking based on Markov location prediction

NASA Astrophysics Data System (ADS)

Zhou, Xingyu; Fu, Dongmei; Yang, Tao; Shi, Yanan

2017-03-01

Object tracking is an interdisciplinary research topic in image processing, pattern recognition, and computer vision which has theoretical and practical application value in video surveillance, virtual reality, and automatic navigation. Compressive tracking (CT) has many advantages, such as efficiency and accuracy. However, when there are object occlusion, abrupt motion and blur, similar objects, and scale changing, the CT has the problem of tracking drift. We propose the Markov object location prediction to get the initial position of the object. Then CT is used to locate the object accurately, and the classifier parameter adaptive updating strategy is given based on the confidence map. At the same time according to the object location, extract the scale features, which is able to deal with object scale variations effectively. Experimental results show that the proposed algorithm has better tracking accuracy and robustness than current advanced algorithms and achieves real-time performance.

Nonlinear dynamic model for visual object tracking on Grassmann manifolds with partial occlusion handling.

PubMed

Khan, Zulfiqar Hasan; Gu, Irene Yu-Hua

2013-12-01

This paper proposes a novel Bayesian online learning and tracking scheme for video objects on Grassmann manifolds. Although manifold visual object tracking is promising, large and fast nonplanar (or out-of-plane) pose changes and long-term partial occlusions of deformable objects in video remain a challenge that limits the tracking performance. The proposed method tackles these problems with the main novelties on: 1) online estimation of object appearances on Grassmann manifolds; 2) optimal criterion-based occlusion handling for online updating of object appearances; 3) a nonlinear dynamic model for both the appearance basis matrix and its velocity; and 4) Bayesian formulations, separately for the tracking process and the online learning process, that are realized by employing two particle filters: one is on the manifold for generating appearance particles and another on the linear space for generating affine box particles. Tracking and online updating are performed in an alternating fashion to mitigate the tracking drift. Experiments using the proposed tracker on videos captured by a single dynamic/static camera have shown robust tracking performance, particularly for scenarios when target objects contain significant nonplanar pose changes and long-term partial occlusions. Comparisons with eight existing state-of-the-art/most relevant manifold/nonmanifold trackers with evaluations have provided further support to the proposed scheme.

Real-time reliability measure-driven multi-hypothesis tracking using 2D and 3D features

NASA Astrophysics Data System (ADS)

Zúñiga, Marcos D.; Brémond, François; Thonnat, Monique

2011-12-01

We propose a new multi-target tracking approach, which is able to reliably track multiple objects even with poor segmentation results due to noisy environments. The approach takes advantage of a new dual object model combining 2D and 3D features through reliability measures. In order to obtain these 3D features, a new classifier associates an object class label to each moving region (e.g. person, vehicle), a parallelepiped model and visual reliability measures of its attributes. These reliability measures allow to properly weight the contribution of noisy, erroneous or false data in order to better maintain the integrity of the object dynamics model. Then, a new multi-target tracking algorithm uses these object descriptions to generate tracking hypotheses about the objects moving in the scene. This tracking approach is able to manage many-to-many visual target correspondences. For achieving this characteristic, the algorithm takes advantage of 3D models for merging dissociated visual evidence (moving regions) potentially corresponding to the same real object, according to previously obtained information. The tracking approach has been validated using video surveillance benchmarks publicly accessible. The obtained performance is real time and the results are competitive compared with other tracking algorithms, with minimal (or null) reconfiguration effort between different videos.

Multiple objects tracking in fluorescence microscopy.

PubMed

Kalaidzidis, Yannis

2009-01-01

Many processes in cell biology are connected to the movement of compact entities: intracellular vesicles and even single molecules. The tracking of individual objects is important for understanding cellular dynamics. Here we describe the tracking algorithms which have been developed in the non-biological fields and successfully applied to object detection and tracking in biological applications. The characteristics features of the different algorithms are compared.

Constraints on Multiple Object Tracking in Williams Syndrome: How Atypical Development Can Inform Theories of Visual Processing

ERIC Educational Resources Information Center

Ferrara, Katrina; Hoffman, James E.; O'Hearn, Kirsten; Landau, Barbara

2016-01-01

The ability to track moving objects is a crucial skill for performance in everyday spatial tasks. The tracking mechanism depends on representation of moving items as coherent entities, which follow the spatiotemporal constraints of objects in the world. In the present experiment, participants tracked 1 to 4 targets in a display of 8 identical…

Maintaining the ties that bind: the role of an intermediate visual memory store in the persistence of awareness.

PubMed

Ferber, Susanne; Emrich, Stephen M

2007-03-01

Segregation and feature binding are essential to the perception and awareness of objects in a visual scene. When a fragmented line-drawing of an object moves relative to a background of randomly oriented lines, the previously hidden object is segregated from the background and consequently enters awareness. Interestingly, in such shape-from-motion displays, the percept of the object persists briefly when the motion stops, suggesting that the segregated and bound representation of the object is maintained in awareness. Here, we tested whether this persistence effect is mediated by capacity-limited working-memory processes, or by the amount of object-related information available. The experiments demonstrate that persistence is affected mainly by the proportion of object information available and is independent of working-memory limits. We suggest that this persistence effect can be seen as evidence for an intermediate, form-based memory store mediating between sensory and working memory.

Evidence of Structure and Persistence in Motivational Attraction to Serial Pavlovian Cues

ERIC Educational Resources Information Center

Smedley, Elizabeth B.; Smith, Kyle S.

2018-01-01

Sign-tracking is a form of autoshaping where animals develop conditioned responding directed toward stimuli predictive of an outcome even though the outcome is not contingent on the animal's behavior. Sign-tracking behaviors are thought to arise out of the attribution of incentive salience (i.e., motivational value) to reward-predictive cues. It…

Yearly Success and Progress Rates (Fall 2010 Entering Cohort). Snapshot™ Report

ERIC Educational Resources Information Center

National Student Clearinghouse, 2017

2017-01-01

This snapshot goes beyond traditional measures of postsecondary attainment by tracking the fall 2010 entering cohort over time, and showing persistence, stop-out, and completion rates at the end of each subsequent academic year. The model tracks outcomes for both full-time and part-time starters, and takes spring and summer terms into account.…

Object Tracking Using Adaptive Covariance Descriptor and Clustering-Based Model Updating for Visual Surveillance

PubMed Central

Qin, Lei; Snoussi, Hichem; Abdallah, Fahed

2014-01-01

We propose a novel approach for tracking an arbitrary object in video sequences for visual surveillance. The first contribution of this work is an automatic feature extraction method that is able to extract compact discriminative features from a feature pool before computing the region covariance descriptor. As the feature extraction method is adaptive to a specific object of interest, we refer to the region covariance descriptor computed using the extracted features as the adaptive covariance descriptor. The second contribution is to propose a weakly supervised method for updating the object appearance model during tracking. The method performs a mean-shift clustering procedure among the tracking result samples accumulated during a period of time and selects a group of reliable samples for updating the object appearance model. As such, the object appearance model is kept up-to-date and is prevented from contamination even in case of tracking mistakes. We conducted comparing experiments on real-world video sequences, which confirmed the effectiveness of the proposed approaches. The tracking system that integrates the adaptive covariance descriptor and the clustering-based model updating method accomplished stable object tracking on challenging video sequences. PMID:24865883

Situation exploration in a persistent surveillance system with multidimensional data

NASA Astrophysics Data System (ADS)

Habibi, Mohammad S.

2013-03-01

There is an emerging need for fusing hard and soft sensor data in an efficient surveillance system to provide accurate estimation of situation awareness. These mostly abstract, multi-dimensional and multi-sensor data pose a great challenge to the user in performing analysis of multi-threaded events efficiently and cohesively. To address this concern an interactive Visual Analytics (VA) application is developed for rapid assessment and evaluation of different hypotheses based on context-sensitive ontology spawn from taxonomies describing human/human and human/vehicle/object interactions. A methodology is described here for generating relevant ontology in a Persistent Surveillance System (PSS) and demonstrates how they can be utilized in the context of PSS to track and identify group activities pertaining to potential threats. The proposed VA system allows for visual analysis of raw data as well as metadata that have spatiotemporal representation and content-based implications. Additionally in this paper, a technique for rapid search of tagged information contingent to ranking and confidence is explained for analysis of multi-dimensional data. Lastly the issue of uncertainty associated with processing and interpretation of heterogeneous data is also addressed.

Hardware accelerator design for tracking in smart camera

NASA Astrophysics Data System (ADS)

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

2011-10-01

Smart Cameras are important components in video analysis. For video analysis, smart cameras needs to detect interesting moving objects, track such objects from frame to frame, and perform analysis of object track in real time. Therefore, the use of real-time tracking is prominent in smart cameras. The software implementation of tracking algorithm on a general purpose processor (like PowerPC) could achieve low frame rate far from real-time requirements. This paper presents the SIMD approach based hardware accelerator designed for real-time tracking of objects in a scene. The system is designed and simulated using VHDL and implemented on Xilinx XUP Virtex-IIPro FPGA. Resulted frame rate is 30 frames per second for 250x200 resolution video in gray scale.

Low-Latency Line Tracking Using Event-Based Dynamic Vision Sensors

PubMed Central

Everding, Lukas; Conradt, Jörg

2018-01-01

In order to safely navigate and orient in their local surroundings autonomous systems need to rapidly extract and persistently track visual features from the environment. While there are many algorithms tackling those tasks for traditional frame-based cameras, these have to deal with the fact that conventional cameras sample their environment with a fixed frequency. Most prominently, the same features have to be found in consecutive frames and corresponding features then need to be matched using elaborate techniques as any information between the two frames is lost. We introduce a novel method to detect and track line structures in data streams of event-based silicon retinae [also known as dynamic vision sensors (DVS)]. In contrast to conventional cameras, these biologically inspired sensors generate a quasicontinuous stream of vision information analogous to the information stream created by the ganglion cells in mammal retinae. All pixels of DVS operate asynchronously without a periodic sampling rate and emit a so-called DVS address event as soon as they perceive a luminance change exceeding an adjustable threshold. We use the high temporal resolution achieved by the DVS to track features continuously through time instead of only at fixed points in time. The focus of this work lies on tracking lines in a mostly static environment which is observed by a moving camera, a typical setting in mobile robotics. Since DVS events are mostly generated at object boundaries and edges which in man-made environments often form lines they were chosen as feature to track. Our method is based on detecting planes of DVS address events in x-y-t-space and tracing these planes through time. It is robust against noise and runs in real time on a standard computer, hence it is suitable for low latency robotics. The efficacy and performance are evaluated on real-world data sets which show artificial structures in an office-building using event data for tracking and frame data for ground-truth estimation from a DAVIS240C sensor. PMID:29515386

Evidence against a speed limit in multiple-object tracking.

PubMed

Franconeri, S L; Lin, J Y; Pylyshyn, Z W; Fisher, B; Enns, J T

2008-08-01

Everyday tasks often require us to keep track of multiple objects in dynamic scenes. Past studies show that tracking becomes more difficult as objects move faster. In the present study, we show that this trade-off may not be due to increased speed itself but may, instead, be due to the increased crowding that usually accompanies increases in speed. Here, we isolate changes in speed from variations in crowding, by projecting a tracking display either onto a small area at the center of a hemispheric projection dome or onto the entire dome. Use of the larger display increased retinal image size and object speed by a factor of 4 but did not increase interobject crowding. Results showed that tracking accuracy was equally good in the large-display condition, even when the objects traveled far into the visual periphery. Accuracy was also not reduced when we tested object speeds that limited performance in the small-display condition. These results, along with a reinterpretation of past studies, suggest that we might be able to track multiple moving objects as fast as we can a single moving object, once the effect of object crowding is eliminated.

The role of temporal synchrony as a binding cue for visual persistence in early visual areas: an fMRI study.

PubMed

Wong, Yvonne J; Aldcroft, Adrian J; Large, Mary-Ellen; Culham, Jody C; Vilis, Tutis

2009-12-01

We examined the role of temporal synchrony-the simultaneous appearance of visual features-in the perceptual and neural processes underlying object persistence. When a binding cue (such as color or motion) momentarily exposes an object from a background of similar elements, viewers remain aware of the object for several seconds before it perceptually fades into the background, a phenomenon known as object persistence. We showed that persistence from temporal stimulus synchrony, like that arising from motion and color, is associated with activation in the lateral occipital (LO) area, as measured by functional magnetic resonance imaging. We also compared the distribution of occipital cortex activity related to persistence to that of iconic visual memory. Although activation related to iconic memory was largely confined to LO, activation related to object persistence was present across V1 to LO, peaking in V3 and V4, regardless of the binding cue (temporal synchrony, motion, or color). Although persistence from motion cues was not associated with higher activation in the MT+ motion complex, persistence from color cues was associated with increased activation in V4. Taken together, these results demonstrate that although persistence is a form of visual memory, it relies on neural mechanisms different from those of iconic memory. That is, persistence not only activates LO in a cue-independent manner, it also recruits visual areas that may be necessary to maintain binding between object elements.

Towards a real-time wide area motion imagery system

NASA Astrophysics Data System (ADS)

Young, R. I.; Foulkes, S. B.

2015-10-01

It is becoming increasingly important in both the defence and security domains to conduct persistent wide area surveillance (PWAS) of large populations of targets. Wide Area Motion Imagery (WAMI) is a key technique for achieving this wide area surveillance. The recent development of multi-million pixel sensors has provided sensors with wide field of view replete with sufficient resolution for detection and tracking of objects of interest to be achieved across these extended areas of interest. WAMI sensors simultaneously provide high spatial and temporal resolutions, giving extreme pixel counts over large geographical areas. The high temporal resolution is required to enable effective tracking of targets. The provision of wide area coverage with high frame rates generates data deluge issues; these are especially profound if the sensor is mounted on an airborne platform, with finite data-link bandwidth and processing power that is constrained by size, weight and power (SWAP) limitations. These issues manifest themselves either as bottlenecks in the transmission of the imagery off-board or as latency in the time taken to analyse the data due to limited computational processing power.

Brain Activation during Spatial Updating and Attentive Tracking of Moving Targets

ERIC Educational Resources Information Center

Jahn, Georg; Wendt, Julia; Lotze, Martin; Papenmeier, Frank; Huff, Markus

2012-01-01

Keeping aware of the locations of objects while one is moving requires the updating of spatial representations. As long as the objects are visible, attentional tracking is sufficient, but knowing where objects out of view went in relation to one's own body involves an updating of spatial working memory. Here, multiple object tracking was employed…

A coarse-to-fine kernel matching approach for mean-shift based visual tracking

NASA Astrophysics Data System (ADS)

Liangfu, L.; Zuren, F.; Weidong, C.; Ming, J.

2009-03-01

Mean shift is an efficient pattern match algorithm. It is widely used in visual tracking fields since it need not perform whole search in the image space. It employs gradient optimization method to reduce the time of feature matching and realize rapid object localization, and uses Bhattacharyya coefficient as the similarity measure between object template and candidate template. This thesis presents a mean shift algorithm based on coarse-to-fine search for the best kernel matching. This paper researches for object tracking with large motion area based on mean shift. To realize efficient tracking of such an object, we present a kernel matching method from coarseness to fine. If the motion areas of the object between two frames are very large and they are not overlapped in image space, then the traditional mean shift method can only obtain local optimal value by iterative computing in the old object window area, so the real tracking position cannot be obtained and the object tracking will be disabled. Our proposed algorithm can efficiently use a similarity measure function to realize the rough location of motion object, then use mean shift method to obtain the accurate local optimal value by iterative computing, which successfully realizes object tracking with large motion. Experimental results show its good performance in accuracy and speed when compared with background-weighted histogram algorithm in the literature.

Correlation and 3D-tracking of objects by pointing sensors

DOEpatents

Griesmeyer, J. Michael

2017-04-04

A method and system for tracking at least one object using a plurality of pointing sensors and a tracking system are disclosed herein. In a general embodiment, the tracking system is configured to receive a series of observation data relative to the at least one object over a time base for each of the plurality of pointing sensors. The observation data may include sensor position data, pointing vector data and observation error data. The tracking system may further determine a triangulation point using a magnitude of a shortest line connecting a line of sight value from each of the series of observation data from each of the plurality of sensors to the at least one object, and perform correlation processing on the observation data and triangulation point to determine if at least two of the plurality of sensors are tracking the same object. Observation data may also be branched, associated and pruned using new incoming observation data.

Cooperative multisensor system for real-time face detection and tracking in uncontrolled conditions

NASA Astrophysics Data System (ADS)

Marchesotti, Luca; Piva, Stefano; Turolla, Andrea; Minetti, Deborah; Regazzoni, Carlo S.

2005-03-01

The presented work describes an innovative architecture for multi-sensor distributed video surveillance applications. The aim of the system is to track moving objects in outdoor environments with a cooperative strategy exploiting two video cameras. The system also exhibits the capacity of focusing its attention on the faces of detected pedestrians collecting snapshot frames of face images, by segmenting and tracking them over time at different resolution. The system is designed to employ two video cameras in a cooperative client/server structure: the first camera monitors the entire area of interest and detects the moving objects using change detection techniques. The detected objects are tracked over time and their position is indicated on a map representing the monitored area. The objects" coordinates are sent to the server sensor in order to point its zooming optics towards the moving object. The second camera tracks the objects at high resolution. As well as the client camera, this sensor is calibrated and the position of the object detected on the image plane reference system is translated in its coordinates referred to the same area map. In the map common reference system, data fusion techniques are applied to achieve a more precise and robust estimation of the objects" track and to perform face detection and tracking. The work novelties and strength reside in the cooperative multi-sensor approach, in the high resolution long distance tracking and in the automatic collection of biometric data such as a person face clip for recognition purposes.

Persistence of F-Specific RNA Coliphages in Surface Waters from a Produce Production Region along the Central Coast of California.

PubMed

Ravva, Subbarao V; Sarreal, Chester Z

2016-01-01

F+ RNA coliphages (FRNA) are used to source-track fecal contamination and as surrogates for enteric pathogen persistence in the environment. However, the environmental persistence of FRNA is not clearly understood and necessitates the evaluation of the survival of prototype and environmental isolates of FRNA representing all four genogroups in surface waters from the central coast of California. Water temperature played a significant role in persistence-all prototype and environmental strains survived significantly longer at 10 °C compared to 25 °C. Similarly, the availability of host bacterium was found to be critical in FRNA survival. In the absence of E. coli F(amp), all prototypes of FRNA disappeared rapidly with a D-value (days for one log reduction) of <1.2 d from water samples incubated at 25 °C; the longest surviving prototype was SP. However, in the presence of the host, the order of persistence at 25 °C was QB>MS2>SP>GA and at 10 °C it was QB = MS2>GA>SP. Significant differences in survival were observed between prototypes and environmental isolates of FRNA. While most environmental isolates disappeared rapidly at 25 °C and in the absence of the host, members of genogroups GIII and GI persisted longer with the host compared to members of GII and GIV. Consequentially, FRNA based source tracking methods can be used to detect phages from recent fecal contamination along with those that persist longer in the environment as a result of cooler temperatures and increased host presence.

Multi-Complementary Model for Long-Term Tracking

PubMed Central

Zhang, Deng; Zhang, Junchang; Xia, Chenyang

2018-01-01

In recent years, video target tracking algorithms have been widely used. However, many tracking algorithms do not achieve satisfactory performance, especially when dealing with problems such as object occlusions, background clutters, motion blur, low illumination color images, and sudden illumination changes in real scenes. In this paper, we incorporate an object model based on contour information into a Staple tracker that combines the correlation filter model and color model to greatly improve the tracking robustness. Since each model is responsible for tracking specific features, the three complementary models combine for more robust tracking. In addition, we propose an efficient object detection model with contour and color histogram features, which has good detection performance and better detection efficiency compared to the traditional target detection algorithm. Finally, we optimize the traditional scale calculation, which greatly improves the tracking execution speed. We evaluate our tracker on the Object Tracking Benchmarks 2013 (OTB-13) and Object Tracking Benchmarks 2015 (OTB-15) benchmark datasets. With the OTB-13 benchmark datasets, our algorithm is improved by 4.8%, 9.6%, and 10.9% on the success plots of OPE, TRE and SRE, respectively, in contrast to another classic LCT (Long-term Correlation Tracking) algorithm. On the OTB-15 benchmark datasets, when compared with the LCT algorithm, our algorithm achieves 10.4%, 12.5%, and 16.1% improvement on the success plots of OPE, TRE, and SRE, respectively. At the same time, it needs to be emphasized that, due to the high computational efficiency of the color model and the object detection model using efficient data structures, and the speed advantage of the correlation filters, our tracking algorithm could still achieve good tracking speed. PMID:29425170

Acoustic signature recognition technique for Human-Object Interactions (HOI) in persistent surveillance systems

NASA Astrophysics Data System (ADS)

Alkilani, Amjad; Shirkhodaie, Amir

2013-05-01

Handling, manipulation, and placement of objects, hereon called Human-Object Interaction (HOI), in the environment generate sounds. Such sounds are readily identifiable by the human hearing. However, in the presence of background environment noises, recognition of minute HOI sounds is challenging, though vital for improvement of multi-modality sensor data fusion in Persistent Surveillance Systems (PSS). Identification of HOI sound signatures can be used as precursors to detection of pertinent threats that otherwise other sensor modalities may miss to detect. In this paper, we present a robust method for detection and classification of HOI events via clustering of extracted features from training of HOI acoustic sound waves. In this approach, salient sound events are preliminary identified and segmented from background via a sound energy tracking method. Upon this segmentation, frequency spectral pattern of each sound event is modeled and its features are extracted to form a feature vector for training. To reduce dimensionality of training feature space, a Principal Component Analysis (PCA) technique is employed to expedite fast classification of test feature vectors, a kd-tree and Random Forest classifiers are trained for rapid classification of training sound waves. Each classifiers employs different similarity distance matching technique for classification. Performance evaluations of classifiers are compared for classification of a batch of training HOI acoustic signatures. Furthermore, to facilitate semantic annotation of acoustic sound events, a scheme based on Transducer Mockup Language (TML) is proposed. The results demonstrate the proposed approach is both reliable and effective, and can be extended to future PSS applications.

A resource oriented webs service for environmental modeling

NASA Astrophysics Data System (ADS)

Ferencik, Ioan

2013-04-01

Environmental modeling is a largely adopted practice in the study of natural phenomena. Environmental models can be difficult to build and use and thus sharing them within the community is an important aspect. The most common approach to share a model is to expose it as a web service. In practice the interaction with this web service is cumbersome due to lack of standardized contract and the complexity of the model being exposed. In this work we investigate the use of a resource oriented approach in exposing environmental models as web services. We view a model as a layered resource build atop the object concept from Object Oriented Programming, augmented with persistence capabilities provided by an embedded object database to keep track of its state and implementing the four basic principles of resource oriented architectures: addressability, statelessness, representation and uniform interface. For implementation we use exclusively open source software: Django framework, dyBase object oriented database and Python programming language. We developed a generic framework of resources structured into a hierarchy of types and consequently extended this typology with recurses specific to the domain of environmental modeling. To test our web service we used cURL, a robust command-line based web client.

Multiple objects tracking with HOGs matching in circular windows

NASA Astrophysics Data System (ADS)

Miramontes-Jaramillo, Daniel; Kober, Vitaly; Díaz-Ramírez, Víctor H.

2014-09-01

In recent years tracking applications with development of new technologies like smart TVs, Kinect, Google Glass and Oculus Rift become very important. When tracking uses a matching algorithm, a good prediction algorithm is required to reduce the search area for each object to be tracked as well as processing time. In this work, we analyze the performance of different tracking algorithms based on prediction and matching for a real-time tracking multiple objects. The used matching algorithm utilizes histograms of oriented gradients. It carries out matching in circular windows, and possesses rotation invariance and tolerance to viewpoint and scale changes. The proposed algorithm is implemented in a personal computer with GPU, and its performance is analyzed in terms of processing time in real scenarios. Such implementation takes advantage of current technologies and helps to process video sequences in real-time for tracking several objects at the same time.

Multiple Object Tracking Reveals Object-Based Grouping Interference in Children with ASD

ERIC Educational Resources Information Center

Van der Hallen, Ruth; Evers, Kris; de-Wit, Lee; Steyaert, Jean; Noens, Ilse; Wagemans, Johan

2018-01-01

The multiple object tracking (MOT) paradigm has proven its value in targeting a number of aspects of visual cognition. This study used MOT to investigate the effect of object-based grouping, both in children with and without autism spectrum disorder (ASD). A modified MOT task was administered to both groups, who had to track and distinguish four…

Real-Time Radar-Based Tracking and State Estimation of Multiple Non-Conformant Aircraft

NASA Technical Reports Server (NTRS)

Cook, Brandon; Arnett, Timothy; Macmann, Owen; Kumar, Manish

2017-01-01

In this study, a novel solution for automated tracking of multiple unknown aircraft is proposed. Many current methods use transponders to self-report state information and augment track identification. While conformant aircraft typically report transponder information to alert surrounding aircraft of its state, vehicles may exist in the airspace that are non-compliant and need to be accurately tracked using alternative methods. In this study, a multi-agent tracking solution is presented that solely utilizes primary surveillance radar data to estimate aircraft state information. Main research challenges include state estimation, track management, data association, and establishing persistent track validity. In an effort to realize these challenges, techniques such as Maximum a Posteriori estimation, Kalman filtering, degree of membership data association, and Nearest Neighbor Spanning Tree clustering are implemented for this application.

Tracking Financial Aid and Persistence of Women, Minority, and Needy Students in Science, Engineering, and Mathematics.

ERIC Educational Resources Information Center

Fenske, Robert H.; Porter, John D.; DuBrock, Caryl P.

2000-01-01

This longitudinal study followed four consecutive freshmen cohorts at a large urban public university. Found science, engineering, and mathematics (SEM) students persisted and graduated at higher rates than non-SEM majors. Gift aid for SEM majors was more likely to be merit-based than need-based. Women, but not underrepresented minorities or needy…

Persistence of New Students Who Entered College of the Desert, Fall 1991 and Fall 1992.

ERIC Educational Resources Information Center

Breindel, Matthew D.

A study was undertaken at California's College of the Desert to determine the persistence rates of new students who entered the college in fall 1991 and fall 1992. Course enrollment was tracked for these students through fall 1996, with outcomes examined by student gender, ethnicity, and age; student enrollment in credit or non-credit courses;…

The Effect of Types of Financial Aid on Student Persistence towards Graduation. AIR 1995 Annual Forum Paper.

ERIC Educational Resources Information Center

Murdock, Tullise; And Others

The relationship between student persistence and types of financial aid at a Jesuit comprehensive university was studied. Three freshmen cohorts (134 for 1989, 171 for 1990, and 131 for 1991) of 436 students were tracked through fall 1994. Attention was focused on nine financial aid variables, five additional noncategorical and six categorical…

Students Left Behind: Measuring 10th to 12th Grade Student Persistence Rates in Texas High Schools

PubMed Central

Domina, Thurston; Ghosh-Dastidar, Bonnie; Tienda, Marta

2012-01-01

The No Child Left Behind Act requires states to publish high school graduation rates for public schools and the U.S. Department of Education is currently considering a mandate to standardize high school graduation rate reporting. However, no consensus exists among researchers or policy-makers about how to measure high school graduation rates. In this paper, we use longitudinal data tracking a cohort of students at 82 Texas public high schools to assess the accuracy and precision of three widely-used high school graduation rate measures: Texas’s official graduation rates, and two competing estimates based on publicly available enrollment data from the Common Core of Data. Our analyses show that these widely-used approaches yield inaccurate and highly imprecise estimates of high school graduation and persistence rates. We propose several guidelines for using existing graduation and persistence rate data and argue that a national effort to track students as they progress through high school is essential to reconcile conflicting estimates. PMID:23077375

Students Left Behind: Measuring 10(th) to 12(th) Grade Student Persistence Rates in Texas High Schools.

PubMed

Domina, Thurston; Ghosh-Dastidar, Bonnie; Tienda, Marta

2010-06-01

The No Child Left Behind Act requires states to publish high school graduation rates for public schools and the U.S. Department of Education is currently considering a mandate to standardize high school graduation rate reporting. However, no consensus exists among researchers or policy-makers about how to measure high school graduation rates. In this paper, we use longitudinal data tracking a cohort of students at 82 Texas public high schools to assess the accuracy and precision of three widely-used high school graduation rate measures: Texas's official graduation rates, and two competing estimates based on publicly available enrollment data from the Common Core of Data. Our analyses show that these widely-used approaches yield inaccurate and highly imprecise estimates of high school graduation and persistence rates. We propose several guidelines for using existing graduation and persistence rate data and argue that a national effort to track students as they progress through high school is essential to reconcile conflicting estimates.

Nanohybrids with Magnetic and Persistent Luminescence Properties for Cell Labeling, Tracking, In Vivo Real-Time Imaging, and Magnetic Vectorization.

PubMed

Teston, Eliott; Maldiney, Thomas; Marangon, Iris; Volatron, Jeanne; Lalatonne, Yoann; Motte, Laurence; Boisson-Vidal, Catherine; Autret, Gwennhael; Clément, Olivier; Scherman, Daniel; Gazeau, Florence; Richard, Cyrille

2018-04-01

Once injected into a living organism, cells diffuse or migrate around the initial injection point and become impossible to be visualized and tracked in vivo. The present work concerns the development of a new technique for therapeutic cell labeling and subsequent in vivo visualization and magnetic retention. It is hypothesized and subsequently demonstrated that nanohybrids made of persistent luminescence nanoparticles and ultrasmall superparamagnetic iron oxide nanoparticles incorporated into a silica matrix can be used as an effective nanoplatform to label therapeutic cells in a nontoxic way in order to dynamically track them in real-time in vitro and in living mice. As a proof-of-concept, it is shown that once injected, these labeled cells can be visualized and attracted in vivo using a magnet. This first step suggests that these nanohybrids represent efficient multifunctional nanoprobes for further imaging guided cell therapies development. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Detection and Tracking of Dynamic Objects by Using a Multirobot System: Application to Critical Infrastructures Surveillance

PubMed Central

Rodríguez-Canosa, Gonzalo; Giner, Jaime del Cerro; Barrientos, Antonio

2014-01-01

The detection and tracking of mobile objects (DATMO) is progressively gaining importance for security and surveillance applications. This article proposes a set of new algorithms and procedures for detecting and tracking mobile objects by robots that work collaboratively as part of a multirobot system. These surveillance algorithms are conceived of to work with data provided by long distance range sensors and are intended for highly reliable object detection in wide outdoor environments. Contrary to most common approaches, in which detection and tracking are done by an integrated procedure, the approach proposed here relies on a modular structure, in which detection and tracking are carried out independently, and the latter might accept input data from different detection algorithms. Two movement detection algorithms have been developed for the detection of dynamic objects by using both static and/or mobile robots. The solution to the overall problem is based on the use of a Kalman filter to predict the next state of each tracked object. Additionally, new tracking algorithms capable of combining dynamic objects lists coming from either one or various sources complete the solution. The complementary performance of the separated modular structure for detection and identification is evaluated and, finally, a selection of test examples discussed. PMID:24526305

All eyes on relevance: strategic allocation of attention as a result of feature-based task demands in multiple object tracking.

PubMed

Brockhoff, Alisa; Huff, Markus

2016-10-01

Multiple object tracking (MOT) plays a fundamental role in processing and interpreting dynamic environments. Regarding the type of information utilized by the observer, recent studies reported evidence for the use of object features in an automatic, low- level manner. By introducing a novel paradigm that allowed us to combine tracking with a noninterfering top-down task, we tested whether a voluntary component can regulate the deployment of attention to task-relevant features in a selective manner. In four experiments we found conclusive evidence for a task-driven selection mechanism that guides attention during tracking: The observers were able to ignore or prioritize distinct objects. They marked the distinct (cued) object (target/distractor) more or less often than other objects of the same type (targets /distractors)-but only when they had received an identification task that required them to actively process object features (cues) during tracking. These effects are discussed with regard to existing theoretical approaches to attentive tracking, gaze-cue usability as well as attentional readiness, a term that originally stems from research on attention capture and visual search. Our findings indicate that existing theories of MOT need to be adjusted to allow for flexible top-down, voluntary processing during tracking.

Nonstationary EO/IR Clutter Suppression and Dim Object Tracking

NASA Astrophysics Data System (ADS)

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

2010-09-01

We develop and evaluate the performance of advanced algorithms which provide significantly improved capabilities for automated detection and tracking of ballistic and flying dim objects in the presence of highly structured intense clutter. Applications include ballistic missile early warning, midcourse tracking, trajectory prediction, and resident space object detection and tracking. The set of algorithms include, in particular, adaptive spatiotemporal clutter estimation-suppression and nonlinear filtering-based multiple-object track-before-detect. These algorithms are suitable for integration into geostationary, highly elliptical, or low earth orbit scanning or staring sensor suites, and are based on data-driven processing that adapts to real-world clutter backgrounds, including celestial, earth limb, or terrestrial clutter. In many scenarios of interest, e.g., for highly elliptic and, especially, low earth orbits, the resulting clutter is highly nonstationary, providing a significant challenge for clutter suppression to or below sensor noise levels, which is essential for dim object detection and tracking. We demonstrate the success of the developed algorithms using semi-synthetic and real data. In particular, our algorithms are shown to be capable of detecting and tracking point objects with signal-to-clutter levels down to 1/1000 and signal-to-noise levels down to 1/4.

Persistent maritime surveillance using multi-sensor feature association and classification

NASA Astrophysics Data System (ADS)

van den Broek, Sebastiaan P.; Schwering, Piet B. W.; Liem, Kwan D.; Schleijpen, Ric

2012-06-01

In maritime operational scenarios, such as smuggling, piracy, or terrorist threats, it is not only relevant who or what an observed object is, but also where it is now and in the past in relation to other (geographical) objects. In situation and impact assessment, this information is used to determine whether an object is a threat. Single platform (ship, harbor) or single sensor information will not provide all this information. The work presented in this paper focuses on the sensor and object levels that provide a description of currently observed objects to situation assessment. For use of information of objects at higher information levels, it is necessary to have not only a good description of observed objects at this moment, but also from its past. Therefore, currently observed objects have to be linked to previous occurrences. Kinematic features, as used in tracking, are of limited use, as uncertainties over longer time intervals are so large that no unique associations can be made. Features extracted from different sensors (e.g., ESM, EO/IR) can be used for both association and classification. Features and classifications are used to associate current objects to previous object descriptions, allowing objects to be described better, and provide position history. In this paper a description of a high level architecture in which such a multi-sensor association is used is described. Results of an assessment of the usability of several features from ESM (from spectrum), EO and IR (shape, contour, keypoints) data for association and classification are shown.

A visual tracking method based on deep learning without online model updating

NASA Astrophysics Data System (ADS)

Tang, Cong; Wang, Yicheng; Feng, Yunsong; Zheng, Chao; Jin, Wei

2018-02-01

The paper proposes a visual tracking method based on deep learning without online model updating. In consideration of the advantages of deep learning in feature representation, deep model SSD (Single Shot Multibox Detector) is used as the object extractor in the tracking model. Simultaneously, the color histogram feature and HOG (Histogram of Oriented Gradient) feature are combined to select the tracking object. In the process of tracking, multi-scale object searching map is built to improve the detection performance of deep detection model and the tracking efficiency. In the experiment of eight respective tracking video sequences in the baseline dataset, compared with six state-of-the-art methods, the method in the paper has better robustness in the tracking challenging factors, such as deformation, scale variation, rotation variation, illumination variation, and background clutters, moreover, its general performance is better than other six tracking methods.

Feature-based interference from unattended visual field during attentional tracking in younger and older adults.

PubMed

Störmer, Viola S; Li, Shu-Chen; Heekeren, Hauke R; Lindenberger, Ulman

2011-02-01

The ability to attend to multiple objects that move in the visual field is important for many aspects of daily functioning. The attentional capacity for such dynamic tracking, however, is highly limited and undergoes age-related decline. Several aspects of the tracking process can influence performance. Here, we investigated effects of feature-based interference from distractor objects that appear in unattended regions of the visual field with a hemifield-tracking task. Younger and older participants performed an attentional tracking task in one hemifield while distractor objects were concurrently presented in the unattended hemifield. Feature similarity between objects in the attended and unattended hemifields as well as motion speed and the number of to-be-tracked objects were parametrically manipulated. The results show that increasing feature overlap leads to greater interference from the unattended visual field. This effect of feature-based interference was only present in the slow speed condition, indicating that the interference is mainly modulated by perceptual demands. High-performing older adults showed a similar interference effect as younger adults, whereas low-performing adults showed poor tracking performance overall.

Robust Pedestrian Tracking and Recognition from FLIR Video: A Unified Approach via Sparse Coding

PubMed Central

Li, Xin; Guo, Rui; Chen, Chao

2014-01-01

Sparse coding is an emerging method that has been successfully applied to both robust object tracking and recognition in the vision literature. In this paper, we propose to explore a sparse coding-based approach toward joint object tracking-and-recognition and explore its potential in the analysis of forward-looking infrared (FLIR) video to support nighttime machine vision systems. A key technical contribution of this work is to unify existing sparse coding-based approaches toward tracking and recognition under the same framework, so that they can benefit from each other in a closed-loop. On the one hand, tracking the same object through temporal frames allows us to achieve improved recognition performance through dynamical updating of template/dictionary and combining multiple recognition results; on the other hand, the recognition of individual objects facilitates the tracking of multiple objects (i.e., walking pedestrians), especially in the presence of occlusion within a crowded environment. We report experimental results on both the CASIAPedestrian Database and our own collected FLIR video database to demonstrate the effectiveness of the proposed joint tracking-and-recognition approach. PMID:24961216

The research on the mean shift algorithm for target tracking

NASA Astrophysics Data System (ADS)

CAO, Honghong

2017-06-01

The traditional mean shift algorithm for target tracking is effective and high real-time, but there still are some shortcomings. The traditional mean shift algorithm is easy to fall into local optimum in the tracking process, the effectiveness of the method is weak when the object is moving fast. And the size of the tracking window never changes, the method will fail when the size of the moving object changes, as a result, we come up with a new method. We use particle swarm optimization algorithm to optimize the mean shift algorithm for target tracking, Meanwhile, SIFT (scale-invariant feature transform) and affine transformation make the size of tracking window adaptive. At last, we evaluate the method by comparing experiments. Experimental result indicates that the proposed method can effectively track the object and the size of the tracking window changes.

Ego-Motion and Tracking for Continuous Object Learning: A Brief Survey

DTIC Science & Technology

2017-09-01

ARL-TR-8167• SEP 2017 US Army Research Laboratory Ego-motion and Tracking for ContinuousObject Learning: A Brief Survey by Jason Owens and Philip...SEP 2017 US Army Research Laboratory Ego-motion and Tracking for ContinuousObject Learning: A Brief Survey by Jason Owens and Philip OsteenVehicle...

Locator-Checker-Scaler Object Tracking Using Spatially Ordered and Weighted Patch Descriptor.

PubMed

Kim, Han-Ul; Kim, Chang-Su

2017-08-01

In this paper, we propose a simple yet effective object descriptor and a novel tracking algorithm to track a target object accurately. For the object description, we divide the bounding box of a target object into multiple patches and describe them with color and gradient histograms. Then, we determine the foreground weight of each patch to alleviate the impacts of background information in the bounding box. To this end, we perform random walk with restart (RWR) simulation. We then concatenate the weighted patch descriptors to yield the spatially ordered and weighted patch (SOWP) descriptor. For the object tracking, we incorporate the proposed SOWP descriptor into a novel tracking algorithm, which has three components: locator, checker, and scaler (LCS). The locator and the scaler estimate the center location and the size of a target, respectively. The checker determines whether it is safe to adjust the target scale in a current frame. These three components cooperate with one another to achieve robust tracking. Experimental results demonstrate that the proposed LCS tracker achieves excellent performance on recent benchmarks.

3D noise-resistant segmentation and tracking of unknown and occluded objects using integral imaging

NASA Astrophysics Data System (ADS)

Aloni, Doron; Jung, Jae-Hyun; Yitzhaky, Yitzhak

2017-10-01

Three dimensional (3D) object segmentation and tracking can be useful in various computer vision applications, such as: object surveillance for security uses, robot navigation, etc. We present a method for 3D multiple-object tracking using computational integral imaging, based on accurate 3D object segmentation. The method does not employ object detection by motion analysis in a video as conventionally performed (such as background subtraction or block matching). This means that the movement properties do not significantly affect the detection quality. The object detection is performed by analyzing static 3D image data obtained through computational integral imaging With regard to previous works that used integral imaging data in such a scenario, the proposed method performs the 3D tracking of objects without prior information about the objects in the scene, and it is found efficient under severe noise conditions.

Obstacle penetrating dynamic radar imaging system

DOEpatents

Romero, Carlos E [Livermore, CA; Zumstein, James E [Livermore, CA; Chang, John T [Danville, CA; Leach, Jr Richard R. [Castro Valley, CA

2006-12-12

An obstacle penetrating dynamic radar imaging system for the detection, tracking, and imaging of an individual, animal, or object comprising a multiplicity of low power ultra wideband radar units that produce a set of return radar signals from the individual, animal, or object, and a processing system for said set of return radar signals for detection, tracking, and imaging of the individual, animal, or object. The system provides a radar video system for detecting and tracking an individual, animal, or object by producing a set of return radar signals from the individual, animal, or object with a multiplicity of low power ultra wideband radar units, and processing said set of return radar signals for detecting and tracking of the individual, animal, or object.

Attention Modulates Spatial Precision in Multiple-Object Tracking.

PubMed

Srivastava, Nisheeth; Vul, Ed

2016-01-01

We present a computational model of multiple-object tracking that makes trial-level predictions about the allocation of visual attention and the effect of this allocation on observers' ability to track multiple objects simultaneously. This model follows the intuition that increased attention to a location increases the spatial resolution of its internal representation. Using a combination of empirical and computational experiments, we demonstrate the existence of a tight coupling between cognitive and perceptual resources in this task: Low-level tracking of objects generates bottom-up predictions of error likelihood, and high-level attention allocation selectively reduces error probabilities in attended locations while increasing it at non-attended locations. Whereas earlier models of multiple-object tracking have predicted the big picture relationship between stimulus complexity and response accuracy, our approach makes accurate predictions of both the macro-scale effect of target number and velocity on tracking difficulty and micro-scale variations in difficulty across individual trials and targets arising from the idiosyncratic within-trial interactions of targets and distractors. Copyright © 2016 Cognitive Science Society, Inc.

An Object-Oriented Database Interface for Ada

DTIC Science & Technology

1993-12-01

single object model, a unique extension for each ODM system may be required. The existence of Classic Ada with persistence provides evidence that a...prototypes and also through a commercial product known as Classic Ada with persistence. Classic Ada, a product marketed by Software Productivity Solutions...legal Ada constructs. Classic Ada with persistence provides an extra keyword, persistent, so that a user-defined class can be declared persistent. The

Enhanced online convolutional neural networks for object tracking

NASA Astrophysics Data System (ADS)

Zhang, Dengzhuo; Gao, Yun; Zhou, Hao; Li, Tianwen

2018-04-01

In recent several years, object tracking based on convolution neural network has gained more and more attention. The initialization and update of convolution filters can directly affect the precision of object tracking effective. In this paper, a novel object tracking via an enhanced online convolution neural network without offline training is proposed, which initializes the convolution filters by a k-means++ algorithm and updates the filters by an error back-propagation. The comparative experiments of 7 trackers on 15 challenging sequences showed that our tracker can perform better than other trackers in terms of AUC and precision.

Efficient Spatiotemporal Clutter Rejection and Nonlinear Filtering-based Dim Resolved and Unresolved Object Tracking Algorithms

NASA Astrophysics Data System (ADS)

Tartakovsky, A.; Tong, M.; Brown, A. P.; Agh, C.

2013-09-01

We develop efficient spatiotemporal image processing algorithms for rejection of non-stationary clutter and tracking of multiple dim objects using non-linear track-before-detect methods. For clutter suppression, we include an innovative image alignment (registration) algorithm. The images are assumed to contain elements of the same scene, but taken at different angles, from different locations, and at different times, with substantial clutter non-stationarity. These challenges are typical for space-based and surface-based IR/EO moving sensors, e.g., highly elliptical orbit or low earth orbit scenarios. The algorithm assumes that the images are related via a planar homography, also known as the projective transformation. The parameters are estimated in an iterative manner, at each step adjusting the parameter vector so as to achieve improved alignment of the images. Operating in the parameter space rather than in the coordinate space is a new idea, which makes the algorithm more robust with respect to noise as well as to large inter-frame disturbances, while operating at real-time rates. For dim object tracking, we include new advancements to a particle non-linear filtering-based track-before-detect (TrbD) algorithm. The new TrbD algorithm includes both real-time full image search for resolved objects not yet in track and joint super-resolution and tracking of individual objects in closely spaced object (CSO) clusters. The real-time full image search provides near-optimal detection and tracking of multiple extremely dim, maneuvering objects/clusters. The super-resolution and tracking CSO TrbD algorithm provides efficient near-optimal estimation of the number of unresolved objects in a CSO cluster, as well as the locations, velocities, accelerations, and intensities of the individual objects. We demonstrate that the algorithm is able to accurately estimate the number of CSO objects and their locations when the initial uncertainty on the number of objects is large. We demonstrate performance of the TrbD algorithm both for satellite-based and surface-based EO/IR surveillance scenarios.

Juggling Toddlers, Teens, and Tenure: The Personal and Professional Realities of Women on the Tenure Track with Children

ERIC Educational Resources Information Center

Sipes, Baker; Lynn, Jennifer

2010-01-01

The purpose of this study was to understand the personal and professional experiences of women faculty on the tenure track with children. Despite more than 30 years of conversation about gender equity since the passage of Title IX as part of the Education Amendments of 1972, an inverse relationship persists between the prestige of an academic rank…

Adaptive particle filter for robust visual tracking

NASA Astrophysics Data System (ADS)

Dai, Jianghua; Yu, Shengsheng; Sun, Weiping; Chen, Xiaoping; Xiang, Jinhai

2009-10-01

Object tracking plays a key role in the field of computer vision. Particle filter has been widely used for visual tracking under nonlinear and/or non-Gaussian circumstances. In particle filter, the state transition model for predicting the next location of tracked object assumes the object motion is invariable, which cannot well approximate the varying dynamics of the motion changes. In addition, the state estimate calculated by the mean of all the weighted particles is coarse or inaccurate due to various noise disturbances. Both these two factors may degrade tracking performance greatly. In this work, an adaptive particle filter (APF) with a velocity-updating based transition model (VTM) and an adaptive state estimate approach (ASEA) is proposed to improve object tracking. In APF, the motion velocity embedded into the state transition model is updated continuously by a recursive equation, and the state estimate is obtained adaptively according to the state posterior distribution. The experiment results show that the APF can increase the tracking accuracy and efficiency in complex environments.

Memory-Based Multiagent Coevolution Modeling for Robust Moving Object Tracking

PubMed Central

Wang, Yanjiang; Qi, Yujuan; Li, Yongping

2013-01-01

The three-stage human brain memory model is incorporated into a multiagent coevolutionary process for finding the best match of the appearance of an object, and a memory-based multiagent coevolution algorithm for robust tracking the moving objects is presented in this paper. Each agent can remember, retrieve, or forget the appearance of the object through its own memory system by its own experience. A number of such memory-based agents are randomly distributed nearby the located object region and then mapped onto a 2D lattice-like environment for predicting the new location of the object by their coevolutionary behaviors, such as competition, recombination, and migration. Experimental results show that the proposed method can deal with large appearance changes and heavy occlusions when tracking a moving object. It can locate the correct object after the appearance changed or the occlusion recovered and outperforms the traditional particle filter-based tracking methods. PMID:23843739

Memory-based multiagent coevolution modeling for robust moving object tracking.

PubMed

Wang, Yanjiang; Qi, Yujuan; Li, Yongping

2013-01-01

The three-stage human brain memory model is incorporated into a multiagent coevolutionary process for finding the best match of the appearance of an object, and a memory-based multiagent coevolution algorithm for robust tracking the moving objects is presented in this paper. Each agent can remember, retrieve, or forget the appearance of the object through its own memory system by its own experience. A number of such memory-based agents are randomly distributed nearby the located object region and then mapped onto a 2D lattice-like environment for predicting the new location of the object by their coevolutionary behaviors, such as competition, recombination, and migration. Experimental results show that the proposed method can deal with large appearance changes and heavy occlusions when tracking a moving object. It can locate the correct object after the appearance changed or the occlusion recovered and outperforms the traditional particle filter-based tracking methods.

An experimental comparison of online object-tracking algorithms

NASA Astrophysics Data System (ADS)

Wang, Qing; Chen, Feng; Xu, Wenli; Yang, Ming-Hsuan

2011-09-01

This paper reviews and evaluates several state-of-the-art online object tracking algorithms. Notwithstanding decades of efforts, object tracking remains a challenging problem due to factors such as illumination, pose, scale, deformation, motion blur, noise, and occlusion. To account for appearance change, most recent tracking algorithms focus on robust object representations and effective state prediction. In this paper, we analyze the components of each tracking method and identify their key roles in dealing with specific challenges, thereby shedding light on how to choose and design algorithms for different situations. We compare state-of-the-art online tracking methods including the IVT,1 VRT,2 FragT,3 BoostT,4 SemiT,5 BeSemiT,6 L1T,7 MILT,8 VTD9 and TLD10 algorithms on numerous challenging sequences, and evaluate them with different performance metrics. The qualitative and quantitative comparative results demonstrate the strength and weakness of these algorithms.

Lagrangian 3D tracking of fluorescent microscopic objects in motion

NASA Astrophysics Data System (ADS)

Darnige, T.; Figueroa-Morales, N.; Bohec, P.; Lindner, A.; Clément, E.

2017-05-01

We describe the development of a tracking device, mounted on an epi-fluorescent inverted microscope, suited to obtain time resolved 3D Lagrangian tracks of fluorescent passive or active micro-objects in microfluidic devices. The system is based on real-time image processing, determining the displacement of a x, y mechanical stage to keep the chosen object at a fixed position in the observation frame. The z displacement is based on the refocusing of the fluorescent object determining the displacement of a piezo mover keeping the moving object in focus. Track coordinates of the object with respect to the microfluidic device as well as images of the object are obtained at a frequency of several tenths of Hertz. This device is particularly well adapted to obtain trajectories of motile micro-organisms in microfluidic devices with or without flow.

Lagrangian 3D tracking of fluorescent microscopic objects in motion.

PubMed

Darnige, T; Figueroa-Morales, N; Bohec, P; Lindner, A; Clément, E

2017-05-01

We describe the development of a tracking device, mounted on an epi-fluorescent inverted microscope, suited to obtain time resolved 3D Lagrangian tracks of fluorescent passive or active micro-objects in microfluidic devices. The system is based on real-time image processing, determining the displacement of a x, y mechanical stage to keep the chosen object at a fixed position in the observation frame. The z displacement is based on the refocusing of the fluorescent object determining the displacement of a piezo mover keeping the moving object in focus. Track coordinates of the object with respect to the microfluidic device as well as images of the object are obtained at a frequency of several tenths of Hertz. This device is particularly well adapted to obtain trajectories of motile micro-organisms in microfluidic devices with or without flow.

Emergency Department Allies: a Web-based multihospital pediatric asthma tracking system.

PubMed

Kelly, Kevin J; Walsh-Kelly, Christine M; Christenson, Peter; Rogalinski, Steven; Gorelick, Marc H; Barthell, Edward N; Grabowski, Laura

2006-04-01

To describe the development of a Web-based multihospital pediatric asthma tracking system and present results from the initial 18-month implementation of patient tracking experience. The Emergency Department (ED) Allies tracking system is a secure, password-protected data repository. Use-case methodology served as the foundation for technical development, testing, and implementation. Seventy-seven data elements addressing sociodemographics, wheezing history, quality of life, triggers, and ED managment were included for each subject visit. The ED Allies partners comprised 1 academic pediatric ED and 5 community EDs. Subjects with a physician diagnosis of asthma who presented to the ED for acute respiratory complaints composed the asthma group; subjects lacking a physician diagnosis of asthma but presenting with wheezing composed the wheezing group. The tracking-system development and implementation process included identification of data elements, system database and use case development, and delineation of screen features, system users, reporting functions, and help screens. For the asthma group, 2005 subjects with physician-diagnosed asthma were enrolled between July 15, 2002 and January 14, 2004. These subjects accounted for 2978 visits; 10.4% had > or = 3 visits. Persistent asthma was noted in 68% of the subjects. During the same time period, 1297 wheezing subjects with a total of 1628 ED visits (wheezing group) were entered into the tracking system. After enrollment, 57% of the subjects with > or = 1 subsequent ED visits received a physician diagnosis of asthma. Our sophisticated tracking system facilitated data collection and identified key intervention opportunities for a diverse ED wheezing population. A significant asthma burden was identified with significant rates of hospitalization, acute care visits and persistent asthma in 68% of subjects. The surveillance component provided important insights into health care issues of both asthmatic subjects and wheezing subjects, many of whom subsequently were diagnosed with asthma.

The role of "rescue saccades" in tracking objects through occlusions.

PubMed

Zelinsky, Gregory J; Todor, Andrei

2010-12-29

We hypothesize that our ability to track objects through occlusions is mediated by timely assistance from gaze in the form of "rescue saccades"-eye movements to tracked objects that are in danger of being lost due to impending occlusion. Observers tracked 2-4 target sharks (out of 9) for 20 s as they swam through a rendered 3D underwater scene. Targets were either allowed to enter into occlusions (occlusion trials) or not (no occlusion trials). Tracking accuracy with 2-3 targets was ≥ 92% regardless of target occlusion but dropped to 74% on occlusion trials with four targets (no occlusion trials remained accurate; 83%). This pattern was mirrored in the frequency of rescue saccades. Rescue saccades accompanied approximatlely 50% of the Track 2-3 target occlusions, but only 34% of the Track 4 occlusions. Their frequency also decreased with increasing distance between a target and the nearest other object, suggesting that it is the potential for target confusion that summons a rescue saccade, not occlusion itself. These findings provide evidence for a tracking system that monitors for events that might cause track loss (e.g., occlusions) and requests help from the oculomotor system to resolve these momentary crises. As the number of crises increase with the number of targets, some requests for help go unsatisfied, resulting in degraded tracking.

Multiple Objects Fusion Tracker Using a Matching Network for Adaptively Represented Instance Pairs

PubMed Central

Oh, Sang-Il; Kang, Hang-Bong

2017-01-01

Multiple-object tracking is affected by various sources of distortion, such as occlusion, illumination variations and motion changes. Overcoming these distortions by tracking on RGB frames, such as shifting, has limitations because of material distortions caused by RGB frames. To overcome these distortions, we propose a multiple-object fusion tracker (MOFT), which uses a combination of 3D point clouds and corresponding RGB frames. The MOFT uses a matching function initialized on large-scale external sequences to determine which candidates in the current frame match with the target object in the previous frame. After conducting tracking on a few frames, the initialized matching function is fine-tuned according to the appearance models of target objects. The fine-tuning process of the matching function is constructed as a structured form with diverse matching function branches. In general multiple object tracking situations, scale variations for a scene occur depending on the distance between the target objects and the sensors. If the target objects in various scales are equally represented with the same strategy, information losses will occur for any representation of the target objects. In this paper, the output map of the convolutional layer obtained from a pre-trained convolutional neural network is used to adaptively represent instances without information loss. In addition, MOFT fuses the tracking results obtained from each modality at the decision level to compensate the tracking failures of each modality using basic belief assignment, rather than fusing modalities by selectively using the features of each modality. Experimental results indicate that the proposed tracker provides state-of-the-art performance considering multiple objects tracking (MOT) and KITTIbenchmarks. PMID:28420194

Fast object reconstruction in block-based compressive low-light-level imaging

NASA Astrophysics Data System (ADS)

Ke, Jun; Sui, Dong; Wei, Ping

2014-11-01

In this paper we propose a simply yet effective and efficient method for long-term object tracking. Different from traditional visual tracking method which mainly depends on frame-to-frame correspondence, we combine high-level semantic information with low-level correspondences. Our framework is formulated in a confidence selection framework, which allows our system to recover from drift and partly deal with occlusion problem. To summarize, our algorithm can be roughly decomposed in a initialization stage and a tracking stage. In the initialization stage, an offline classifier is trained to get the object appearance information in category level. When the video stream is coming, the pre-trained offline classifier is used for detecting the potential target and initializing the tracking stage. In the tracking stage, it consists of three parts which are online tracking part, offline tracking part and confidence judgment part. Online tracking part captures the specific target appearance information while detection part localizes the object based on the pre-trained offline classifier. Since there is no data dependence between online tracking and offline detection, these two parts are running in parallel to significantly improve the processing speed. A confidence selection mechanism is proposed to optimize the object location. Besides, we also propose a simple mechanism to judge the absence of the object. If the target is lost, the pre-trained offline classifier is utilized to re-initialize the whole algorithm as long as the target is re-located. During experiment, we evaluate our method on several challenging video sequences and demonstrate competitive results.

Kernelized correlation tracking with long-term motion cues

NASA Astrophysics Data System (ADS)

Lv, Yunqiu; Liu, Kai; Cheng, Fei

2018-04-01

Robust object tracking is a challenging task in computer vision due to interruptions such as deformation, fast motion and especially, occlusion of tracked object. When occlusions occur, image data will be unreliable and is insufficient for the tracker to depict the object of interest. Therefore, most trackers are prone to fail under occlusion. In this paper, an occlusion judgement and handling method based on segmentation of the target is proposed. If the target is occluded, the speed and direction of it must be different from the objects occluding it. Hence, the value of motion features are emphasized. Considering the efficiency and robustness of Kernelized Correlation Filter Tracking (KCF), it is adopted as a pre-tracker to obtain a predicted position of the target. By analyzing long-term motion cues of objects around this position, the tracked object is labelled. Hence, occlusion could be detected easily. Experimental results suggest that our tracker achieves a favorable performance and effectively handles occlusion and drifting problems.

Grouping and trajectory storage in multiple object tracking: impairments due to common item motions.

PubMed

Suganuma, Mutsumi; Yokosawa, Kazuhiko

2006-01-01

In our natural viewing, we notice that objects change their locations across space and time. However, there has been relatively little consideration of the role of motion information in the construction and maintenance of object representations. We investigated this question in the context of the multiple object tracking (MOT) paradigm, wherein observers must keep track of target objects as they move randomly amid featurally identical distractors. In three experiments, we observed impairments in tracking ability when the motions of the target and distractor items shared particular properties. Specifically, we observed impairments when the target and distractor items were in a chasing relationship or moved in a uniform direction. Surprisingly, tracking ability was impaired by these manipulations even when observers failed to notice them. Our results suggest that differentiable trajectory information is an important factor in successful performance of MOT tasks. More generally, these results suggest that various types of common motion can serve as cues to form more global object representations even in the absence of other grouping cues.

Persistence of F-Specific RNA Coliphages in Surface Waters from a Produce Production Region along the Central Coast of California

PubMed Central

Ravva, Subbarao V.; Sarreal, Chester Z.

2016-01-01

F+ RNA coliphages (FRNA) are used to source-track fecal contamination and as surrogates for enteric pathogen persistence in the environment. However, the environmental persistence of FRNA is not clearly understood and necessitates the evaluation of the survival of prototype and environmental isolates of FRNA representing all four genogroups in surface waters from the central coast of California. Water temperature played a significant role in persistence–all prototype and environmental strains survived significantly longer at 10°C compared to 25°C. Similarly, the availability of host bacterium was found to be critical in FRNA survival. In the absence of E. coli Famp, all prototypes of FRNA disappeared rapidly with a D-value (days for one log reduction) of <1.2 d from water samples incubated at 25°C; the longest surviving prototype was SP. However, in the presence of the host, the order of persistence at 25°C was QB>MS2>SP>GA and at 10°C it was QB = MS2>GA>SP. Significant differences in survival were observed between prototypes and environmental isolates of FRNA. While most environmental isolates disappeared rapidly at 25°C and in the absence of the host, members of genogroups GIII and GI persisted longer with the host compared to members of GII and GIV. Consequentially, FRNA based source tracking methods can be used to detect phages from recent fecal contamination along with those that persist longer in the environment as a result of cooler temperatures and increased host presence. PMID:26784030

Nonlinear Motion Tracking by Deep Learning Architecture

NASA Astrophysics Data System (ADS)

Verma, Arnav; Samaiya, Devesh; Gupta, Karunesh K.

2018-03-01

In the world of Artificial Intelligence, object motion tracking is one of the major problems. The extensive research is being carried out to track people in crowd. This paper presents a unique technique for nonlinear motion tracking in the absence of prior knowledge of nature of nonlinear path that the object being tracked may follow. We achieve this by first obtaining the centroid of the object and then using the centroid as the current example for a recurrent neural network trained using real-time recurrent learning. We have tweaked the standard algorithm slightly and have accumulated the gradient for few previous iterations instead of using just the current iteration as is the norm. We show that for a single object, such a recurrent neural network is highly capable of approximating the nonlinearity of its path.

Developmental Profiles for Multiple Object Tracking and Spatial Memory: Typically Developing Preschoolers and People with Williams Syndrome

ERIC Educational Resources Information Center

O'Hearn, Kirsten; Hoffman, James E.; Landau, Barbara

2010-01-01

The ability to track moving objects, a crucial skill for mature performance on everyday spatial tasks, has been hypothesized to require a specialized mechanism that may be available in infancy (i.e. indexes). Consistent with the idea of specialization, our previous work showed that object tracking was more impaired than a matched spatial memory…

Assessing Multiple Object Tracking in Young Children Using a Game

ERIC Educational Resources Information Center

Ryokai, Kimiko; Farzin, Faraz; Kaltman, Eric; Niemeyer, Greg

2013-01-01

Visual tracking of multiple objects in a complex scene is a critical survival skill. When we attempt to safely cross a busy street, follow a ball's position during a sporting event, or monitor children in a busy playground, we rely on our brain's capacity to selectively attend to and track the position of specific objects in a dynamic scene. This…

Space Object Query Tool

NASA Technical Reports Server (NTRS)

Phillips, Veronica J.

2017-01-01

STI is for a fact sheet on the Space Object Query Tool being created by the MDC. When planning launches, NASA must first factor in the tens of thousands of objects already in orbit around the Earth. The number of human-made objects, including nonfunctional spacecraft, abandoned launch vehicle stages, mission-related debris and fragmentation debris orbiting Earth has grown steadily since Sputnik 1 was launched in 1957. Currently, the U.S. Department of Defenses Joint Space Operations Center, or JSpOC, tracks over 15,000 distinct objects and provides data for more than 40,000 objects via its Space-Track program, found at space-track.org.

Competency and Persistence of New College Students Enrolled in Math 310 at San Jose City College, Fall 1990. Research Report #127.

ERIC Educational Resources Information Center

Kangas, Jon; Budros, Kathleen

A study was conducted at San Jose City College (SJCC) to identify and track 163 new students enrolled in Math 310 over a period of several semesters. Data on the students' competency and persistence rates were collected for fall 1990 and spring 1991, along with subsequent math class enrollments and success rates. Study findings included the…

Persistent Insomnia: the Role of Objective Short Sleep Duration and Mental Health

PubMed Central

Vgontzas, Alexandros N.; Fernandez-Mendoza, Julio; Bixler, Edward O.; Singareddy, Ravi; Shaffer, Michele L.; Calhoun, Susan L.; Liao, Duanping; Basta, Maria; Chrousos, George P.

2012-01-01

Study Objectives: Few population-based, longitudinal studies have examined risk factors for persistent insomnia, and the results are inconsistent. Furthermore, none of these studies have examined the role of polysomnographic (PSG) variables such as sleep duration or sleep apnea on the persistence of insomnia. Design: Representative longitudinal study. Setting: Sleep laboratory. Participants: From a random, general population sample of 1741 individuals of the adult Penn State Cohort, 1395 were followed-up after 7.5 years. Measurements: Individuals underwent one-night PSG and full medical evaluation at baseline and a telephone interview at follow-up. PSG sleep duration was analyzed as a continuous variable and as a categorical variable: < 6 h sleep (short sleep duration) and ≥ 6 h sleep (longer sleep duration). Results: The rates of insomnia persistence, partial remission, and full remission were 44.0%, 30.0%, and 26.0%, respectively. Objective short sleep duration significantly increased the odds of persistent insomnia as compared to normal sleep (OR = 3.19) and to fully remitted insomnia (OR = 4.92). Mental health problems at baseline were strongly associated with persistent insomnia as compared to normal sleep (OR = 9.67) and to a lesser degree compared to fully remitted insomnia (OR = 3.68). Smoking, caffeine, and alcohol consumption and sleep apnea did not predict persistent insomnia. Conclusions: Objective short sleep duration and mental health problems are the strongest predictors of persistent insomnia. These data further support the validity and clinical utility of objective short sleep duration as a novel marker of the biological severity of insomnia. Citation: Vgontzas AN; Fernandez-Mendoza J; Bixler EO; Singareddy R; Shaffer ML; Calhoun SL; Liao D; Basta M; Chrousos GP. Persistent insomnia: the role of objective short sleep duration and mental health. SLEEP 2012;35(1):61-68. PMID:22215919

A Deep-Structured Conditional Random Field Model for Object Silhouette Tracking

PubMed Central

Shafiee, Mohammad Javad; Azimifar, Zohreh; Wong, Alexander

2015-01-01

In this work, we introduce a deep-structured conditional random field (DS-CRF) model for the purpose of state-based object silhouette tracking. The proposed DS-CRF model consists of a series of state layers, where each state layer spatially characterizes the object silhouette at a particular point in time. The interactions between adjacent state layers are established by inter-layer connectivity dynamically determined based on inter-frame optical flow. By incorporate both spatial and temporal context in a dynamic fashion within such a deep-structured probabilistic graphical model, the proposed DS-CRF model allows us to develop a framework that can accurately and efficiently track object silhouettes that can change greatly over time, as well as under different situations such as occlusion and multiple targets within the scene. Experiment results using video surveillance datasets containing different scenarios such as occlusion and multiple targets showed that the proposed DS-CRF approach provides strong object silhouette tracking performance when compared to baseline methods such as mean-shift tracking, as well as state-of-the-art methods such as context tracking and boosted particle filtering. PMID:26313943

Sustained multifocal attentional enhancement of stimulus processing in early visual areas predicts tracking performance.

PubMed

Störmer, Viola S; Winther, Gesche N; Li, Shu-Chen; Andersen, Søren K

2013-03-20

Keeping track of multiple moving objects is an essential ability of visual perception. However, the mechanisms underlying this ability are not well understood. We instructed human observers to track five or seven independent randomly moving target objects amid identical nontargets and recorded steady-state visual evoked potentials (SSVEPs) elicited by these stimuli. Visual processing of moving targets, as assessed by SSVEP amplitudes, was continuously facilitated relative to the processing of identical but irrelevant nontargets. The cortical sources of this enhancement were located to areas including early visual cortex V1-V3 and motion-sensitive area MT, suggesting that the sustained multifocal attentional enhancement during multiple object tracking already operates at hierarchically early stages of visual processing. Consistent with this interpretation, the magnitude of attentional facilitation during tracking in a single trial predicted the speed of target identification at the end of the trial. Together, these findings demonstrate that attention can flexibly and dynamically facilitate the processing of multiple independent object locations in early visual areas and thereby allow for tracking of these objects.

Unsupervised markerless 3-DOF motion tracking in real time using a single low-budget camera.

PubMed

Quesada, Luis; León, Alejandro J

2012-10-01

Motion tracking is a critical task in many computer vision applications. Existing motion tracking techniques require either a great amount of knowledge on the target object or specific hardware. These requirements discourage the wide spread of commercial applications based on motion tracking. In this paper, we present a novel three degrees of freedom motion tracking system that needs no knowledge on the target object and that only requires a single low-budget camera that can be found installed in most computers and smartphones. Our system estimates, in real time, the three-dimensional position of a nonmodeled unmarked object that may be nonrigid, nonconvex, partially occluded, self-occluded, or motion blurred, given that it is opaque, evenly colored, enough contrasting with the background in each frame, and that it does not rotate. Our system is also able to determine the most relevant object to track in the screen. Our proposal does not impose additional constraints, therefore it allows a market-wide implementation of applications that require the estimation of the three position degrees of freedom of an object.

An object detection and tracking system for unmanned surface vehicles

NASA Astrophysics Data System (ADS)

Yang, Jian; Xiao, Yang; Fang, Zhiwen; Zhang, Naiwen; Wang, Li; Li, Tao

2017-10-01

Object detection and tracking are critical parts of unmanned surface vehicles(USV) to achieve automatic obstacle avoidance. Off-the-shelf object detection methods have achieved impressive accuracy in public datasets, though they still meet bottlenecks in practice, such as high time consumption and low detection quality. In this paper, we propose a novel system for USV, which is able to locate the object more accurately while being fast and stable simultaneously. Firstly, we employ Faster R-CNN to acquire several initial raw bounding boxes. Secondly, the image is segmented to a few superpixels. For each initial box, the superpixels inside will be grouped into a whole according to a combination strategy, and a new box is thereafter generated as the circumscribed bounding box of the final superpixel. Thirdly, we utilize KCF to track these objects after several frames, Faster-RCNN is again used to re-detect objects inside tracked boxes to prevent tracking failure as well as remove empty boxes. Finally, we utilize Faster R-CNN to detect objects in the next image, and refine object boxes by repeating the second module of our system. The experimental results demonstrate that our system is fast, robust and accurate, which can be applied to USV in practice.

Multi-object detection and tracking technology based on hexagonal opto-electronic detector

NASA Astrophysics Data System (ADS)

Song, Yong; Hao, Qun; Li, Xiang

2008-02-01

A novel multi-object detection and tracking technology based on hexagonal opto-electronic detector is proposed, in which (1) a new hexagonal detector, which is composed of 6 linear CCDs, has been firstly developed to achieve the field of view of 360 degree, (2) to achieve the detection and tracking of multi-object with high speed, the object recognition criterions of Object Signal Width Criterion (OSWC) and Horizontal Scale Ratio Criterion (HSRC) are proposed. In this paper, Simulated Experiments have been carried out to verify the validity of the proposed technology, which show that the detection and tracking of multi-object can be achieved with high speed by using the proposed hexagonal detector and the criterions of OSWC and HSRC, indicating that the technology offers significant advantages in Photo-electric Detection, Computer Vision, Virtual Reality, Augment Reality, etc.

An efficient sequential approach to tracking multiple objects through crowds for real-time intelligent CCTV systems.

PubMed

Li, Liyuan; Huang, Weimin; Gu, Irene Yu-Hua; Luo, Ruijiang; Tian, Qi

2008-10-01

Efficiency and robustness are the two most important issues for multiobject tracking algorithms in real-time intelligent video surveillance systems. We propose a novel 2.5-D approach to real-time multiobject tracking in crowds, which is formulated as a maximum a posteriori estimation problem and is approximated through an assignment step and a location step. Observing that the occluding object is usually less affected by the occluded objects, sequential solutions for the assignment and the location are derived. A novel dominant color histogram (DCH) is proposed as an efficient object model. The DCH can be regarded as a generalized color histogram, where dominant colors are selected based on a given distance measure. Comparing with conventional color histograms, the DCH only requires a few color components (31 on average). Furthermore, our theoretical analysis and evaluation on real data have shown that DCHs are robust to illumination changes. Using the DCH, efficient implementations of sequential solutions for the assignment and location steps are proposed. The assignment step includes the estimation of the depth order for the objects in a dispersing group, one-by-one assignment, and feature exclusion from the group representation. The location step includes the depth-order estimation for the objects in a new group, the two-phase mean-shift location, and the exclusion of tracked objects from the new position in the group. Multiobject tracking results and evaluation from public data sets are presented. Experiments on image sequences captured from crowded public environments have shown good tracking results, where about 90% of the objects have been successfully tracked with the correct identification numbers by the proposed method. Our results and evaluation have indicated that the method is efficient and robust for tracking multiple objects (>or= 3) in complex occlusion for real-world surveillance scenarios.

Method and apparatus for imaging through 3-dimensional tracking of protons

NASA Technical Reports Server (NTRS)

Ryan, James M. (Inventor); Macri, John R. (Inventor); McConnell, Mark L. (Inventor)

2001-01-01

A method and apparatus for creating density images of an object through the 3-dimensional tracking of protons that have passed through the object are provided. More specifically, the 3-dimensional tracking of the protons is accomplished by gathering and analyzing images of the ionization tracks of the protons in a closely packed stack of scintillating fibers.

Online Hierarchical Sparse Representation of Multifeature for Robust Object Tracking

PubMed Central

Qu, Shiru

2016-01-01

Object tracking based on sparse representation has given promising tracking results in recent years. However, the trackers under the framework of sparse representation always overemphasize the sparse representation and ignore the correlation of visual information. In addition, the sparse coding methods only encode the local region independently and ignore the spatial neighborhood information of the image. In this paper, we propose a robust tracking algorithm. Firstly, multiple complementary features are used to describe the object appearance; the appearance model of the tracked target is modeled by instantaneous and stable appearance features simultaneously. A two-stage sparse-coded method which takes the spatial neighborhood information of the image patch and the computation burden into consideration is used to compute the reconstructed object appearance. Then, the reliability of each tracker is measured by the tracking likelihood function of transient and reconstructed appearance models. Finally, the most reliable tracker is obtained by a well established particle filter framework; the training set and the template library are incrementally updated based on the current tracking results. Experiment results on different challenging video sequences show that the proposed algorithm performs well with superior tracking accuracy and robustness. PMID:27630710

Visual tracking using objectness-bounding box regression and correlation filters

NASA Astrophysics Data System (ADS)

Mbelwa, Jimmy T.; Zhao, Qingjie; Lu, Yao; Wang, Fasheng; Mbise, Mercy

2018-03-01

Visual tracking is a fundamental problem in computer vision with extensive application domains in surveillance and intelligent systems. Recently, correlation filter-based tracking methods have shown a great achievement in terms of robustness, accuracy, and speed. However, such methods have a problem of dealing with fast motion (FM), motion blur (MB), illumination variation (IV), and drifting caused by occlusion (OCC). To solve this problem, a tracking method that integrates objectness-bounding box regression (O-BBR) model and a scheme based on kernelized correlation filter (KCF) is proposed. The scheme based on KCF is used to improve the tracking performance of FM and MB. For handling drift problem caused by OCC and IV, we propose objectness proposals trained in bounding box regression as prior knowledge to provide candidates and background suppression. Finally, scheme KCF as a base tracker and O-BBR are fused to obtain a state of a target object. Extensive experimental comparisons of the developed tracking method with other state-of-the-art trackers are performed on some of the challenging video sequences. Experimental comparison results show that our proposed tracking method outperforms other state-of-the-art tracking methods in terms of effectiveness, accuracy, and robustness.

Hyperactivity persists in male and female adults with ADHD and remains a highly discriminative feature of the disorder: a case-control study

PubMed Central

2012-01-01

Background Symptoms of hyperactivity are believed to fade with age leaving ADHD adults mostly inattentive and impulsive. Our aim was to test this assertion using objective measures of hyperactivity, impulsivity and inattention. Method Participants were 40 subjects with ADHD (23M/17F; 35±10 yrs) and 60 healthy adults (28M/32F; 29±9 yrs) blindly assessed using Wender-Reimherr interview ratings, Structured Clinical Interview for DSM-IV Disorders and DSM-IV criteria. Infrared motion capture systems tracked head and leg movements during performance of a No-4’s cognitive control task. Subjects also completed the Conners’ CPT-II. Results ADHD and controls differed significantly in activity and attention. Effect sizes for activity measures (d’ = 0.7–1.6) were, on average, two-fold larger than differences in attention or impulsivity, correlated more strongly with executive function ratings and were more discriminatory (ROC area = 0.83 for activity composite, 0.65 for No-4’s distraction composite, 0.63 for Conners’ CPT-II confidence index, 0.96 for the combined activity and attention diagnostic index). This finding was true for subjects with the predominantly inattentive subtype as well as subjects with combined or predominantly hyperactive/impulsive subtype. Males and females with ADHD were equally active. The superior accuracy of activity measures was confirmed using Random Forest and predictive modeling techniques. Conclusions Objectively measured hyperactivity persists in adults with ADHD and is a more discriminative feature of the disorder than computerized measures of inattention or impulsivity. This finding supports the hypothesis that a deficient ability to sit still remains a defining feature of the disorder in adults when it is measured objectively. PMID:23134619

A Temporal Same-Object Advantage in the Tunnel Effect: Facilitated Change Detection for Persisting Objects

ERIC Educational Resources Information Center

Flombaum, Jonathan I.; Scholl, Brian J.

2006-01-01

Meaningful visual experience requires computations that identify objects as the same persisting individuals over time, motion, occlusion, and featural change. This article explores these computations in the tunnel effect: When an object moves behind an occluder, and then an object later emerges following a consistent trajectory, observers…

Multi-view video segmentation and tracking for video surveillance

NASA Astrophysics Data System (ADS)

Mohammadi, Gelareh; Dufaux, Frederic; Minh, Thien Ha; Ebrahimi, Touradj

2009-05-01

Tracking moving objects is a critical step for smart video surveillance systems. Despite the complexity increase, multiple camera systems exhibit the undoubted advantages of covering wide areas and handling the occurrence of occlusions by exploiting the different viewpoints. The technical problems in multiple camera systems are several: installation, calibration, objects matching, switching, data fusion, and occlusion handling. In this paper, we address the issue of tracking moving objects in an environment covered by multiple un-calibrated cameras with overlapping fields of view, typical of most surveillance setups. Our main objective is to create a framework that can be used to integrate objecttracking information from multiple video sources. Basically, the proposed technique consists of the following steps. We first perform a single-view tracking algorithm on each camera view, and then apply a consistent object labeling algorithm on all views. In the next step, we verify objects in each view separately for inconsistencies. Correspondent objects are extracted through a Homography transform from one view to the other and vice versa. Having found the correspondent objects of different views, we partition each object into homogeneous regions. In the last step, we apply the Homography transform to find the region map of first view in the second view and vice versa. For each region (in the main frame and mapped frame) a set of descriptors are extracted to find the best match between two views based on region descriptors similarity. This method is able to deal with multiple objects. Track management issues such as occlusion, appearance and disappearance of objects are resolved using information from all views. This method is capable of tracking rigid and deformable objects and this versatility lets it to be suitable for different application scenarios.

An object tracking method based on guided filter for night fusion image

NASA Astrophysics Data System (ADS)

Qian, Xiaoyan; Wang, Yuedong; Han, Lei

2016-01-01

Online object tracking is a challenging problem as it entails learning an effective model to account for appearance change caused by intrinsic and extrinsic factors. In this paper, we propose a novel online object tracking with guided image filter for accurate and robust night fusion image tracking. Firstly, frame difference is applied to produce the coarse target, which helps to generate observation models. Under the restriction of these models and local source image, guided filter generates sufficient and accurate foreground target. Then accurate boundaries of the target can be extracted from detection results. Finally timely updating for observation models help to avoid tracking shift. Both qualitative and quantitative evaluations on challenging image sequences demonstrate that the proposed tracking algorithm performs favorably against several state-of-art methods.

Object-oriented Persistent Homology

PubMed Central

Wang, Bao; Wei, Guo-Wei

2015-01-01

Persistent homology provides a new approach for the topological simplification of big data via measuring the life time of intrinsic topological features in a filtration process and has found its success in scientific and engineering applications. However, such a success is essentially limited to qualitative data classification and analysis. Indeed, persistent homology has rarely been employed for quantitative modeling and prediction. Additionally, the present persistent homology is a passive tool, rather than a proactive technique, for classification and analysis. In this work, we outline a general protocol to construct object-oriented persistent homology methods. By means of differential geometry theory of surfaces, we construct an objective functional, namely, a surface free energy defined on the data of interest. The minimization of the objective functional leads to a Laplace-Beltrami operator which generates a multiscale representation of the initial data and offers an objective oriented filtration process. The resulting differential geometry based object-oriented persistent homology is able to preserve desirable geometric features in the evolutionary filtration and enhances the corresponding topological persistence. The cubical complex based homology algorithm is employed in the present work to be compatible with the Cartesian representation of the Laplace-Beltrami flow. The proposed Laplace-Beltrami flow based persistent homology method is extensively validated. The consistence between Laplace-Beltrami flow based filtration and Euclidean distance based filtration is confirmed on the Vietoris-Rips complex for a large amount of numerical tests. The convergence and reliability of the present Laplace-Beltrami flow based cubical complex filtration approach are analyzed over various spatial and temporal mesh sizes. The Laplace-Beltrami flow based persistent homology approach is utilized to study the intrinsic topology of proteins and fullerene molecules. Based on a quantitative model which correlates the topological persistence of fullerene central cavity with the total curvature energy of the fullerene structure, the proposed method is used for the prediction of fullerene isomer stability. The efficiency and robustness of the present method are verified by more than 500 fullerene molecules. It is shown that the proposed persistent homology based quantitative model offers good predictions of total curvature energies for ten types of fullerene isomers. The present work offers the first example to design object-oriented persistent homology to enhance or preserve desirable features in the original data during the filtration process and then automatically detect or extract the corresponding topological traits from the data. PMID:26705370

Performance analysis for bounded persistent disturbances in PD/PID-controlled robotic systems with its experimental demonstrations

NASA Astrophysics Data System (ADS)

Kim, Jung Hoon; Hur, Sung-Moon; Oh, Yonghwan

2018-03-01

This paper is concerned with performance analysis of proportional-derivative/proportional-integral-derivative (PD/PID) controller for bounded persistent disturbances in a robotic manipulator. Even though the notion of input-to-state stability (ISS) has been widely used to deal with the effect of disturbances in control of a robotic manipulator, the corresponding studies cannot be directly applied to the treatment of persistent disturbances occurred in robotic manipulators. This is because the conventional studies relevant to ISS consider the H∞ performance for robotic systems, which is confined to the treatment of decaying disturbances, i.e. the disturbances those in the L2 space. To deal with the effect of persistent disturbances in robotic systems, we first provide a new treatment of ISS in the L∞ sense because bounded persistent disturbances should be intrinsically regarded as elements of the L∞ space. We next derive state-space representations of trajectory tracking control in the robotic systems which allow us to define the problem formulations more clearly. We then propose a novel control law that has a PD/PID control form, by which the trajectory tracking system satisfies the reformulated ISS. Furthermore, we can obtain a theoretical argument about the L∞ gain from the disturbance to the regulated output through the proposed control law. Finally, experimental studies for a typical 3-degrees of freedom robotic manipulator are given to demonstrate the effectiveness of the method introduced in this paper.

Image-based tracking system for vibration measurement of a rotating object using a laser scanning vibrometer

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

Kim, Dongkyu, E-mail: akein@gist.ac.kr; Khalil, Hossam; Jo, Youngjoon

2016-06-28

An image-based tracking system using laser scanning vibrometer is developed for vibration measurement of a rotating object. The proposed system unlike a conventional one can be used where the position or velocity sensor such as an encoder cannot be attached to an object. An image processing algorithm is introduced to detect a landmark and laser beam based on their colors. Then, through using feedback control system, the laser beam can track a rotating object.

Visual object tracking by correlation filters and online learning

NASA Astrophysics Data System (ADS)

Zhang, Xin; Xia, Gui-Song; Lu, Qikai; Shen, Weiming; Zhang, Liangpei

2018-06-01

Due to the complexity of background scenarios and the variation of target appearance, it is difficult to achieve high accuracy and fast speed for object tracking. Currently, correlation filters based trackers (CFTs) show promising performance in object tracking. The CFTs estimate the target's position by correlation filters with different kinds of features. However, most of CFTs can hardly re-detect the target in the case of long-term tracking drifts. In this paper, a feature integration object tracker named correlation filters and online learning (CFOL) is proposed. CFOL estimates the target's position and its corresponding correlation score using the same discriminative correlation filter with multi-features. To reduce tracking drifts, a new sampling and updating strategy for online learning is proposed. Experiments conducted on 51 image sequences demonstrate that the proposed algorithm is superior to the state-of-the-art approaches.

Fusion of Cross-Track TerraSAR-X PS Point Clouds over Las Vegas

NASA Astrophysics Data System (ADS)

Wang, Ziyun; Balz, Timo; Wei, Lianhuan; Liao, Mingsheng

2014-11-01

Persistent scatterer interferometry (PS-InSAR) is widely used in radar remote sensing. However, because the surface motion is estimated in the line-of-sight (LOS) direction, it is not possible to differentiate between vertical and horizontal surface motions from a single stack. Cross-track data, i.e. the combination of data from ascending and descending orbits, allows us to better analyze the deformation and to obtain 3d motion information. We implemented a cross-track fusion of PS-InSAR point cloud data, making it possible to separate the vertical and horizontal components of the surface motion.

A-Track: Detecting Moving Objects in FITS images

NASA Astrophysics Data System (ADS)

Atay, T.; Kaplan, M.; Kilic, Y.; Karapinar, N.

2017-04-01

A-Track is a fast, open-source, cross-platform pipeline for detecting moving objects (asteroids and comets) in sequential telescope images in FITS format. The moving objects are detected using a modified line detection algorithm.

Like a rolling stone: naturalistic visual kinematics facilitate tracking eye movements.

PubMed

Souto, David; Kerzel, Dirk

2013-02-06

Newtonian physics constrains object kinematics in the real world. We asked whether eye movements towards tracked objects depend on their compliance with those constraints. In particular, the force of gravity constrains round objects to roll on the ground with a particular rotational and translational motion. We measured tracking eye movements towards rolling objects. We found that objects with rotational and translational motion that was congruent with an object rolling on the ground elicited faster tracking eye movements during pursuit initiation than incongruent stimuli. Relative to a condition without rotational component, we compared objects with this motion with a condition in which there was no rotational component, we essentially obtained benefits of congruence, and, to a lesser extent, costs from incongruence. Anticipatory pursuit responses showed no congruence effect, suggesting that the effect is based on visually-driven predictions, not on velocity storage. We suggest that the eye movement system incorporates information about object kinematics acquired by a lifetime of experience with visual stimuli obeying the laws of Newtonian physics.

Autonomous Space Object Catalogue Construction and Upkeep Using Sensor Control Theory

NASA Astrophysics Data System (ADS)

Moretti, N.; Rutten, M.; Bessell, T.; Morreale, B.

The capability to track objects in space is critical to safeguard domestic and international space assets. Infrequent measurement opportunities, complex dynamics and partial observability of orbital state makes the tracking of resident space objects nontrivial. It is not uncommon for human operators to intervene with space tracking systems, particularly in scheduling sensors. This paper details the development of a system that maintains a catalogue of geostationary objects through dynamically tasking sensors in real time by managing the uncertainty of object states. As the number of objects in space grows the potential for collision grows exponentially. Being able to provide accurate assessment to operators regarding costly collision avoidance manoeuvres is paramount; the accuracy of which is highly dependent on how object states are estimated. The system represents object state and uncertainty using particles and utilises a particle filter for state estimation. Particle filters capture the model and measurement uncertainty accurately, allowing for a more comprehensive representation of the state’s probability density function. Additionally, the number of objects in space is growing disproportionally to the number of sensors used to track them. Maintaining precise positions for all objects places large loads on sensors, limiting the time available to search for new objects or track high priority objects. Rather than precisely track all objects our system manages the uncertainty in orbital state for each object independently. The uncertainty is allowed to grow and sensor data is only requested when the uncertainty must be reduced. For example when object uncertainties overlap leading to data association issues or if the uncertainty grows to beyond a field of view. These control laws are formulated into a cost function, which is optimised in real time to task sensors. By controlling an optical telescope the system has been able to construct and maintain a catalogue of approximately 100 geostationary objects.

Nonstationary EO/IR Clutter Suppression and Dim Object Tracking

DTIC Science & Technology

2010-01-01

Brown, A., and Brown, J., Enhanced Algorithms for EO /IR Electronic Stabilization, Clutter Suppression, and Track - Before - Detect for Multiple Low...estimation-suppression and nonlinear filtering-based multiple-object track - before - detect . These algorithms are suitable for integration into...In such cases, it is imperative to develop efficient real or near-real time tracking before detection methods. This paper continues the work started

A mathematical model for computer image tracking.

PubMed

Legters, G R; Young, T Y

1982-06-01

A mathematical model using an operator formulation for a moving object in a sequence of images is presented. Time-varying translation and rotation operators are derived to describe the motion. A variational estimation algorithm is developed to track the dynamic parameters of the operators. The occlusion problem is alleviated by using a predictive Kalman filter to keep the tracking on course during severe occlusion. The tracking algorithm (variational estimation in conjunction with Kalman filter) is implemented to track moving objects with occasional occlusion in computer-simulated binary images.

Collections and user tools for utilization of persistent identifiers in cyberinfrastructures

NASA Astrophysics Data System (ADS)

Weigel, T.

2014-12-01

The main use of persistent identifiers (PIDs) for data objects has so far been for formal publication and citation purposes with a focus on long-term availability and trust. This core use case has now evolved and broadened to include basic data management tasks as identifiers are increasingly seen as a possible anchor element in the deluge of data for purposes of large-scale automation of tasks. The European Data Infrastructure (EUDAT) for instance uses PIDs in their back-end services and distinctly so for entities where the identifier may be more persistent than a resource with limited lifetime. Despite breaking with the traditional metaphor, this offers new opportunities for data management and end-user tools, but also requires a clear demonstrated benefit of value-added services because en masse identifier assignment does not come at zero costs. There are several obstacles to overcome when establishing identifiers at large scale. The administration of large numbers of identifiers can be cumbersome if they are treated in an isolated manner. Here, identifier collections can enable automated mass operations on groups of associated objects. Several use cases rely on base information that is rapidly available from the identifier systems without the need to retrieve objects, yet they will not work efficiently if the information is not consistently typed. Tools that span cyberinfrastructures and address scientific end-users unaware of the varying back-ends must overcome such obstacles. The Working Group on PID Information Types of the Research Data Alliance (RDA) has developed an interface specification and prototype to access and manipulate typed base information. Concrete prototypes for identifier collections exist as well. We will present some first data and provenance tracking tools that make extensive use of these recent developments and address different user needs that span from administrative tasks to individual end-user services with particular focus on data available from the Earth System Grid Federation (ESGF). We will compare the tools along their respective use cases with existing approaches and discuss benefits and limitations.

Multiple player tracking in sports video: a dual-mode two-way bayesian inference approach with progressive observation modeling.

PubMed

Xing, Junliang; Ai, Haizhou; Liu, Liwei; Lao, Shihong

2011-06-01

Multiple object tracking (MOT) is a very challenging task yet of fundamental importance for many practical applications. In this paper, we focus on the problem of tracking multiple players in sports video which is even more difficult due to the abrupt movements of players and their complex interactions. To handle the difficulties in this problem, we present a new MOT algorithm which contributes both in the observation modeling level and in the tracking strategy level. For the observation modeling, we develop a progressive observation modeling process that is able to provide strong tracking observations and greatly facilitate the tracking task. For the tracking strategy, we propose a dual-mode two-way Bayesian inference approach which dynamically switches between an offline general model and an online dedicated model to deal with single isolated object tracking and multiple occluded object tracking integrally by forward filtering and backward smoothing. Extensive experiments on different kinds of sports videos, including football, basketball, as well as hockey, demonstrate the effectiveness and efficiency of the proposed method.

A case Study of Applying Object-Relational Persistence in Astronomy Data Archiving

NASA Astrophysics Data System (ADS)

Yao, S. S.; Hiriart, R.; Barg, I.; Warner, P.; Gasson, D.

2005-12-01

The NOAO Science Archive (NSA) team is developing a comprehensive domain model to capture the science data in the archive. Java and an object model derived from the domain model weil address the application layer of the archive system. However, since RDBMS is the best proven technology for data management, the challenge is the paradigm mismatch between the object and the relational models. Transparent object-relational mapping (ORM) persistence is a successful solution to this challenge. In the data modeling and persistence implementation of NSA, we are using Hibernate, a well-accepted ORM tool, to bridge the object model in the business tier and the relational model in the database tier. Thus, the database is isolated from the Java application. The application queries directly on objects using a DBMS-independent object-oriented query API, which frees the application developers from the low level JDBC and SQL so that they can focus on the domain logic. We present the detailed design of the NSA R3 (Release 3) data model and object-relational persistence, including mapping, retrieving and caching. Persistence layer optimization and performance tuning will be analyzed. The system is being built on J2EE, so the integration of Hibernate into the EJB container and the transaction management are also explored.

What is the Value Proposition of Persistent Identifiers?

NASA Astrophysics Data System (ADS)

Klump, Jens; Huber, Robert

2017-04-01

Persistent identifiers (PID) are widely used today in scientific communication and documentation. Global unique identification plus persistent resolution of links to referenced digital research objects have been strong selling points for PID Systems as enabling technical infrastructures. Novel applications of PID Systems in research now go beyond the identification of file based objects such as literature or data sets and include the identification of dynamically changing datasets accessed through web services, physical objects, persons and organisations. But not only do we see more use cases but also a proliferation of identifier systems. An analysis of PID Systems used by 1381 repositories listed in the Registry of Research Data Repositories (re3data.org, status of 14 Dec 2015) showed that many disciplinary data repositories make use of PID that are not among the systems promoted by the libraries and publishers (DOI, PURL, ARK). This indicates that a number of communities have developed their own PID Systems. This begs the question, do we need more identifier systems? What makes their value proposition more appealing than those of already existing systems? On the other hand, some of these new use cases deal with entities outside the digital domain, the original scope of application for PIDs. It is therefore necessary to critically appraise the value propositions of available PID Systems and compare these against the requirements of new use cases for PID. Undoubtedly, DOI are the most used persistent identifier in scholarly communication. It was originally designed "to link customers with publishers, facilitate electronic commerce, and enable copyright management systems." Today, the DOI system is described as providing "a technical and social infrastructure for the registration and use of persistent interoperable identifiers for use on digital networks". This example shows how value propositions can change over time. Additional value can be gained by cross-linking between PID Systems, thus allowing new scholarly documentation and evaluation methods such as documenting the track record of researchers in publications and successful funding proposals, apply advanced bibliometric approaches, estimate the output and impact of funding, assess the reuse and subsequent impact of data publications, demonstrate the efficient use of research infrastructures, etc. This recombination of systems raise a series of new expectations and each stakeholder group may have its own vision of the benefits and value proposition of PIDs, which might be in conflict with others. New PID applications will arise with the application of PID Systems to semantic web technologies and to the Internet of Things, which extend PID applications to beyond digital objects to concepts and things, respectively, raising yet again their own expectations and value propositions. What are we trying to identify? What is the purpose served by identifying it? What are the implications for semantic web technologies? How certain can we be about the identity of an object and its state changes over time (Ship of Theseus Paradox)? In this presentation we will discuss a number of PID use cases and match these against the value propositions offered by a selection of PID Systems.

Putting and Keeping Students on Track: Toward a Comprehensive Model of College Persistence and Goal Attainment. Research Report. ETS RR-13-14

ERIC Educational Resources Information Center

Burrus, Jeremy; Elliott, Diane; Brenneman, Meghan; Markle, Ross; Carney, Lauren; Moore, Gabrielle; Betancourt, Anthony; Jackson, Teresa; Robbins, Steve; Kyllonen, Patrick; Roberts, Richard D.

2013-01-01

Despite near universal acceptance in the value of higher education for individuals and society, college persistence rates in 4-year and community colleges are low. Only 57% of students who began college at a 4-year institution in 2001 had completed a bachelor's degree by 2007, and only 28% of community college students who started school in 2005…

Optical Jitter Effects on Target Detection and Tracking of Overhead Persistent Infrared Systems

DTIC Science & Technology

2015-12-01

infrared CdSe cadmium selenide DSP Defense Support Program FIR far-infrared FPA focal plane array Ge germanium GEO geostationary earth orbit...HBCRT High Energy Laser Beam Control Research Testbed HEL high energy laser HgCdTe mercury cadmium telluride IR infrared InSb indium antimonide...MOD model MTF modulation transfer function MWIR mid-wave infrared NIR near infrared OPIR overhead persistent infrared PbSe lead selenide

Ship recognition for improved persistent tracking with descriptor localization and compact representations

NASA Astrophysics Data System (ADS)

van den Broek, Sebastiaan P.; Bouma, Henri; den Hollander, Richard J. M.; Veerman, Henny E. T.; Benoist, Koen W.; Schwering, Piet B. W.

2014-10-01

For maritime situational awareness, it is important to identify currently observed ships as earlier encounters. For example, past location and behavior analysis are useful to determine whether a ship is of interest in case of piracy and smuggling. It is beneficial to verify this with cameras at a distance, to avoid the costs of bringing an own asset closer to the ship. The focus of this paper is on ship recognition from electro-optical imagery. The main contribution is an analysis of the effect of using the combination of descriptor localization and compact representations. An evaluation is performed to assess the usefulness in persistent tracking, especially for larger intervals (i.e. re-identification of ships). From the evaluation on recordings of imagery, it is estimated how well the system discriminates between different ships.

Biology of Epstein-Barr virus during infectious mononucleosis.

PubMed

Sitki-Green, Diane L; Edwards, Rachel Hood; Covington, Mary M; Raab-Traub, Nancy

2004-02-01

Infectious mononucleosis is the clinical manifestation of primary infection with Epstein-Barr virus (EBV). We monitored primary infection during convalescence and during the establishment of persistent infection. The profiles of EBV strains in the oral cavity and in peripheral blood were determined by use of a heteroduplex tracking assay specific for the EBV gene encoding latent membrane protein 1. Multiple EBV strains were detected in most patients and persisted in and were possibly transmitted among 3 distinct compartments of infection, including the oral cavity, peripheral blood lymphocytes, and the cell-free fraction of the blood plasma. We also tracked transmission of multiple strains from an asymptomatic carrier to a patient diagnosed with primary EBV infection. These data reveal that primary EBV infection is complex, with transmission of multiple strains and clear differences in relative abundance of strains in distinct compartments.

Object tracking using multiple camera video streams

NASA Astrophysics Data System (ADS)

Mehrubeoglu, Mehrube; Rojas, Diego; McLauchlan, Lifford

2010-05-01

Two synchronized cameras are utilized to obtain independent video streams to detect moving objects from two different viewing angles. The video frames are directly correlated in time. Moving objects in image frames from the two cameras are identified and tagged for tracking. One advantage of such a system involves overcoming effects of occlusions that could result in an object in partial or full view in one camera, when the same object is fully visible in another camera. Object registration is achieved by determining the location of common features in the moving object across simultaneous frames. Perspective differences are adjusted. Combining information from images from multiple cameras increases robustness of the tracking process. Motion tracking is achieved by determining anomalies caused by the objects' movement across frames in time in each and the combined video information. The path of each object is determined heuristically. Accuracy of detection is dependent on the speed of the object as well as variations in direction of motion. Fast cameras increase accuracy but limit the speed and complexity of the algorithm. Such an imaging system has applications in traffic analysis, surveillance and security, as well as object modeling from multi-view images. The system can easily be expanded by increasing the number of cameras such that there is an overlap between the scenes from at least two cameras in proximity. An object can then be tracked long distances or across multiple cameras continuously, applicable, for example, in wireless sensor networks for surveillance or navigation.

Automated Tracking of Cell Migration with Rapid Data Analysis.

PubMed

DuChez, Brian J

2017-09-01

Cell migration is essential for many biological processes including development, wound healing, and metastasis. However, studying cell migration often requires the time-consuming and labor-intensive task of manually tracking cells. To accelerate the task of obtaining coordinate positions of migrating cells, we have developed a graphical user interface (GUI) capable of automating the tracking of fluorescently labeled nuclei. This GUI provides an intuitive user interface that makes automated tracking accessible to researchers with no image-processing experience or familiarity with particle-tracking approaches. Using this GUI, users can interactively determine a minimum of four parameters to identify fluorescently labeled cells and automate acquisition of cell trajectories. Additional features allow for batch processing of numerous time-lapse images, curation of unwanted tracks, and subsequent statistical analysis of tracked cells. Statistical outputs allow users to evaluate migratory phenotypes, including cell speed, distance, displacement, and persistence, as well as measures of directional movement, such as forward migration index (FMI) and angular displacement. © 2017 by John Wiley & Sons, Inc. Copyright © 2017 John Wiley & Sons, Inc.

Electrically tunable lens speeds up 3D orbital tracking

PubMed Central

Annibale, Paolo; Dvornikov, Alexander; Gratton, Enrico

2015-01-01

3D orbital particle tracking is a versatile and effective microscopy technique that allows following fast moving fluorescent objects within living cells and reconstructing complex 3D shapes using laser scanning microscopes. We demonstrated notable improvements in the range, speed and accuracy of 3D orbital particle tracking by replacing commonly used piezoelectric stages with Electrically Tunable Lens (ETL) that eliminates mechanical movement of objective lenses. This allowed tracking and reconstructing shape of structures extending 500 microns in the axial direction. Using the ETL, we tracked at high speed fluorescently labeled genomic loci within the nucleus of living cells with unprecedented temporal resolution of 8ms using a 1.42NA oil-immersion objective. The presented technology is cost effective and allows easy upgrade of scanning microscopes for fast 3D orbital tracking. PMID:26114037

Tracking Algorithm of Multiple Pedestrians Based on Particle Filters in Video Sequences

PubMed Central

Liu, Yun; Wang, Chuanxu; Zhang, Shujun; Cui, Xuehong

2016-01-01

Pedestrian tracking is a critical problem in the field of computer vision. Particle filters have been proven to be very useful in pedestrian tracking for nonlinear and non-Gaussian estimation problems. However, pedestrian tracking in complex environment is still facing many problems due to changes of pedestrian postures and scale, moving background, mutual occlusion, and presence of pedestrian. To surmount these difficulties, this paper presents tracking algorithm of multiple pedestrians based on particle filters in video sequences. The algorithm acquires confidence value of the object and the background through extracting a priori knowledge thus to achieve multipedestrian detection; it adopts color and texture features into particle filter to get better observation results and then automatically adjusts weight value of each feature according to current tracking environment. During the process of tracking, the algorithm processes severe occlusion condition to prevent drift and loss phenomena caused by object occlusion and associates detection results with particle state to propose discriminated method for object disappearance and emergence thus to achieve robust tracking of multiple pedestrians. Experimental verification and analysis in video sequences demonstrate that proposed algorithm improves the tracking performance and has better tracking results. PMID:27847514

Semi-Supervised Tensor-Based Graph Embedding Learning and Its Application to Visual Discriminant Tracking.

PubMed

Hu, Weiming; Gao, Jin; Xing, Junliang; Zhang, Chao; Maybank, Stephen

2017-01-01

An appearance model adaptable to changes in object appearance is critical in visual object tracking. In this paper, we treat an image patch as a two-order tensor which preserves the original image structure. We design two graphs for characterizing the intrinsic local geometrical structure of the tensor samples of the object and the background. Graph embedding is used to reduce the dimensions of the tensors while preserving the structure of the graphs. Then, a discriminant embedding space is constructed. We prove two propositions for finding the transformation matrices which are used to map the original tensor samples to the tensor-based graph embedding space. In order to encode more discriminant information in the embedding space, we propose a transfer-learning- based semi-supervised strategy to iteratively adjust the embedding space into which discriminative information obtained from earlier times is transferred. We apply the proposed semi-supervised tensor-based graph embedding learning algorithm to visual tracking. The new tracking algorithm captures an object's appearance characteristics during tracking and uses a particle filter to estimate the optimal object state. Experimental results on the CVPR 2013 benchmark dataset demonstrate the effectiveness of the proposed tracking algorithm.

Kalman filter-based tracking of moving objects using linear ultrasonic sensor array for road vehicles

NASA Astrophysics Data System (ADS)

Li, Shengbo Eben; Li, Guofa; Yu, Jiaying; Liu, Chang; Cheng, Bo; Wang, Jianqiang; Li, Keqiang

2018-01-01

Detection and tracking of objects in the side-near-field has attracted much attention for the development of advanced driver assistance systems. This paper presents a cost-effective approach to track moving objects around vehicles using linearly arrayed ultrasonic sensors. To understand the detection characteristics of a single sensor, an empirical detection model was developed considering the shapes and surface materials of various detected objects. Eight sensors were arrayed linearly to expand the detection range for further application in traffic environment recognition. Two types of tracking algorithms, including an Extended Kalman filter (EKF) and an Unscented Kalman filter (UKF), for the sensor array were designed for dynamic object tracking. The ultrasonic sensor array was designed to have two types of fire sequences: mutual firing or serial firing. The effectiveness of the designed algorithms were verified in two typical driving scenarios: passing intersections with traffic sign poles or street lights, and overtaking another vehicle. Experimental results showed that both EKF and UKF had more precise tracking position and smaller RMSE (root mean square error) than a traditional triangular positioning method. The effectiveness also encourages the application of cost-effective ultrasonic sensors in the near-field environment perception in autonomous driving systems.

Monitoring Tropical Cyclone Impacts on the Coastal Vegetation of the Southeastern USA in the First Decade of the 21st Century

NASA Astrophysics Data System (ADS)

Brun, J.; Barros, A. P.

2010-12-01

Hurricanes and tropical storms are powerful and hazardous meteorological phenomena causing damages to natural and built areas all around the world. However, on the flip side, Tropical cyclones provide a significant influx of freshwater resources to surface and subsurface reservoirs during the warm season. Therefore it is important to understand ecosystem response to such extreme climatic events, especially in a context of potential changes in the track, frequency or strength of these phenomena that could be induced by climatic change. Here we present a method to measure vegetation disturbance persistence in the aftermath of tropical cyclones based on MODIS North American Carbon Program (NACP) vegetation indices (8-day composite at 500m spatial resolution) was developed with the objective of assessing the eco-hydrological impact of hurricanes in the South-East United States. This technique is based on the relationship between vegetation stress and the persistence of standardized Enhanced Vegetation Index (EVI) anomalies along the terrestrial path of hurricanes. An independent evaluation was conducted against 25 years (1982-2006) of AVHRR data from the Global Inventory Modeling and Mapping Studies (GIMMS) database. The data show that in the aftermath of hurricane landfall, there is a significant decrease in chlorophyll activity at very low elevations, including coastal marshes, wetlands, and the drainage networks of major river systems aligned with the terrestrial path of the storm. This vegetation activity disturbance persists longer (up two 2 years) in coastal areas than in inland forests and could be consistent with impact of salt intrusion in shallow coastal aquifers. In alluvial plains, the spatial pattern of the vegetation anomalies persistence seems to be mostly associated with flooding.

Multiple-Object Tracking in Children: The "Catch the Spies" Task

ERIC Educational Resources Information Center

Trick, L.M.; Jaspers-Fayer, F.; Sethi, N.

2005-01-01

Multiple-object tracking involves simultaneously tracking positions of a number of target-items as they move among distractors. The standard version of the task poses special challenges for children, demanding extended concentration and the ability to distinguish targets from identical-looking distractors, and may thus underestimate children's…

Long-term object tracking combined offline with online learning

NASA Astrophysics Data System (ADS)

Hu, Mengjie; Wei, Zhenzhong; Zhang, Guangjun

2016-04-01

We propose a simple yet effective method for long-term object tracking. Different from the traditional visual tracking method, which mainly depends on frame-to-frame correspondence, we combine high-level semantic information with low-level correspondences. Our framework is formulated in a confidence selection framework, which allows our system to recover from drift and partly deal with occlusion. To summarize, our algorithm can be roughly decomposed into an initialization stage and a tracking stage. In the initialization stage, an offline detector is trained to get the object appearance information at the category level, which is used for detecting the potential target and initializing the tracking stage. The tracking stage consists of three modules: the online tracking module, detection module, and decision module. A pretrained detector is used for maintaining drift of the online tracker, while the online tracker is used for filtering out false positive detections. A confidence selection mechanism is proposed to optimize the object location based on the online tracker and detection. If the target is lost, the pretrained detector is utilized to reinitialize the whole algorithm when the target is relocated. During experiments, we evaluate our method on several challenging video sequences, and it demonstrates huge improvement compared with detection and online tracking only.

Improved semi-supervised online boosting for object tracking

NASA Astrophysics Data System (ADS)

Li, Yicui; Qi, Lin; Tan, Shukun

2016-10-01

The advantage of an online semi-supervised boosting method which takes object tracking problem as a classification problem, is training a binary classifier from labeled and unlabeled examples. Appropriate object features are selected based on real time changes in the object. However, the online semi-supervised boosting method faces one key problem: The traditional self-training using the classification results to update the classifier itself, often leads to drifting or tracking failure, due to the accumulated error during each update of the tracker. To overcome the disadvantages of semi-supervised online boosting based on object tracking methods, the contribution of this paper is an improved online semi-supervised boosting method, in which the learning process is guided by positive (P) and negative (N) constraints, termed P-N constraints, which restrict the labeling of the unlabeled samples. First, we train the classification by an online semi-supervised boosting. Then, this classification is used to process the next frame. Finally, the classification is analyzed by the P-N constraints, which are used to verify if the labels of unlabeled data assigned by the classifier are in line with the assumptions made about positive and negative samples. The proposed algorithm can effectively improve the discriminative ability of the classifier and significantly alleviate the drifting problem in tracking applications. In the experiments, we demonstrate real-time tracking of our tracker on several challenging test sequences where our tracker outperforms other related on-line tracking methods and achieves promising tracking performance.

Mark Tracking: Position/orientation measurements using 4-circle mark and its tracking experiments

NASA Technical Reports Server (NTRS)

Kanda, Shinji; Okabayashi, Keijyu; Maruyama, Tsugito; Uchiyama, Takashi

1994-01-01

Future space robots require position and orientation tracking with visual feedback control to track and capture floating objects and satellites. We developed a four-circle mark that is useful for this purpose. With this mark, four geometric center positions as feature points can be extracted from the mark by simple image processing. We also developed a position and orientation measurement method that uses the four feature points in our mark. The mark gave good enough image measurement accuracy to let space robots approach and contact objects. A visual feedback control system using this mark enabled a robot arm to track a target object accurately. The control system was able to tolerate a time delay of 2 seconds.

Compressed multi-block local binary pattern for object tracking

NASA Astrophysics Data System (ADS)

Li, Tianwen; Gao, Yun; Zhao, Lei; Zhou, Hao

2018-04-01

Both robustness and real-time are very important for the application of object tracking under a real environment. The focused trackers based on deep learning are difficult to satisfy with the real-time of tracking. Compressive sensing provided a technical support for real-time tracking. In this paper, an object can be tracked via a multi-block local binary pattern feature. The feature vector was extracted based on the multi-block local binary pattern feature, which was compressed via a sparse random Gaussian matrix as the measurement matrix. The experiments showed that the proposed tracker ran in real-time and outperformed the existed compressive trackers based on Haar-like feature on many challenging video sequences in terms of accuracy and robustness.

Doublet Pulse Coherent Laser Radar for Tracking of Resident Space Objects

DTIC Science & Technology

2014-09-01

based laser systems can be limited by the effects of tumbling, extremely accurate Doppler measurement is possible using a doublet coherent laser ...Doublet pulse coherent laser radar for tracking of resident space objects Narasimha S. Prasad *1 , Van Rudd 2 , Scott Shald 2 , Stephan...Doublet Pulse Coherent Laser Radar for Tracking of Resident Space Objects 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S

Phenomenal permanence and the development of predictive tracking in infancy.

PubMed

Bertenthal, Bennett I; Longo, Matthew R; Kenny, Sarah

2007-01-01

The perceived spatiotemporal continuity of objects depends on the way they appear and disappear as they move in the spatial layout. This study investigated whether infants' predictive tracking of a briefly occluded object is sensitive to the manner by which the object disappears and reappears. Five-, 7-, and 9-month-old infants were shown a ball rolling across a visual scene and briefly disappearing via kinetic occlusion, instantaneous disappearance, implosion, or virtual occlusion. Three different measures converged to show that predictive tracking increased with age and that infants were most likely to anticipate the reappearance of the ball following kinetic occlusion. These results suggest that infants' knowledge of the permanence and nonpermanence of objects is embodied in their predictive tracking.

Robust object matching for persistent tracking with heterogeneous features.

PubMed

Guo, Yanlin; Hsu, Steve; Sawhney, Harpreet S; Kumar, Rakesh; Shan, Ying

2007-05-01

This paper addresses the problem of matching vehicles across multiple sightings under variations in illumination and camera poses. Since multiple observations of a vehicle are separated in large temporal and/or spatial gaps, thus prohibiting the use of standard frame-to-frame data association, we employ features extracted over a sequence during one time interval as a vehicle fingerprint that is used to compute the likelihood that two or more sequence observations are from the same or different vehicles. Furthermore, since our domain is aerial video tracking, in order to deal with poor image quality and large resolution and quality variations, our approach employs robust alignment and match measures for different stages of vehicle matching. Most notably, we employ a heterogeneous collection of features such as lines, points, and regions in an integrated matching framework. Heterogeneous features are shown to be important. Line and point features provide accurate localization and are employed for robust alignment across disparate views. The challenges of change in pose, aspect, and appearances across two disparate observations are handled by combining a novel feature-based quasi-rigid alignment with flexible matching between two or more sequences. However, since lines and points are relatively sparse, they are not adequate to delineate the object and provide a comprehensive matching set that covers the complete object. Region features provide a high degree of coverage and are employed for continuous frames to provide a delineation of the vehicle region for subsequent generation of a match measure. Our approach reliably delineates objects by representing regions as robust blob features and matching multiple regions to multiple regions using Earth Mover's Distance (EMD). Extensive experimentation under a variety of real-world scenarios and over hundreds of thousands of Confirmatory Identification (CID) trails has demonstrated about 95 percent accuracy in vehicle reacquisition with both visible and Infrared (IR) imaging cameras.

Robust feedback zoom tracking for digital video surveillance.

PubMed

Zou, Tengyue; Tang, Xiaoqi; Song, Bao; Wang, Jin; Chen, Jihong

2012-01-01

Zoom tracking is an important function in video surveillance, particularly in traffic management and security monitoring. It involves keeping an object of interest in focus during the zoom operation. Zoom tracking is typically achieved by moving the zoom and focus motors in lenses following the so-called "trace curve", which shows the in-focus motor positions versus the zoom motor positions for a specific object distance. The main task of a zoom tracking approach is to accurately estimate the trace curve for the specified object. Because a proportional integral derivative (PID) controller has historically been considered to be the best controller in the absence of knowledge of the underlying process and its high-quality performance in motor control, in this paper, we propose a novel feedback zoom tracking (FZT) approach based on the geometric trace curve estimation and PID feedback controller. The performance of this approach is compared with existing zoom tracking methods in digital video surveillance. The real-time implementation results obtained on an actual digital video platform indicate that the developed FZT approach not only solves the traditional one-to-many mapping problem without pre-training but also improves the robustness for tracking moving or switching objects which is the key challenge in video surveillance.

Immersive Virtual Reality Therapy with Myoelectric Control for Treatment-resistant Phantom Limb Pain: Case Report.

PubMed

Chau, Brian; Phelan, Ivan; Ta, Phillip; Humbert, Sarah; Hata, Justin; Tran, Duc

2017-01-01

Objective: Phantom limb pain is a condition frequently experienced after amputation. One treatment for phantom limb pain is traditional mirror therapy, yet some patients do not respond to this intervention, and immersive virtual reality mirror therapy offers some potential advantages. We report the case of a patient with severe phantom limb pain following an upper limb amputation and successful treatment with therapy in a custom virtual reality environment. Methods: An interactive 3-D kitchen environment was developed based on the principles of mirror therapy to allow for control of virtual hands while wearing a motion-tracked, head-mounted virtual reality display. The patient used myoelectric control of a virtual hand as well as motion-tracking control in this setting for five therapy sessions. Pain scale measurements and subjective feedback was elicited at each session. Results: Analysis of the measured pain scales showed statistically significant decreases per session [Visual Analog Scale, Short Form McGill Pain Questionnaire, and Wong-Baker FACES pain scores decreased by 55 percent (p=0.0143), 60 percent (p=0.023), and 90 percent (p=0.0024), respectively]. Significant subjective pain relief persisting between sessions was also reported, as well as marked immersion within the virtual environments. On followup at six weeks, the patient noted continued decrease in phantom limb pain symptoms. Conclusions: Currently available immersive virtual reality technology with myolectric and motion tracking control may represent a possible therapy option for treatment-resistant phantom limb pain.

Immersive Virtual Reality Therapy with Myoelectric Control for Treatment-resistant Phantom Limb Pain: Case Report

PubMed Central

Phelan, Ivan; Ta, Phillip; Humbert, Sarah; Hata, Justin; Tran, Duc

2017-01-01

Objective: Phantom limb pain is a condition frequently experienced after amputation. One treatment for phantom limb pain is traditional mirror therapy, yet some patients do not respond to this intervention, and immersive virtual reality mirror therapy offers some potential advantages. We report the case of a patient with severe phantom limb pain following an upper limb amputation and successful treatment with therapy in a custom virtual reality environment. Methods: An interactive 3-D kitchen environment was developed based on the principles of mirror therapy to allow for control of virtual hands while wearing a motion-tracked, head-mounted virtual reality display. The patient used myoelectric control of a virtual hand as well as motion-tracking control in this setting for five therapy sessions. Pain scale measurements and subjective feedback was elicited at each session. Results: Analysis of the measured pain scales showed statistically significant decreases per session [Visual Analog Scale, Short Form McGill Pain Questionnaire, and Wong-Baker FACES pain scores decreased by 55 percent (p=0.0143), 60 percent (p=0.023), and 90 percent (p=0.0024), respectively]. Significant subjective pain relief persisting between sessions was also reported, as well as marked immersion within the virtual environments. On followup at six weeks, the patient noted continued decrease in phantom limb pain symptoms. Conclusions: Currently available immersive virtual reality technology with myolectric and motion tracking control may represent a possible therapy option for treatment-resistant phantom limb pain. PMID:29616149

CellProfiler Tracer: exploring and validating high-throughput, time-lapse microscopy image data.

PubMed

Bray, Mark-Anthony; Carpenter, Anne E

2015-11-04

Time-lapse analysis of cellular images is an important and growing need in biology. Algorithms for cell tracking are widely available; what researchers have been missing is a single open-source software package to visualize standard tracking output (from software like CellProfiler) in a way that allows convenient assessment of track quality, especially for researchers tuning tracking parameters for high-content time-lapse experiments. This makes quality assessment and algorithm adjustment a substantial challenge, particularly when dealing with hundreds of time-lapse movies collected in a high-throughput manner. We present CellProfiler Tracer, a free and open-source tool that complements the object tracking functionality of the CellProfiler biological image analysis package. Tracer allows multi-parametric morphological data to be visualized on object tracks, providing visualizations that have already been validated within the scientific community for time-lapse experiments, and combining them with simple graph-based measures for highlighting possible tracking artifacts. CellProfiler Tracer is a useful, free tool for inspection and quality control of object tracking data, available from http://www.cellprofiler.org/tracer/.

Real-time Human Activity Recognition

NASA Astrophysics Data System (ADS)

Albukhary, N.; Mustafah, Y. M.

2017-11-01

The traditional Closed-circuit Television (CCTV) system requires human to monitor the CCTV for 24/7 which is inefficient and costly. Therefore, there’s a need for a system which can recognize human activity effectively in real-time. This paper concentrates on recognizing simple activity such as walking, running, sitting, standing and landing by using image processing techniques. Firstly, object detection is done by using background subtraction to detect moving object. Then, object tracking and object classification are constructed so that different person can be differentiated by using feature detection. Geometrical attributes of tracked object, which are centroid and aspect ratio of identified tracked are manipulated so that simple activity can be detected.

Detection and Tracking of Moving Objects with Real-Time Onboard Vision System

NASA Astrophysics Data System (ADS)

Erokhin, D. Y.; Feldman, A. B.; Korepanov, S. E.

2017-05-01

Detection of moving objects in video sequence received from moving video sensor is a one of the most important problem in computer vision. The main purpose of this work is developing set of algorithms, which can detect and track moving objects in real time computer vision system. This set includes three main parts: the algorithm for estimation and compensation of geometric transformations of images, an algorithm for detection of moving objects, an algorithm to tracking of the detected objects and prediction their position. The results can be claimed to create onboard vision systems of aircraft, including those relating to small and unmanned aircraft.

Attentional Signatures of Perception: Multiple Object Tracking Reveals the Automaticity of Contour Interpolation

ERIC Educational Resources Information Center

Keane, Brian P.; Mettler, Everett; Tsoi, Vicky; Kellman, Philip J.

2011-01-01

Multiple object tracking (MOT) is an attentional task wherein observers attempt to track multiple targets among moving distractors. Contour interpolation is a perceptual process that fills-in nonvisible edges on the basis of how surrounding edges (inducers) are spatiotemporally related. In five experiments, we explored the automaticity of…

A complete system for head tracking using motion-based particle filter and randomly perturbed active contour

NASA Astrophysics Data System (ADS)

Bouaynaya, N.; Schonfeld, Dan

2005-03-01

Many real world applications in computer and multimedia such as augmented reality and environmental imaging require an elastic accurate contour around a tracked object. In the first part of the paper we introduce a novel tracking algorithm that combines a motion estimation technique with the Bayesian Importance Sampling framework. We use Adaptive Block Matching (ABM) as the motion estimation technique. We construct the proposal density from the estimated motion vector. The resulting algorithm requires a small number of particles for efficient tracking. The tracking is adaptive to different categories of motion even with a poor a priori knowledge of the system dynamics. Particulary off-line learning is not needed. A parametric representation of the object is used for tracking purposes. In the second part of the paper, we refine the tracking output from a parametric sample to an elastic contour around the object. We use a 1D active contour model based on a dynamic programming scheme to refine the output of the tracker. To improve the convergence of the active contour, we perform the optimization over a set of randomly perturbed initial conditions. Our experiments are applied to head tracking. We report promising tracking results in complex environments.

Object tracking with adaptive HOG detector and adaptive Rao-Blackwellised particle filter

NASA Astrophysics Data System (ADS)

Rosa, Stefano; Paleari, Marco; Ariano, Paolo; Bona, Basilio

2012-01-01

Scenarios for a manned mission to the Moon or Mars call for astronaut teams to be accompanied by semiautonomous robots. A prerequisite for human-robot interaction is the capability of successfully tracking humans and objects in the environment. In this paper we present a system for real-time visual object tracking in 2D images for mobile robotic systems. The proposed algorithm is able to specialize to individual objects and to adapt to substantial changes in illumination and object appearance during tracking. The algorithm is composed by two main blocks: a detector based on Histogram of Oriented Gradient (HOG) descriptors and linear Support Vector Machines (SVM), and a tracker which is implemented by an adaptive Rao-Blackwellised particle filter (RBPF). The SVM is re-trained online on new samples taken from previous predicted positions. We use the effective sample size to decide when the classifier needs to be re-trained. Position hypotheses for the tracked object are the result of a clustering procedure applied on the set of particles. The algorithm has been tested on challenging video sequences presenting strong changes in object appearance, illumination, and occlusion. Experimental tests show that the presented method is able to achieve near real-time performances with a precision of about 7 pixels on standard video sequences of dimensions 320 × 240.

Deterministic object tracking using Gaussian ringlet and directional edge features

NASA Astrophysics Data System (ADS)

Krieger, Evan W.; Sidike, Paheding; Aspiras, Theus; Asari, Vijayan K.

2017-10-01

Challenges currently existing for intensity-based histogram feature tracking methods in wide area motion imagery (WAMI) data include object structural information distortions, background variations, and object scale change. These issues are caused by different pavement or ground types and from changing the sensor or altitude. All of these challenges need to be overcome in order to have a robust object tracker, while attaining a computation time appropriate for real-time processing. To achieve this, we present a novel method, Directional Ringlet Intensity Feature Transform (DRIFT), which employs Kirsch kernel filtering for edge features and a ringlet feature mapping for rotational invariance. The method also includes an automatic scale change component to obtain accurate object boundaries and improvements for lowering computation times. We evaluated the DRIFT algorithm on two challenging WAMI datasets, namely Columbus Large Image Format (CLIF) and Large Area Image Recorder (LAIR), to evaluate its robustness and efficiency. Additional evaluations on general tracking video sequences are performed using the Visual Tracker Benchmark and Visual Object Tracking 2014 databases to demonstrate the algorithms ability with additional challenges in long complex sequences including scale change. Experimental results show that the proposed approach yields competitive results compared to state-of-the-art object tracking methods on the testing datasets.

Real-time tracking of visually attended objects in virtual environments and its application to LOD.

PubMed

Lee, Sungkil; Kim, Gerard Jounghyun; Choi, Seungmoon

2009-01-01

This paper presents a real-time framework for computationally tracking objects visually attended by the user while navigating in interactive virtual environments. In addition to the conventional bottom-up (stimulus-driven) saliency map, the proposed framework uses top-down (goal-directed) contexts inferred from the user's spatial and temporal behaviors, and identifies the most plausibly attended objects among candidates in the object saliency map. The computational framework was implemented using GPU, exhibiting high computational performance adequate for interactive virtual environments. A user experiment was also conducted to evaluate the prediction accuracy of the tracking framework by comparing objects regarded as visually attended by the framework to actual human gaze collected with an eye tracker. The results indicated that the accuracy was in the level well supported by the theory of human cognition for visually identifying single and multiple attentive targets, especially owing to the addition of top-down contextual information. Finally, we demonstrate how the visual attention tracking framework can be applied to managing the level of details in virtual environments, without any hardware for head or eye tracking.

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.

Accurate object tracking system by integrating texture and depth cues

NASA Astrophysics Data System (ADS)

Chen, Ju-Chin; Lin, Yu-Hang

2016-03-01

A robust object tracking system that is invariant to object appearance variations and background clutter is proposed. Multiple instance learning with a boosting algorithm is applied to select discriminant texture information between the object and background data. Additionally, depth information, which is important to distinguish the object from a complicated background, is integrated. We propose two depth-based models that can compensate texture information to cope with both appearance variants and background clutter. Moreover, in order to reduce the risk of drifting problem increased for the textureless depth templates, an update mechanism is proposed to select more precise tracking results to avoid incorrect model updates. In the experiments, the robustness of the proposed system is evaluated and quantitative results are provided for performance analysis. Experimental results show that the proposed system can provide the best success rate and has more accurate tracking results than other well-known algorithms.

Infrared tag and track technique

DOEpatents

Partin, Judy K.; Stone, Mark L.; Slater, John; Davidson, James R.

2007-12-04

A method of covertly tagging an object for later tracking includes providing a material capable of at least one of being applied to the object and being included in the object, which material includes deuterium; and performing at least one of applying the material to the object and including the material in the object in a manner in which in the appearance of the object is not changed, to the naked eye.

Tracking target objects orbiting earth using satellite-based telescopes

DOEpatents

De Vries, Willem H; Olivier, Scot S; Pertica, Alexander J

2014-10-14

A system for tracking objects that are in earth orbit via a constellation or network of satellites having imaging devices is provided. An object tracking system includes a ground controller and, for each satellite in the constellation, an onboard controller. The ground controller receives ephemeris information for a target object and directs that ephemeris information be transmitted to the satellites. Each onboard controller receives ephemeris information for a target object, collects images of the target object based on the expected location of the target object at an expected time, identifies actual locations of the target object from the collected images, and identifies a next expected location at a next expected time based on the identified actual locations of the target object. The onboard controller processes the collected image to identify the actual location of the target object and transmits the actual location information to the ground controller.

Object Persistence Enhances Spatial Navigation: A Case Study in Smartphone Vision Science.

PubMed

Liverence, Brandon M; Scholl, Brian J

2015-07-01

Violations of spatiotemporal continuity disrupt performance in many tasks involving attention and working memory, but experiments on this topic have been limited to the study of moment-by-moment on-line perception, typically assessed by passive monitoring tasks. We tested whether persisting object representations also serve as underlying units of longer-term memory and active spatial navigation, using a novel paradigm inspired by the visual interfaces common to many smartphones. Participants used key presses to navigate through simple visual environments consisting of grids of icons (depicting real-world objects), only one of which was visible at a time through a static virtual window. Participants found target icons faster when navigation involved persistence cues (via sliding animations) than when persistence was disrupted (e.g., via temporally matched fading animations), with all transitions inspired by smartphone interfaces. Moreover, this difference occurred even after explicit memorization of the relevant information, which demonstrates that object persistence enhances spatial navigation in an automatic and irresistible fashion. © The Author(s) 2015.

A novel vehicle tracking algorithm based on mean shift and active contour model in complex environment

NASA Astrophysics Data System (ADS)

Cai, Lei; Wang, Lin; Li, Bo; Zhang, Libao; Lv, Wen

2017-06-01

Vehicle tracking technology is currently one of the most active research topics in machine vision. It is an important part of intelligent transportation system. However, in theory and technology, it still faces many challenges including real-time and robustness. In video surveillance, the targets need to be detected in real-time and to be calculated accurate position for judging the motives. The contents of video sequence images and the target motion are complex, so the objects can't be expressed by a unified mathematical model. Object-tracking is defined as locating the interest moving target in each frame of a piece of video. The current tracking technology can achieve reliable results in simple environment over the target with easy identified characteristics. However, in more complex environment, it is easy to lose the target because of the mismatch between the target appearance and its dynamic model. Moreover, the target usually has a complex shape, but the tradition target tracking algorithm usually represents the tracking results by simple geometric such as rectangle or circle, so it cannot provide accurate information for the subsequent upper application. This paper combines a traditional object-tracking technology, Mean-Shift algorithm, with a kind of image segmentation algorithm, Active-Contour model, to get the outlines of objects while the tracking process and automatically handle topology changes. Meanwhile, the outline information is used to aid tracking algorithm to improve it.

Moving object detection and tracking in videos through turbulent medium

NASA Astrophysics Data System (ADS)

Halder, Kalyan Kumar; Tahtali, Murat; Anavatti, Sreenatha G.

2016-06-01

This paper addresses the problem of identifying and tracking moving objects in a video sequence having a time-varying background. This is a fundamental task in many computer vision applications, though a very challenging one because of turbulence that causes blurring and spatiotemporal movements of the background images. Our proposed approach involves two major steps. First, a moving object detection algorithm that deals with the detection of real motions by separating the turbulence-induced motions using a two-level thresholding technique is used. In the second step, a feature-based generalized regression neural network is applied to track the detected objects throughout the frames in the video sequence. The proposed approach uses the centroid and area features of the moving objects and creates the reference regions instantly by selecting the objects within a circle. Simulation experiments are carried out on several turbulence-degraded video sequences and comparisons with an earlier method confirms that the proposed approach provides a more effective tracking of the targets.

Photometric Data from Non-Resolved Objects for Space Object Characterization and Improved Atmospheric Modeling

NASA Astrophysics Data System (ADS)

Linares, R.; Palmer, D.; Thompson, D.; Koller, J.

2013-09-01

Recent events in space, including the collision of Russia's Cosmos 2251 satellite with Iridium 33 and China's Feng Yun 1C anti-satellite demonstration, have stressed the capabilities of Space Surveillance Network (SSN) and its ability to provide accurate and actionable impact probability estimates. The SSN network has the unique challenge of tracking more than 18,000 resident space objects (RSOs) and providing critical collision avoidance warnings to military, NASA, and commercial systems. However, due to the large number of RSOs and the limited number of sensors available to track them, it is impossible to maintain persistent surveillance. Observation gaps result in large propagation intervals between measurements and close approaches. Coupled with nonlinear RSO dynamics this results in difficulty in modeling the probability distribution functions (pdfs) of the RSO. In particular low-Earth orbiting (LEO) satellites are heavily influenced by atmospheric drag, which is very difficult to model accurately. A number of atmospheric models exist which can be classified as either empirical or physics-based models. The current Air Force standard is the High Accuracy Satellite Drag Model (HASDM), which is an empirical model based on observation of calibration satellites. These satellite observations are used to determine model parameters based on their orbit determination solutions. Atmospheric orbits are perturbed by a number of factors including drag coefficient, attitude, and shape of the space object. The satellites used for the HASDM model calibration process are chosen because of their relatively simple shapes, to minimize errors introduced due to shape miss-modeling. Under this requirement the number of calibration satellites that can be used for calibrating the atmospheric models is limited. Los Alamos National Laboratory (LANL) has established a research effort, called IMPACT (Integrated Modeling of Perturbations in Atmospheres for Conjunction Tracking), to improve impact assessment via improved physics-based modeling. As part of this effort calibration satellite observations are used to dynamically calibrate the physics-based model and to improve its forecasting capability. The observations are collected from a variety of sources, including from LANL's own Raven-class optical telescope. This system collects both astrometric and photometric data on space objects. The photometric data will be used to estimate the space objects' attitude and shape. Non-resolved photometric data have been studied by many as a mechanism for space object characterization. Photometry is the measurement of an object's flux or apparent brightness measured over a wavelength band. The temporal variation of photometric measurements is referred to as photometric signature. The photometric optical signature of an object contains information about shape, attitude, size and material composition. This work focuses on the processing of the data collected with LANL's telescope in an effort to use photometric data to expand the number of space objects that can be used as calibration satellites. An Unscented Kalman filter is used to estimate the attitude and angular velocity of the space object; both real data and simulated data scenarios are shown. A number of inactive space objects are used for the real data examples and good estimation results are shown.

Hidden Markov model tracking of continuous gravitational waves from young supernova remnants

NASA Astrophysics Data System (ADS)

Sun, L.; Melatos, A.; Suvorova, S.; Moran, W.; Evans, R. J.

2018-02-01

Searches for persistent gravitational radiation from nonpulsating neutron stars in young supernova remnants are computationally challenging because of rapid stellar braking. We describe a practical, efficient, semicoherent search based on a hidden Markov model tracking scheme, solved by the Viterbi algorithm, combined with a maximum likelihood matched filter, the F statistic. The scheme is well suited to analyzing data from advanced detectors like the Advanced Laser Interferometer Gravitational Wave Observatory (Advanced LIGO). It can track rapid phase evolution from secular stellar braking and stochastic timing noise torques simultaneously without searching second- and higher-order derivatives of the signal frequency, providing an economical alternative to stack-slide-based semicoherent algorithms. One implementation tracks the signal frequency alone. A second implementation tracks the signal frequency and its first time derivative. It improves the sensitivity by a factor of a few upon the first implementation, but the cost increases by 2 to 3 orders of magnitude.

Why do people appear not to extrapolate trajectories during multiple object tracking? A computational investigation

PubMed Central

Zhong, Sheng-hua; Ma, Zheng; Wilson, Colin; Liu, Yan; Flombaum, Jonathan I

2014-01-01

Intuitively, extrapolating object trajectories should make visual tracking more accurate. This has proven to be true in many contexts that involve tracking a single item. But surprisingly, when tracking multiple identical items in what is known as “multiple object tracking,” observers often appear to ignore direction of motion, relying instead on basic spatial memory. We investigated potential reasons for this behavior through probabilistic models that were endowed with perceptual limitations in the range of typical human observers, including noisy spatial perception. When we compared a model that weights its extrapolations relative to other sources of information about object position, and one that does not extrapolate at all, we found no reliable difference in performance, belying the intuition that extrapolation always benefits tracking. In follow-up experiments we found this to be true for a variety of models that weight observations and predictions in different ways; in some cases we even observed worse performance for models that use extrapolations compared to a model that does not at all. Ultimately, the best performing models either did not extrapolate, or extrapolated very conservatively, relying heavily on observations. These results illustrate the difficulty and attendant hazards of using noisy inputs to extrapolate the trajectories of multiple objects simultaneously in situations with targets and featurally confusable nontargets. PMID:25311300

Persistence of the Intuitive Conception of Living Things in Adolescence

NASA Astrophysics Data System (ADS)

Babai, Reuven; Sekal, Rachel; Stavy, Ruth

2010-02-01

This study investigated whether intuitive, naive conceptions of "living things" based on objects' mobility (movement = alive) persist into adolescence and affect 10th graders' accuracy of responses and reaction times during object classification. Most of the 58 students classified the test objects correctly as living/nonliving, yet they demonstrated significantly longer reaction times for classifying plants compared to animals and for classifying dynamic objects compared to static inanimate objects. Findings indicated that, despite prior learning in biology, the intuitive conception of living things persists up to age 15-16 years, affecting related reasoning processes. Consideration of these findings may help educators in their decisions about the nature of examples they use in their classrooms.

Connection-based and object-based grouping in multiple-object tracking: A developmental study.

PubMed

Van der Hallen, Ruth; Reusens, Julie; Evers, Kris; de-Wit, Lee; Wagemans, Johan

2018-03-30

Developmental research on Gestalt laws has previously revealed that, even as young as infancy, we are bound to group visual elements into unitary structures in accordance with a variety of organizational principles. Here, we focus on the developmental trajectory of both connection-based and object-based grouping, and investigate their impact on object formation in participants, aged 9-21 years old (N = 113), using a multiple-object tracking paradigm. Results reveal a main effect of both age and grouping type, indicating that 9- to 21-year-olds are sensitive to both connection-based and object-based grouping interference, and tracking ability increases with age. In addition to its importance for typical development, these results provide an informative baseline to understand clinical aberrations in this regard. Statement of contribution What is already known on this subject? The origin of the Gestalt principles is still an ongoing debate: Are they innate, learned over time, or both? Developmental research has revealed how each Gestalt principle has its own trajectory and unique relationship to visual experience. Both connectedness and object-based grouping play an important role in object formation during childhood. What does this study add? The study identifies how sensitivity to connectedness and object-based grouping evolves in individuals, aged 9-21 years old. Using multiple-object tracking, results reveal that the ability to track multiple objects increases with age. These results provide an informative baseline to understand clinical aberrations in different types of grouping. © 2018 The Authors. British Journal of Developmental Psychology published by John Wiley & Sons Ltd on behalf of British Psychological Society.

Eye Movements during Multiple Object Tracking: Where Do Participants Look?

ERIC Educational Resources Information Center

Fehd, Hilda M.; Seiffert, Adriane E.

2008-01-01

Similar to the eye movements you might make when viewing a sports game, this experiment investigated where participants tend to look while keeping track of multiple objects. While eye movements were recorded, participants tracked either 1 or 3 of 8 red dots that moved randomly within a square box on a black background. Results indicated that…

Another Way of Tracking Moving Objects Using Short Video Clips

ERIC Educational Resources Information Center

Vera, Francisco; Romanque, Cristian

2009-01-01

Physics teachers have long employed video clips to study moving objects in their classrooms and instructional labs. A number of approaches exist, both free and commercial, for tracking the coordinates of a point using video. The main characteristics of the method described in this paper are: it is simple to use; coordinates can be tracked using…

Single and Multiple Object Tracking Using a Multi-Feature Joint Sparse Representation.

PubMed

Hu, Weiming; Li, Wei; Zhang, Xiaoqin; Maybank, Stephen

2015-04-01

In this paper, we propose a tracking algorithm based on a multi-feature joint sparse representation. The templates for the sparse representation can include pixel values, textures, and edges. In the multi-feature joint optimization, noise or occlusion is dealt with using a set of trivial templates. A sparse weight constraint is introduced to dynamically select the relevant templates from the full set of templates. A variance ratio measure is adopted to adaptively adjust the weights of different features. The multi-feature template set is updated adaptively. We further propose an algorithm for tracking multi-objects with occlusion handling based on the multi-feature joint sparse reconstruction. The observation model based on sparse reconstruction automatically focuses on the visible parts of an occluded object by using the information in the trivial templates. The multi-object tracking is simplified into a joint Bayesian inference. The experimental results show the superiority of our algorithm over several state-of-the-art tracking algorithms.

MetaTracker: integration and abstraction of 3D motion tracking data from multiple hardware systems

NASA Astrophysics Data System (ADS)

Kopecky, Ken; Winer, Eliot

2014-06-01

Motion tracking has long been one of the primary challenges in mixed reality (MR), augmented reality (AR), and virtual reality (VR). Military and defense training can provide particularly difficult challenges for motion tracking, such as in the case of Military Operations in Urban Terrain (MOUT) and other dismounted, close quarters simulations. These simulations can take place across multiple rooms, with many fast-moving objects that need to be tracked with a high degree of accuracy and low latency. Many tracking technologies exist, such as optical, inertial, ultrasonic, and magnetic. Some tracking systems even combine these technologies to complement each other. However, there are no systems that provide a high-resolution, flexible, wide-area solution that is resistant to occlusion. While frameworks exist that simplify the use of tracking systems and other input devices, none allow data from multiple tracking systems to be combined, as if from a single system. In this paper, we introduce a method for compensating for the weaknesses of individual tracking systems by combining data from multiple sources and presenting it as a single tracking system. Individual tracked objects are identified by name, and their data is provided to simulation applications through a server program. This allows tracked objects to transition seamlessly from the area of one tracking system to another. Furthermore, it abstracts away the individual drivers, APIs, and data formats for each system, providing a simplified API that can be used to receive data from any of the available tracking systems. Finally, when single-piece tracking systems are used, those systems can themselves be tracked, allowing for real-time adjustment of the trackable area. This allows simulation operators to leverage limited resources in more effective ways, improving the quality of training.

Persistence of the Intuitive Conception of Living Things in Adolescence

ERIC Educational Resources Information Center

Babai, Reuven; Sekal, Rachel; Stavy, Ruth

2010-01-01

This study investigated whether intuitive, naive conceptions of "living things" based on objects' mobility (movement = alive) persist into adolescence and affect 10th graders' accuracy of responses and reaction times during object classification. Most of the 58 students classified the test objects correctly as living/nonliving, yet they…

Tracking with occlusions via graph cuts.

PubMed

Papadakis, Nicolas; Bugeau, Aurélie

2011-01-01

This work presents a new method for tracking and segmenting along time-interacting objects within an image sequence. One major contribution of the paper is the formalization of the notion of visible and occluded parts. For each object, we aim at tracking these two parts. Assuming that the velocity of each object is driven by a dynamical law, predictions can be used to guide the successive estimations. Separating these predicted areas into good and bad parts with respect to the final segmentation and representing the objects with their visible and occluded parts permit handling partial and complete occlusions. To achieve this tracking, a label is assigned to each object and an energy function representing the multilabel problem is minimized via a graph cuts optimization. This energy contains terms based on image intensities which enable segmenting and regularizing the visible parts of the objects. It also includes terms dedicated to the management of the occluded and disappearing areas, which are defined on the areas of prediction of the objects. The results on several challenging sequences prove the strength of the proposed approach.

Robust Feedback Zoom Tracking for Digital Video Surveillance

PubMed Central

Zou, Tengyue; Tang, Xiaoqi; Song, Bao; Wang, Jin; Chen, Jihong

2012-01-01

Zoom tracking is an important function in video surveillance, particularly in traffic management and security monitoring. It involves keeping an object of interest in focus during the zoom operation. Zoom tracking is typically achieved by moving the zoom and focus motors in lenses following the so-called “trace curve”, which shows the in-focus motor positions versus the zoom motor positions for a specific object distance. The main task of a zoom tracking approach is to accurately estimate the trace curve for the specified object. Because a proportional integral derivative (PID) controller has historically been considered to be the best controller in the absence of knowledge of the underlying process and its high-quality performance in motor control, in this paper, we propose a novel feedback zoom tracking (FZT) approach based on the geometric trace curve estimation and PID feedback controller. The performance of this approach is compared with existing zoom tracking methods in digital video surveillance. The real-time implementation results obtained on an actual digital video platform indicate that the developed FZT approach not only solves the traditional one-to-many mapping problem without pre-training but also improves the robustness for tracking moving or switching objects which is the key challenge in video surveillance. PMID:22969388

Striations and preferred eddy tracks triggered by topographic steering of the background flow in the eastern South Pacific

NASA Astrophysics Data System (ADS)

Belmadani, Ali; Concha, Emilio; Donoso, David; Chaigneau, Alexis; Colas, François; Maximenko, Nikolai; Di Lorenzo, Emanuele

2017-04-01

In recent years, persistent quasi-zonal jets or striations have been ubiquitously detected in the world ocean using satellite and in situ data as well as numerical models. This study aims at determining the role of mesoscale eddies in the generation and persistence of striations off Chile in the eastern South Pacific. A 50 year climatological integration of an eddy-resolving numerical ocean model is used to assess the long-term persistence of striations. Automated eddy tracking algorithms are applied to the model outputs and altimetry data. Results reveal that striations coincide with both polarized eddy tracks and the offshore formation of new eddies in the subtropical front and coastal transition zone, without any significant decay over time that discards random eddies as a primary driver of the striations. Localized patches of vortex stretching and relative vorticity advection, alternating meridionally near the eastern edge of the subtropical front, are associated with topographic steering of the background flow in the presence of steep topography, and with baroclinically and barotropically unstable meridional flow. These sinks and sources of vorticity are suggested to generate the banded structure further west, consistently with a β-plume mechanism. On the other hand, zonal/meridional eddy advection of relative vorticity and the associated Reynolds stress covariance are consistent with eddy deformation over rough topography and participate to sustain the striations in the far field. Shear instability of mean striations is proposed to feedback onto the eddy field, acting to maintain the subtropical front eddy streets and thus the striations.

Flying over an infected landscape: Distribution of highly pathogenic avian influenza H5N1 risk in South Asia and satellite tracking of wild waterfowl

USGS Publications Warehouse

Gilbert, Marius; Newman, Scott H.; Takekawa, John Y.; Loth, Leo; Biradar, Chandrashekhar; Prosser, Diann J.; Balachandran, Sivananinthaperumal; Rao, Mandava Venkata Subba; Mundkur, Taej; Yan, Baoping; Xing, Zhi; Hou, Yuansheng; Batbayar, Nyambayar; Tseveenmayadag, Natsagdorj; Hogerwerf, Lenny; Slingenbergh, Jan; Xiao, Xiangming

2010-01-01

Highly pathogenic avian influenza (HPAI) H5N1 virus persists in Asia, posing a threat to poultry, wild birds, and humans. Previous work in Southeast Asia demonstrated that HPAI H5N1 risk is related to domestic ducks and people. Other studies discussed the role of migratory birds in the long distance spread of HPAI H5N1. However, the interplay between local persistence and long-distance dispersal has never been studied. We expand previous geospatial risk analysis to include South and Southeast Asia, and integrate the analysis with migration data of satellite-tracked wild waterfowl along the Central Asia flyway. We find that the population of domestic duck is the main factor delineating areas at risk of HPAI H5N1 spread in domestic poultry in South Asia, and that other risk factors, such as human population and chicken density, are associated with HPAI H5N1 risk within those areas. We also find that satellite tracked birds (Ruddy Shelduck and two Bar-headed Geese) reveal a direct spatio-temporal link between the HPAI H5N1 hot-spots identified in India and Bangladesh through our risk model, and the wild bird outbreaks in May,June,July 2009 in China(Qinghai Lake), Mongolia, and Russia. This suggests that the continental-scale dynamics of HPAI H5N1 are structured as a number of persistence areas delineated by domestic ducks, connected by rare transmission through migratory waterfowl.

Normal aging delays and compromises early multifocal visual attention during object tracking.

PubMed

Störmer, Viola S; Li, Shu-Chen; Heekeren, Hauke R; Lindenberger, Ulman

2013-02-01

Declines in selective attention are one of the sources contributing to age-related impairments in a broad range of cognitive functions. Most previous research on mechanisms underlying older adults' selection deficits has studied the deployment of visual attention to static objects and features. Here we investigate neural correlates of age-related differences in spatial attention to multiple objects as they move. We used a multiple object tracking task, in which younger and older adults were asked to keep track of moving target objects that moved randomly in the visual field among irrelevant distractor objects. By recording the brain's electrophysiological responses during the tracking period, we were able to delineate neural processing for targets and distractors at early stages of visual processing (~100-300 msec). Older adults showed less selective attentional modulation in the early phase of the visual P1 component (100-125 msec) than younger adults, indicating that early selection is compromised in old age. However, with a 25-msec delay relative to younger adults, older adults showed distinct processing of targets (125-150 msec), that is, a delayed yet intact attentional modulation. The magnitude of this delayed attentional modulation was related to tracking performance in older adults. The amplitude of the N1 component (175-210 msec) was smaller in older adults than in younger adults, and the target amplification effect of this component was also smaller in older relative to younger adults. Overall, these results indicate that normal aging affects the efficiency and timing of early visual processing during multiple object tracking.

Real-time edge tracking using a tactile sensor

NASA Technical Reports Server (NTRS)

Berger, Alan D.; Volpe, Richard; Khosla, Pradeep K.

1989-01-01

Object recognition through the use of input from multiple sensors is an important aspect of an autonomous manipulation system. In tactile object recognition, it is necessary to determine the location and orientation of object edges and surfaces. A controller is proposed that utilizes a tactile sensor in the feedback loop of a manipulator to track along edges. In the control system, the data from the tactile sensor is first processed to find edges. The parameters of these edges are then used to generate a control signal to a hybrid controller. Theory is presented for tactile edge detection and an edge tracking controller. In addition, experimental verification of the edge tracking controller is presented.

Detecting multiple moving objects in crowded environments with coherent motion regions

DOEpatents

Cheriyadat, Anil M.; Radke, Richard J.

2013-06-11

Coherent motion regions extend in time as well as space, enforcing consistency in detected objects over long time periods and making the algorithm robust to noisy or short point tracks. As a result of enforcing the constraint that selected coherent motion regions contain disjoint sets of tracks defined in a three-dimensional space including a time dimension. An algorithm operates directly on raw, unconditioned low-level feature point tracks, and minimizes a global measure of the coherent motion regions. At least one discrete moving object is identified in a time series of video images based on the trajectory similarity factors, which is a measure of a maximum distance between a pair of feature point tracks.

Real-time model-based vision system for object acquisition and tracking

NASA Technical Reports Server (NTRS)

Wilcox, Brian; Gennery, Donald B.; Bon, Bruce; Litwin, Todd

1987-01-01

A machine vision system is described which is designed to acquire and track polyhedral objects moving and rotating in space by means of two or more cameras, programmable image-processing hardware, and a general-purpose computer for high-level functions. The image-processing hardware is capable of performing a large variety of operations on images and on image-like arrays of data. Acquisition utilizes image locations and velocities of the features extracted by the image-processing hardware to determine the three-dimensional position, orientation, velocity, and angular velocity of the object. Tracking correlates edges detected in the current image with edge locations predicted from an internal model of the object and its motion, continually updating velocity information to predict where edges should appear in future frames. With some 10 frames processed per second, real-time tracking is possible.

Color image processing and object tracking workstation

NASA Technical Reports Server (NTRS)

Klimek, Robert B.; Paulick, Michael J.

1992-01-01

A system is described for automatic and semiautomatic tracking of objects on film or video tape which was developed to meet the needs of the microgravity combustion and fluid science experiments at NASA Lewis. The system consists of individual hardware parts working under computer control to achieve a high degree of automation. The most important hardware parts include 16 mm film projector, a lens system, a video camera, an S-VHS tapedeck, a frame grabber, and some storage and output devices. Both the projector and tapedeck have a computer interface enabling remote control. Tracking software was developed to control the overall operation. In the automatic mode, the main tracking program controls the projector or the tapedeck frame incrementation, grabs a frame, processes it, locates the edge of the objects being tracked, and stores the coordinates in a file. This process is performed repeatedly until the last frame is reached. Three representative applications are described. These applications represent typical uses and include tracking the propagation of a flame front, tracking the movement of a liquid-gas interface with extremely poor visibility, and characterizing a diffusion flame according to color and shape.

Transfer of Learning between Hemifields in Multiple Object Tracking: Memory Reduces Constraints of Attention

PubMed Central

Lapierre, Mark; Howe, Piers D. L.; Cropper, Simon J.

2013-01-01

Many tasks involve tracking multiple moving objects, or stimuli. Some require that individuals adapt to changing or unfamiliar conditions to be able to track well. This study explores processes involved in such adaptation through an investigation of the interaction of attention and memory during tracking. Previous research has shown that during tracking, attention operates independently to some degree in the left and right visual hemifields, due to putative anatomical constraints. It has been suggested that the degree of independence is related to the relative dominance of processes of attention versus processes of memory. Here we show that when individuals are trained to track a unique pattern of movement in one hemifield, that learning can be transferred to the opposite hemifield, without any evidence of hemifield independence. However, learning is not influenced by an explicit strategy of memorisation of brief periods of recognisable movement. The findings lend support to a role for implicit memory in overcoming putative anatomical constraints on the dynamic, distributed spatial allocation of attention involved in tracking multiple objects. PMID:24349555

Persistent insomnia: the role of objective short sleep duration and mental health.

PubMed

Vgontzas, Alexandros N; Fernandez-Mendoza, Julio; Bixler, Edward O; Singareddy, Ravi; Shaffer, Michele L; Calhoun, Susan L; Liao, Duanping; Basta, Maria; Chrousos, George P

2012-01-01

Few population-based, longitudinal studies have examined risk factors for persistent insomnia, and the results are inconsistent. Furthermore, none of these studies have examined the role of polysomnographic (PSG) variables such as sleep duration or sleep apnea on the persistence of insomnia. Representative longitudinal study. Sleep laboratory. From a random, general population sample of 1741 individuals of the adult Penn State Cohort, 1395 were followed-up after 7.5 years. Individuals underwent one-night PSG and full medical evaluation at baseline and a telephone interview at follow-up. PSG sleep duration was analyzed as a continuous variable and as a categorical variable: < 6 h sleep (short sleep duration) and ≥ 6 h sleep (longer sleep duration). The rates of insomnia persistence, partial remission, and full remission were 44.0%, 30.0%, and 26.0%, respectively. Objective short sleep duration significantly increased the odds of persistent insomnia as compared to normal sleep (OR = 3.19) and to fully remitted insomnia (OR = 4.92). Mental health problems at baseline were strongly associated with persistent insomnia as compared to normal sleep (OR = 9.67) and to a lesser degree compared to fully remitted insomnia (OR = 3.68). Smoking, caffeine, and alcohol consumption and sleep apnea did not predict persistent insomnia. Objective short sleep duration and mental health problems are the strongest predictors of persistent insomnia. These data further support the validity and clinical utility of objective short sleep duration as a novel marker of the biological severity of insomnia.

Exhausting Attentional Tracking Resources with a Single Fast-Moving Object

ERIC Educational Resources Information Center

Holcombe, Alex O.; Chen, Wei-Ying

2012-01-01

Driving on a busy road, eluding a group of predators, or playing a team sport involves keeping track of multiple moving objects. In typical laboratory tasks, the number of visual targets that humans can track is about four. Three types of theories have been advanced to explain this limit. The fixed-limit theory posits a set number of attentional…

Real-time multiple objects tracking on Raspberry-Pi-based smart embedded camera

NASA Astrophysics Data System (ADS)

Dziri, Aziz; Duranton, Marc; Chapuis, Roland

2016-07-01

Multiple-object tracking constitutes a major step in several computer vision applications, such as surveillance, advanced driver assistance systems, and automatic traffic monitoring. Because of the number of cameras used to cover a large area, these applications are constrained by the cost of each node, the power consumption, the robustness of the tracking, the processing time, and the ease of deployment of the system. To meet these challenges, the use of low-power and low-cost embedded vision platforms to achieve reliable tracking becomes essential in networks of cameras. We propose a tracking pipeline that is designed for fixed smart cameras and which can handle occlusions between objects. We show that the proposed pipeline reaches real-time processing on a low-cost embedded smart camera composed of a Raspberry-Pi board and a RaspiCam camera. The tracking quality and the processing speed obtained with the proposed pipeline are evaluated on publicly available datasets and compared to the state-of-the-art methods.

Tracking-Learning-Detection.

PubMed

Kalal, Zdenek; Mikolajczyk, Krystian; Matas, Jiri

2012-07-01

This paper investigates long-term tracking of unknown objects in a video stream. The object is defined by its location and extent in a single frame. In every frame that follows, the task is to determine the object's location and extent or indicate that the object is not present. We propose a novel tracking framework (TLD) that explicitly decomposes the long-term tracking task into tracking, learning, and detection. The tracker follows the object from frame to frame. The detector localizes all appearances that have been observed so far and corrects the tracker if necessary. The learning estimates the detector's errors and updates it to avoid these errors in the future. We study how to identify the detector's errors and learn from them. We develop a novel learning method (P-N learning) which estimates the errors by a pair of "experts": (1) P-expert estimates missed detections, and (2) N-expert estimates false alarms. The learning process is modeled as a discrete dynamical system and the conditions under which the learning guarantees improvement are found. We describe our real-time implementation of the TLD framework and the P-N learning. We carry out an extensive quantitative evaluation which shows a significant improvement over state-of-the-art approaches.

Persistence and evolution of allergen-specific IgE repertoires during subcutaneous specific immunotherapy

PubMed Central

Levin, Mattias; King, Jasmine J.; Glanville, Jacob; Jackson, Katherine J. L.; Looney, Timothy J.; Hoh, Ramona A.; Mari, Adriano; Andersson, Morgan; Greiff, Lennart; Fire, Andrew Z.; Boyd, Scott D.; Ohlin, Mats

2016-01-01

Background Specific immunotherapy (SIT) is the only treatment with proven long-term curative potential in allergic disease. Allergen-specific IgE is the causative agent of allergic disease, and antibodies contribute to SIT, but the effects of SIT on aeroallergen-specific B cell repertoires are not well understood. Objective To characterize the IgE sequences expressed by allergen-specific B cells, and track the fate of these B cell clones during SIT. Methods We have used high-throughput antibody gene sequencing and identification of allergen-specific IgE using combinatorial antibody fragment library technology to analyze immunoglobulin repertoires of blood and nasal mucosa of aeroallergen-sensitized individuals before and during the first year of subcutaneous SIT. Results Of 52 distinct allergen-specific IgE heavy chains from eight allergic donors, 37 were also detected by high-throughput antibody gene sequencing of blood, nasal mucosa, or both sample types. The allergen-specific clones had increased persistence, higher likelihood of belonging to clones expressing other switched isotypes, and possibly larger clone size than the rest of the IgE repertoire. Clone members in nasal tissue showed close mutational relationships. Conclusion Combining functional binding studies, deep antibody repertoire sequencing, and information on clinical outcomes in larger studies may in the future aid assessment of SIT mechanisms and efficacy. PMID:26559321

Multi-object tracking of human spermatozoa

NASA Astrophysics Data System (ADS)

Sørensen, Lauge; Østergaard, Jakob; Johansen, Peter; de Bruijne, Marleen

2008-03-01

We propose a system for tracking of human spermatozoa in phase-contrast microscopy image sequences. One of the main aims of a computer-aided sperm analysis (CASA) system is to automatically assess sperm quality based on spermatozoa motility variables. In our case, the problem of assessing sperm quality is cast as a multi-object tracking problem, where the objects being tracked are the spermatozoa. The system combines a particle filter and Kalman filters for robust motion estimation of the spermatozoa tracks. Further, the combinatorial aspect of assigning observations to labels in the particle filter is formulated as a linear assignment problem solved using the Hungarian algorithm on a rectangular cost matrix, making the algorithm capable of handling missing or spurious observations. The costs are calculated using hidden Markov models that express the plausibility of an observation being the next position in the track history of the particle labels. Observations are extracted using a scale-space blob detector utilizing the fact that the spermatozoa appear as bright blobs in a phase-contrast microscope. The output of the system is the complete motion track of each of the spermatozoa. Based on these tracks, different CASA motility variables can be computed, for example curvilinear velocity or straight-line velocity. The performance of the system is tested on three different phase-contrast image sequences of varying complexity, both by visual inspection of the estimated spermatozoa tracks and by measuring the mean squared error (MSE) between the estimated spermatozoa tracks and manually annotated tracks, showing good agreement.

Tracking and people counting using Particle Filter Method

NASA Astrophysics Data System (ADS)

Sulistyaningrum, D. R.; Setiyono, B.; Rizky, M. S.

2018-03-01

In recent years, technology has developed quite rapidly, especially in the field of object tracking. Moreover, if the object under study is a person and the number of people a lot. The purpose of this research is to apply Particle Filter method for tracking and counting people in certain area. Tracking people will be rather difficult if there are some obstacles, one of which is occlusion. The stages of tracking and people counting scheme in this study include pre-processing, segmentation using Gaussian Mixture Model (GMM), tracking using particle filter, and counting based on centroid. The Particle Filter method uses the estimated motion included in the model used. The test results show that the tracking and people counting can be done well with an average accuracy of 89.33% and 77.33% respectively from six videos test data. In the process of tracking people, the results are good if there is partial occlusion and no occlusion

Real-Time Visual Tracking through Fusion Features

PubMed Central

Ruan, Yang; Wei, Zhenzhong

2016-01-01

Due to their high-speed, correlation filters for object tracking have begun to receive increasing attention. Traditional object trackers based on correlation filters typically use a single type of feature. In this paper, we attempt to integrate multiple feature types to improve the performance, and we propose a new DD-HOG fusion feature that consists of discriminative descriptors (DDs) and histograms of oriented gradients (HOG). However, fusion features as multi-vector descriptors cannot be directly used in prior correlation filters. To overcome this difficulty, we propose a multi-vector correlation filter (MVCF) that can directly convolve with a multi-vector descriptor to obtain a single-channel response that indicates the location of an object. Experiments on the CVPR2013 tracking benchmark with the evaluation of state-of-the-art trackers show the effectiveness and speed of the proposed method. Moreover, we show that our MVCF tracker, which uses the DD-HOG descriptor, outperforms the structure-preserving object tracker (SPOT) in multi-object tracking because of its high-speed and ability to address heavy occlusion. PMID:27347951

Low Earth Orbit Satellite Tracking Telescope Network: Collaborative Optical Tracking for Enhanced Space Situational Awareness

DTIC Science & Technology

2015-03-27

i.e., temporarily focusing on one object instead of wide area survey) or SOI collection on high interest objects (e.g., unidentified objects ...The Air Force Institute of Technology has spent the last seven years conducting research on orbit identification and object characterization of space... objects through the use of commercial-off-the-shelf hardware systems controlled via custom software routines, referred to simply as TeleTrak. Year

Sensor and Processing COI (Briefing Charts)

DTIC Science & Technology

2014-05-27

Persistent Surveillance • Target Detection, Recognition & ID at Standoff Ranges • Force/Platform/Sensor Protection • Target Tracking • Early Warning • BDA ...inhomogeneous and complex media is also a foundational challenge for President’s BRAIN initiative. 38 Explore Advanced Sensors And Processing

Robot Grasps Rotating Object

NASA Technical Reports Server (NTRS)

Wilcox, Brian H.; Tso, Kam S.; Litwin, Todd E.; Hayati, Samad A.; Bon, Bruce B.

1991-01-01

Experimental robotic system semiautomatically grasps rotating object, stops rotation, and pulls object to rest in fixture. Based on combination of advanced techniques for sensing and control, constructed to test concepts for robotic recapture of spinning artificial satellites. Potential terrestrial applications for technology developed with help of system includes tracking and grasping of industrial parts on conveyor belts, tracking of vehicles and animals, and soft grasping of moving objects in general.

The role of visual attention in multiple object tracking: evidence from ERPs.

PubMed

Doran, Matthew M; Hoffman, James E

2010-01-01

We examined the role of visual attention in the multiple object tracking (MOT) task by measuring the amplitude of the N1 component of the event-related potential (ERP) to probe flashes presented on targets, distractors, or empty background areas. We found evidence that visual attention enhances targets and suppresses distractors (Experiment 1 & 3). However, we also found that when tracking load was light (two targets and two distractors), accurate tracking could be carried out without any apparent contribution from the visual attention system (Experiment 2). Our results suggest that attentional selection during MOT is flexibly determined by task demands as well as tracking load and that visual attention may not always be necessary for accurate tracking.

Autonomous space target recognition and tracking approach using star sensors based on a Kalman filter.

PubMed

Ye, Tao; Zhou, Fuqiang

2015-04-10

When imaged by detectors, space targets (including satellites and debris) and background stars have similar point-spread functions, and both objects appear to change as detectors track targets. Therefore, traditional tracking methods cannot separate targets from stars and cannot directly recognize targets in 2D images. Consequently, we propose an autonomous space target recognition and tracking approach using a star sensor technique and a Kalman filter (KF). A two-step method for subpixel-scale detection of star objects (including stars and targets) is developed, and the combination of the star sensor technique and a KF is used to track targets. The experimental results show that the proposed method is adequate for autonomously recognizing and tracking space targets.

Characterization of Inactive Rocket Bodies Via Non-Resolved Photometric Data

NASA Astrophysics Data System (ADS)

Linares, R.; Palmer, D.; Thompson, D.; Klimenko, A.

2014-09-01

Recent events in space, including the collision of Russias Cosmos 2251 satellite with Iridium 33 and Chinas Feng Yun 1C anti-satellite demonstration, have stressed the capabilities of Space Surveillance Network (SSN) and its ability to provide accurate and actionable impact probability estimates. The SSN network has the unique challenge of tracking more than 18,000 resident space objects (RSOs) and providing critical collision avoidance warnings to military, NASA, and commercial systems. However, due to the large number of RSOs and the limited number of sensors available to track them, it is impossible to maintain persistent surveillance. Observation gaps result in large propagation intervals between measurements and close approaches. Coupled with nonlinear RSO dynamics this results in difficulty in modeling the probability distribution functions (pdfs) of the RSO. In particular low-Earth orbiting (LEO) satellites are heavily influenced by atmospheric drag, which is very difficult to model accurately. A number of atmospheric models exist which can be classified as either empirical or physics-based models. The current Air Force standard is the High Accuracy Satellite Drag Model (HASDM), which is an empirical model based on observation of calibration satellites. These satellite observations are used to determine model parameters based on their orbit determination solutions. Atmospheric orbits are perturbed by a number of factors including drag coefficient, attitude, and shape of the space object. The satellites used for the HASDM model calibration process are chosen because of their relatively simple shapes, to minimize errors introduced due to shape miss-modeling. Under this requirement the number of calibration satellites that can be used for calibrating the atmospheric models is limited. Los Alamos National Laboratory (LANL) has established a research effort, called IMPACT (Integrated Modeling of Perturbations in Atmospheres for Conjunction Tracking), to improve impact assessment via improved physics-based modeling. As part of this effort calibration satellite observations are used to dynamically calibrate the physics-based model and to improve its forecasting capability. The observations are collected from a variety of sources, including from LANLs own Raven-class optical telescope. This system collects both astrometric and photometric data on space objects. The photometric data will be used to estimate the space objects attitude and shape. Non-resolved photometric data have been studied by many as a mechanism for space object characterization. Photometry is the measurement of an objects flux or apparent brightness measured over a wavelength band. The temporal variation of photometric measurements is referred to as photometric signature. The photometric optical signature of an object contains information about shape, attitude, size and material composition. This work focuses on the processing of the data collected with LANLs telescope in an effort to use photometric data to expand the number of space objects that can be used as calibration satellites. A nonlinear least squares is used to estimate the attitude and angular velocity of the space object; a number of real data examples are shown. Inactive space objects are used for the real data examples and good estimation results are shown.

Lateral Motion and Bending of Microtubules Studied with a New Single-Filament Tracking Routine in Living Cells

PubMed Central

Pallavicini, Carla; Levi, Valeria; Wetzler, Diana E.; Angiolini, Juan F.; Benseñor, Lorena; Despósito, Marcelo A.; Bruno, Luciana

2014-01-01

The cytoskeleton is involved in numerous cellular processes such as migration, division, and contraction and provides the tracks for transport driven by molecular motors. Therefore, it is very important to quantify the mechanical behavior of the cytoskeletal filaments to get a better insight into cell mechanics and organization. It has been demonstrated that relevant mechanical properties of microtubules can be extracted from the analysis of their motion and shape fluctuations. However, tracking individual filaments in living cells is extremely complex due, for example, to the high and heterogeneous background. We introduce a believed new tracking algorithm that allows recovering the coordinates of fluorescent microtubules with ∼9 nm precision in in vitro conditions. To illustrate potential applications of this algorithm, we studied the curvature distributions of fluorescent microtubules in living cells. By performing a Fourier analysis of the microtubule shapes, we found that the curvatures followed a thermal-like distribution as previously reported with an effective persistence length of ∼20 μm, a value significantly smaller than that measured in vitro. We also verified that the microtubule-associated protein XTP or the depolymerization of the actin network do not affect this value; however, the disruption of intermediate filaments decreased the persistence length. Also, we recovered trajectories of microtubule segments in actin or intermediate filament-depleted cells, and observed a significant increase of their motion with respect to untreated cells showing that these filaments contribute to the overall organization of the microtubule network. Moreover, the analysis of trajectories of microtubule segments in untreated cells showed that these filaments presented a slower but more directional motion in the cortex with respect to the perinuclear region, and suggests that the tracking routine would allow mapping the microtubule dynamical organization in cells. PMID:24940780

Real-time visual tracking of less textured three-dimensional objects on mobile platforms

NASA Astrophysics Data System (ADS)

Seo, Byung-Kuk; Park, Jungsik; Park, Hanhoon; Park, Jong-Il

2012-12-01

Natural feature-based approaches are still challenging for mobile applications (e.g., mobile augmented reality), because they are feasible only in limited environments such as highly textured and planar scenes/objects, and they need powerful mobile hardware for fast and reliable tracking. In many cases where conventional approaches are not effective, three-dimensional (3-D) knowledge of target scenes would be beneficial. We present a well-established framework for real-time visual tracking of less textured 3-D objects on mobile platforms. Our framework is based on model-based tracking that efficiently exploits partially known 3-D scene knowledge such as object models and a background's distinctive geometric or photometric knowledge. Moreover, we elaborate on implementation in order to make it suitable for real-time vision processing on mobile hardware. The performance of the framework is tested and evaluated on recent commercially available smartphones, and its feasibility is shown by real-time demonstrations.

Object Tracking and Target Reacquisition Based on 3-D Range Data for Moving Vehicles

PubMed Central

Lee, Jehoon; Lankton, Shawn; Tannenbaum, Allen

2013-01-01

In this paper, we propose an approach for tracking an object of interest based on 3-D range data. We employ particle filtering and active contours to simultaneously estimate the global motion of the object and its local deformations. The proposed algorithm takes advantage of range information to deal with the challenging (but common) situation in which the tracked object disappears from the image domain entirely and reappears later. To cope with this problem, a method based on principle component analysis (PCA) of shape information is proposed. In the proposed method, if the target disappears out of frame, shape similarity energy is used to detect target candidates that match a template shape learned online from previously observed frames. Thus, we require no a priori knowledge of the target’s shape. Experimental results show the practical applicability and robustness of the proposed algorithm in realistic tracking scenarios. PMID:21486717

Creating objective and measurable postgraduate year 1 residency graduation requirements.

PubMed

Starosta, Kaitlin; Davis, Susan L; Kenney, Rachel M; Peters, Michael; To, Long; Kalus, James S

2017-03-15

The process of developing objective and measurable postgraduate year 1 (PGY1) residency graduation requirements and a progress tracking system is described. The PGY1 residency accreditation standard requires that programs establish criteria that must be met by residents for successful completion of the program (i.e., graduation requirements), which should presumably be aligned with helping residents to achieve the purpose of residency training. In addition, programs must track a resident's progress toward fulfillment of residency goals and objectives. Defining graduation requirements and establishing the process for tracking residents' progress are left up to the discretion of the residency program. To help standardize resident performance assessments, leaders of an academic medical center-based PGY1 residency program developed graduation requirement criteria that are objective, measurable, and linked back to residency goals and objectives. A system for tracking resident progress relative to quarterly progress targets was instituted. Leaders also developed a focused, on-the-spot skills assessment termed "the Thunderdome," which was designed for objective evaluation of direct patient care skills. Quarterly data on residents' progress are used to update and customize each resident's training plan. Implementation of this system allowed seamless linkage of the training plan, the progress tracking system, and the specified graduation requirement criteria. PGY1 residency requirements that are objective, that are measurable, and that attempt to identify what skills the resident must demonstrate in order to graduate from the program were developed for use in our residency program. A system for tracking the residents' progress by comparing residents' performance to predetermined quarterly benchmarks was developed. Copyright © 2017 by the American Society of Health-System Pharmacists, Inc. All rights reserved.

Real-time moving objects detection and tracking from airborne infrared camera

NASA Astrophysics Data System (ADS)

Zingoni, Andrea; Diani, Marco; Corsini, Giovanni

2017-10-01

Detecting and tracking moving objects in real-time from an airborne infrared (IR) camera offers interesting possibilities in video surveillance, remote sensing and computer vision applications, such as monitoring large areas simultaneously, quickly changing the point of view on the scene and pursuing objects of interest. To fully exploit such a potential, versatile solutions are needed, but, in the literature, the majority of them works only under specific conditions about the considered scenario, the characteristics of the moving objects or the aircraft movements. In order to overcome these limitations, we propose a novel approach to the problem, based on the use of a cheap inertial navigation system (INS), mounted on the aircraft. To exploit jointly the information contained in the acquired video sequence and the data provided by the INS, a specific detection and tracking algorithm has been developed. It consists of three main stages performed iteratively on each acquired frame. The detection stage, in which a coarse detection map is computed, using a local statistic both fast to calculate and robust to noise and self-deletion of the targeted objects. The registration stage, in which the position of the detected objects is coherently reported on a common reference frame, by exploiting the INS data. The tracking stage, in which the steady objects are rejected, the moving objects are tracked, and an estimation of their future position is computed, to be used in the subsequent iteration. The algorithm has been tested on a large dataset of simulated IR video sequences, recreating different environments and different movements of the aircraft. Promising results have been obtained, both in terms of detection and false alarm rate, and in terms of accuracy in the estimation of position and velocity of the objects. In addition, for each frame, the detection and tracking map has been generated by the algorithm, before the acquisition of the subsequent frame, proving its capability to work in real-time.

Delayed visual feedback affects both manual tracking and grip force control when transporting a handheld object.

PubMed

Sarlegna, Fabrice R; Baud-Bovy, Gabriel; Danion, Frédéric

2010-08-01

When we manipulate an object, grip force is adjusted in anticipation of the mechanical consequences of hand motion (i.e., load force) to prevent the object from slipping. This predictive behavior is assumed to rely on an internal representation of the object dynamic properties, which would be elaborated via visual information before the object is grasped and via somatosensory feedback once the object is grasped. Here we examined this view by investigating the effect of delayed visual feedback during dextrous object manipulation. Adult participants manually tracked a sinusoidal target by oscillating a handheld object whose current position was displayed as a cursor on a screen along with the visual target. A delay was introduced between actual object displacement and cursor motion. This delay was linearly increased (from 0 to 300 ms) and decreased within 2-min trials. As previously reported, delayed visual feedback altered performance in manual tracking. Importantly, although the physical properties of the object remained unchanged, delayed visual feedback altered the timing of grip force relative to load force by about 50 ms. Additional experiments showed that this effect was not due to task complexity nor to manual tracking. A model inspired by the behavior of mass-spring systems suggests that delayed visual feedback may have biased the representation of object dynamics. Overall, our findings support the idea that visual feedback of object motion can influence the predictive control of grip force even when the object is grasped.

AN/FSY-3 Space Fence System Support of Conjunction Assessment

NASA Astrophysics Data System (ADS)

Koltiska, M.; Du, H.; Prochoda, D.; Kelly, K.

2016-09-01

The Space Fence System is a ground-based space surveillance radar system designed to detect and track all objects in Low Earth Orbit the size of a softball or larger. The system detects many objects that are not currently in the catalog of satellites and space debris that is maintained by the US Air Force. In addition, it will also be capable of tracking many of the deep space objects in the catalog. By providing daily updates of the orbits of these new objects along with updates of most of the objects in the catalog, it will enhance Space Situational Awareness and significantly improve our ability to predict close approaches, aka conjunctions, of objects in space. With this additional capacity for tracking objects in space the Space Surveillance Network has significantly more resources for monitoring orbital debris, especially for debris that could collide with active satellites and other debris.

Large scale tracking algorithms

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

Hansen, Ross L.; Love, Joshua Alan; Melgaard, David Kennett

2015-01-01

Low signal-to-noise data processing algorithms for improved detection, tracking, discrimination and situational threat assessment are a key research challenge. As sensor technologies progress, the number of pixels will increase signi cantly. This will result in increased resolution, which could improve object discrimination, but unfortunately, will also result in a significant increase in the number of potential targets to track. Many tracking techniques, like multi-hypothesis trackers, suffer from a combinatorial explosion as the number of potential targets increase. As the resolution increases, the phenomenology applied towards detection algorithms also changes. For low resolution sensors, "blob" tracking is the norm. For highermore » resolution data, additional information may be employed in the detection and classfication steps. The most challenging scenarios are those where the targets cannot be fully resolved, yet must be tracked and distinguished for neighboring closely spaced objects. Tracking vehicles in an urban environment is an example of such a challenging scenario. This report evaluates several potential tracking algorithms for large-scale tracking in an urban environment.« less

Monocular Stereo Measurement Using High-Speed Catadioptric Tracking

PubMed Central

Hu, Shaopeng; Matsumoto, Yuji; Takaki, Takeshi; Ishii, Idaku

2017-01-01

This paper presents a novel concept of real-time catadioptric stereo tracking using a single ultrafast mirror-drive pan-tilt active vision system that can simultaneously switch between hundreds of different views in a second. By accelerating video-shooting, computation, and actuation at the millisecond-granularity level for time-division multithreaded processing in ultrafast gaze control, the active vision system can function virtually as two or more tracking cameras with different views. It enables a single active vision system to act as virtual left and right pan-tilt cameras that can simultaneously shoot a pair of stereo images for the same object to be observed at arbitrary viewpoints by switching the direction of the mirrors of the active vision system frame by frame. We developed a monocular galvano-mirror-based stereo tracking system that can switch between 500 different views in a second, and it functions as a catadioptric active stereo with left and right pan-tilt tracking cameras that can virtually capture 8-bit color 512×512 images each operating at 250 fps to mechanically track a fast-moving object with a sufficient parallax for accurate 3D measurement. Several tracking experiments for moving objects in 3D space are described to demonstrate the performance of our monocular stereo tracking system. PMID:28792483

TRACKING THE RESPONSE OF BURKHOLDERIA CEPACIA G4 5223-PR1 IN AQUIFER MICROCOSMS

EPA Science Inventory

The introduction of bacteria into the environment for bioremediation purposes (bioaugmentation) requires analysis and monitoring of microbial population dynamics to define persistence and activity from both efficacy and risk assessment perspectives, Burkholderia cepacia G4 5223-P...

Siamese convolutional networks for tracking the spine motion

NASA Astrophysics Data System (ADS)

Liu, Yuan; Sui, Xiubao; Sun, Yicheng; Liu, Chengwei; Hu, Yong

2017-09-01

Deep learning models have demonstrated great success in various computer vision tasks such as image classification and object tracking. However, tracking the lumbar spine by digitalized video fluoroscopic imaging (DVFI), which can quantitatively analyze the motion mode of spine to diagnose lumbar instability, has not yet been well developed due to the lack of steady and robust tracking method. In this paper, we propose a novel visual tracking algorithm of the lumbar vertebra motion based on a Siamese convolutional neural network (CNN) model. We train a full-convolutional neural network offline to learn generic image features. The network is trained to learn a similarity function that compares the labeled target in the first frame with the candidate patches in the current frame. The similarity function returns a high score if the two images depict the same object. Once learned, the similarity function is used to track a previously unseen object without any adapting online. In the current frame, our tracker is performed by evaluating the candidate rotated patches sampled around the previous frame target position and presents a rotated bounding box to locate the predicted target precisely. Results indicate that the proposed tracking method can detect the lumbar vertebra steadily and robustly. Especially for images with low contrast and cluttered background, the presented tracker can still achieve good tracking performance. Further, the proposed algorithm operates at high speed for real time tracking.

Tracks detection from high-orbit space objects

NASA Astrophysics Data System (ADS)

Shumilov, Yu. P.; Vygon, V. G.; Grishin, E. A.; Konoplev, A. O.; Semichev, O. P.; Shargorodskii, V. D.

2017-05-01

The paper presents studies results of a complex algorithm for the detection of highly orbital space objects. Before the implementation of the algorithm, a series of frames with weak tracks of space objects, which can be discrete, is recorded. The algorithm includes pre-processing, classical for astronomy, consistent filtering of each frame and its threshold processing, shear transformation, median filtering of the transformed series of frames, repeated threshold processing and detection decision making. Modeling of space objects weak tracks on of the night starry sky real frames obtained in the regime of a stationary telescope was carried out. It is shown that the permeability of an optoelectronic device has increased by almost 2m.

Application of Multi-Hypothesis Sequential Monte Carlo for Breakup Analysis

NASA Astrophysics Data System (ADS)

Faber, W. R.; Zaidi, W.; Hussein, I. I.; Roscoe, C. W. T.; Wilkins, M. P.; Schumacher, P. W., Jr.

As more objects are launched into space, the potential for breakup events and space object collisions is ever increasing. These events create large clouds of debris that are extremely hazardous to space operations. Providing timely, accurate, and statistically meaningful Space Situational Awareness (SSA) data is crucial in order to protect assets and operations in space. The space object tracking problem, in general, is nonlinear in both state dynamics and observations, making it ill-suited to linear filtering techniques such as the Kalman filter. Additionally, given the multi-object, multi-scenario nature of the problem, space situational awareness requires multi-hypothesis tracking and management that is combinatorially challenging in nature. In practice, it is often seen that assumptions of underlying linearity and/or Gaussianity are used to provide tractable solutions to the multiple space object tracking problem. However, these assumptions are, at times, detrimental to tracking data and provide statistically inconsistent solutions. This paper details a tractable solution to the multiple space object tracking problem applicable to space object breakup events. Within this solution, simplifying assumptions of the underlying probability density function are relaxed and heuristic methods for hypothesis management are avoided. This is done by implementing Sequential Monte Carlo (SMC) methods for both nonlinear filtering as well as hypothesis management. This goal of this paper is to detail the solution and use it as a platform to discuss computational limitations that hinder proper analysis of large breakup events.

Phenomenal Permanence and the Development of Predictive Tracking in Infancy

ERIC Educational Resources Information Center

Bertenthal, Bennett I.; Longo, Matthew R.; Kenny, Sarah

2007-01-01

The perceived spatiotemporal continuity of objects depends on the way they appear and disappear as they move in the spatial layout. This study investigated whether infants' predictive tracking of a briefly occluded object is sensitive to the manner by which the object disappears and reappears. Five-, 7-, and 9-month-old infants were shown a ball…

Indoor Trajectory Tracking Scheme Based on Delaunay Triangulation and Heuristic Information in Wireless Sensor Networks.

PubMed

Qin, Junping; Sun, Shiwen; Deng, Qingxu; Liu, Limin; Tian, Yonghong

2017-06-02

Object tracking and detection is one of the most significant research areas for wireless sensor networks. Existing indoor trajectory tracking schemes in wireless sensor networks are based on continuous localization and moving object data mining. Indoor trajectory tracking based on the received signal strength indicator ( RSSI ) has received increased attention because it has low cost and requires no special infrastructure. However, RSSI tracking introduces uncertainty because of the inaccuracies of measurement instruments and the irregularities (unstable, multipath, diffraction) of wireless signal transmissions in indoor environments. Heuristic information includes some key factors for trajectory tracking procedures. This paper proposes a novel trajectory tracking scheme based on Delaunay triangulation and heuristic information (TTDH). In this scheme, the entire field is divided into a series of triangular regions. The common side of adjacent triangular regions is regarded as a regional boundary. Our scheme detects heuristic information related to a moving object's trajectory, including boundaries and triangular regions. Then, the trajectory is formed by means of a dynamic time-warping position-fingerprint-matching algorithm with heuristic information constraints. Field experiments show that the average error distance of our scheme is less than 1.5 m, and that error does not accumulate among the regions.

Color Image Processing and Object Tracking System

NASA Technical Reports Server (NTRS)

Klimek, Robert B.; Wright, Ted W.; Sielken, Robert S.

1996-01-01

This report describes a personal computer based system for automatic and semiautomatic tracking of objects on film or video tape, developed to meet the needs of the Microgravity Combustion and Fluids Science Research Programs at the NASA Lewis Research Center. The system consists of individual hardware components working under computer control to achieve a high degree of automation. The most important hardware components include 16-mm and 35-mm film transports, a high resolution digital camera mounted on a x-y-z micro-positioning stage, an S-VHS tapedeck, an Hi8 tapedeck, video laserdisk, and a framegrabber. All of the image input devices are remotely controlled by a computer. Software was developed to integrate the overall operation of the system including device frame incrementation, grabbing of image frames, image processing of the object's neighborhood, locating the position of the object being tracked, and storing the coordinates in a file. This process is performed repeatedly until the last frame is reached. Several different tracking methods are supported. To illustrate the process, two representative applications of the system are described. These applications represent typical uses of the system and include tracking the propagation of a flame front and tracking the movement of a liquid-gas interface with extremely poor visibility.

A Real-Time Orbit Determination Method for Smooth Transition from Optical Tracking to Laser Ranging of Debris

PubMed Central

Li, Bin; Sang, Jizhang; Zhang, Zhongping

2016-01-01

A critical requirement to achieve high efficiency of debris laser tracking is to have sufficiently accurate orbit predictions (OP) in both the pointing direction (better than 20 arc seconds) and distance from the tracking station to the debris objects, with the former more important than the latter because of the narrow laser beam. When the two line element (TLE) is used to provide the orbit predictions, the resultant pointing errors are usually on the order of tens to hundreds of arc seconds. In practice, therefore, angular observations of debris objects are first collected using an optical tracking sensor, and then used to guide the laser beam pointing to the objects. The manual guidance may cause interrupts to the laser tracking, and consequently loss of valuable laser tracking data. This paper presents a real-time orbit determination (OD) and prediction method to realize smooth and efficient debris laser tracking. The method uses TLE-computed positions and angles over a short-arc of less than 2 min as observations in an OD process where simplified force models are considered. After the OD convergence, the OP is performed from the last observation epoch to the end of the tracking pass. Simulation and real tracking data processing results show that the pointing prediction errors are usually less than 10″, and the distance errors less than 100 m, therefore, the prediction accuracy is sufficient for the blind laser tracking. PMID:27347958

Defining the Biological Effectiveness of Components of High-LET Track Structure.

PubMed

Sridharan, Deepa M; Chappell, Lori J; Whalen, Mary K; Cucinotta, Francis A; Pluth, Janice M

2015-07-01

During space travel, astronauts are exposed to a wide array of high-linear energy transfer (LET) particles, with differing energies and resulting biological effects. Risk assessment of these exposures carries a large uncertainty predominantly due to the unique track structure of the particle's energy deposition. The complex damage elicited by high charge and energy (HZE) particles results from both lesions along the track core and from energetic electrons, δ rays, generated as a consequence of particle traversal. To better define how cells respond to this complex radiation exposure, a normal hTERT immortalized skin fibroblast cell line was exposed to a defined panel of particles carefully chosen to tease out track structure effects. Phosphorylation kinetics for several key double-strand break (DSB) response proteins (γ-H2AX, pATF2 and pSMC1) were defined after exposure to ten different high-LET radiation qualities and one low-LET radiation (X ray), at two doses (0.5-2 Gy) and time points (2 and 24 h). The results reveal that the lower energy particles (Fe 300, Si 93 and Ti 300 MeV/u), with a narrower track width and higher number and intensity of δ rays, cause the highest degree of persistent damage response. The persistent γ-H2AX signal at lower energies suggests that damage from these exposures are more difficult to resolve, likely due to the greater complexity of the associated DNA lesions. However, different kinetics were observed for the solely ATM-mediated phosphorylations (pATF2 and pSMC1), revealing a shallow induction at early times and a higher level of residual phosphorylation compared to γ-H2AX. The differing phospho-protein profiles exhibited, compared to γ-H2AX, suggests additional functions for these proteins within the cell. The strong correspondence between the predicted curves for energy deposition per nucleosome for each ion/energy combination and the persistent levels of γ-H2AX indicates that the nature of energy distribution defines residual levels of γ-H2AX, an indicator of unrepaired DSBs. Our results suggest that decreasing the energy of a particle results in more complex damage that may increase genomic instability and increase the risk of carcinogenesis.

Hardy Objects in Saturn F Ring

NASA Image and Video Library

2017-02-24

As NASA's Cassini spacecraft continues its weekly ring-grazing orbits, diving just past the outside of Saturn F ring, it is tracking several small, persistent objects there. These images show two such objects that Cassini originally detected in spring 2016, as the spacecraft transitioned from more equatorial orbits to orbits at increasingly high inclination about the planet's equator. Imaging team members studying these objects gave them the informal designations F16QA (right image) and F16QB (left image). The researchers have observed that objects such as these occasionally crash through the F ring's bright core, producing spectacular collisional structures.While these objects may be mostly loose agglomerations of tiny ring particles, scientists suspect that small, fairly solid bodies lurk within each object, given that they have survived several collisions with the ring since their discovery. The faint retinue of dust around them is likely the result of the most recent collision each underwent before these images were obtained. The researchers think these objects originally form as loose clumps in the F ring core as a result of perturbations triggered by Saturn's moon Prometheus. . If they survive subsequent encounters with Prometheus, their orbits can evolve, eventually leading to core-crossing clumps that produce spectacular features, even though they collide with the ring at low speeds. The images were obtained using the Cassini spacecraft narrow-angle camera on Feb. 5, 2017, at a distance of 610,000 miles (982,000 kilometers, left image) and 556,000 miles (894,000 kilometers, right image) from the F ring. Image scale is about 4 miles (6 kilometers) per pixel. http://photojournal.jpl.nasa.gov/catalog/PIA21432

Delineating the Neural Signatures of Tracking Spatial Position and Working Memory during Attentive Tracking

PubMed Central

Drew, Trafton; Horowitz, Todd S.; Wolfe, Jeremy M.; Vogel, Edward K.

2015-01-01

In the attentive tracking task, observers track multiple objects as they move independently and unpredictably among visually identical distractors. Although a number of models of attentive tracking implicate visual working memory as the mechanism responsible for representing target locations, no study has ever directly compared the neural mechanisms of the two tasks. In the current set of experiments, we used electrophysiological recordings to delineate similarities and differences between the neural processing involved in working memory and attentive tracking. We found that the contralateral electrophysiological response to the two tasks was similarly sensitive to the number of items attended in both tasks but that there was also a unique contralateral negativity related to the process of monitoring target position during tracking. This signal was absent for periods of time during tracking tasks when objects briefly stopped moving. These results provide evidence that, during attentive tracking, the process of tracking target locations elicits an electrophysiological response that is distinct and dissociable from neural measures of the number of items being attended. PMID:21228175

Object motion computation for the initiation of smooth pursuit eye movements in humans.

PubMed

Wallace, Julian M; Stone, Leland S; Masson, Guillaume S

2005-04-01

Pursuing an object with smooth eye movements requires an accurate estimate of its two-dimensional (2D) trajectory. This 2D motion computation requires that different local motion measurements are extracted and combined to recover the global object-motion direction and speed. Several combination rules have been proposed such as vector averaging (VA), intersection of constraints (IOC), or 2D feature tracking (2DFT). To examine this computation, we investigated the time course of smooth pursuit eye movements driven by simple objects of different shapes. For type II diamond (where the direction of true object motion is dramatically different from the vector average of the 1-dimensional edge motions, i.e., VA not equal IOC = 2DFT), the ocular tracking is initiated in the vector average direction. Over a period of less than 300 ms, the eye-tracking direction converges on the true object motion. The reduction of the tracking error starts before the closing of the oculomotor loop. For type I diamonds (where the direction of true object motion is identical to the vector average direction, i.e., VA = IOC = 2DFT), there is no such bias. We quantified this effect by calculating the direction error between responses to types I and II and measuring its maximum value and time constant. At low contrast and high speeds, the initial bias in tracking direction is larger and takes longer to converge onto the actual object-motion direction. This effect is attenuated with the introduction of more 2D information to the extent that it was totally obliterated with a texture-filled type II diamond. These results suggest a flexible 2D computation for motion integration, which combines all available one-dimensional (edge) and 2D (feature) motion information to refine the estimate of object-motion direction over time.

Online Object Tracking, Learning and Parsing with And-Or Graphs.

PubMed

Wu, Tianfu; Lu, Yang; Zhu, Song-Chun

2017-12-01

This paper presents a method, called AOGTracker, for simultaneously tracking, learning and parsing (TLP) of unknown objects in video sequences with a hierarchical and compositional And-Or graph (AOG) representation. The TLP method is formulated in the Bayesian framework with a spatial and a temporal dynamic programming (DP) algorithms inferring object bounding boxes on-the-fly. During online learning, the AOG is discriminatively learned using latent SVM [1] to account for appearance (e.g., lighting and partial occlusion) and structural (e.g., different poses and viewpoints) variations of a tracked object, as well as distractors (e.g., similar objects) in background. Three key issues in online inference and learning are addressed: (i) maintaining purity of positive and negative examples collected online, (ii) controling model complexity in latent structure learning, and (iii) identifying critical moments to re-learn the structure of AOG based on its intrackability. The intrackability measures uncertainty of an AOG based on its score maps in a frame. In experiments, our AOGTracker is tested on two popular tracking benchmarks with the same parameter setting: the TB-100/50/CVPR2013 benchmarks  , [3] , and the VOT benchmarks [4] -VOT 2013, 2014, 2015 and TIR2015 (thermal imagery tracking). In the former, our AOGTracker outperforms state-of-the-art tracking algorithms including two trackers based on deep convolutional network   [5] , [6] . In the latter, our AOGTracker outperforms all other trackers in VOT2013 and is comparable to the state-of-the-art methods in VOT2014, 2015 and TIR2015.

A-Track: A new approach for detection of moving objects in FITS images

NASA Astrophysics Data System (ADS)

Atay, T.; Kaplan, M.; Kilic, Y.; Karapinar, N.

2016-10-01

We have developed a fast, open-source, cross-platform pipeline, called A-Track, for detecting the moving objects (asteroids and comets) in sequential telescope images in FITS format. The pipeline is coded in Python 3. The moving objects are detected using a modified line detection algorithm, called MILD. We tested the pipeline on astronomical data acquired by an SI-1100 CCD with a 1-meter telescope. We found that A-Track performs very well in terms of detection efficiency, stability, and processing time. The code is hosted on GitHub under the GNU GPL v3 license.

Measuring persistence: A literature review focusing on methodological issues

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

Wolfe, A.K.; Brown, M.A.; Trumble, D.

1995-03-01

This literature review was conducted as part of a larger project to produce a handbook on the measurement of persistence. The past decade has marked the development of the concept of persistence and a growing recognition that the long-term impacts of demand-side management (DSM) programs warrant careful assessment. Although Increasing attention has been paid to the topic of persistence, no clear consensus has emerged either about its definition or about the methods most appropriate for its measurement and analysis. This project strives to fill that gap by reviewing the goals, terminology, and methods of past persistence studies. It was conductedmore » from the perspective of a utility that seeks to acquire demand-side resources and is interested in their long-term durability; it was not conducted from the perspective of the individual consumer. Over 30 persistence studies, articles, and protocols were examined for this report. The review begins by discussing the underpinnings of persistence studies: namely, the definitions of persistence and the purposes of persistence studies. Then. it describes issues relevant to both the collection and analysis of data on the persistence of energy and demand savings. Findings from persistence studies also are summarized. Throughout the review, four studies are used repeatedly to illustrate different methodological and analytical approaches to persistence so that readers can track the data collection. data analysis, and findings of a set of comprehensive studies that represent alternative approaches.« less

High-performance object tracking and fixation with an online neural estimator.

PubMed

Kumarawadu, Sisil; Watanabe, Keigo; Lee, Tsu-Tian

2007-02-01

Vision-based target tracking and fixation to keep objects that move in three dimensions in view is important for many tasks in several fields including intelligent transportation systems and robotics. Much of the visual control literature has focused on the kinematics of visual control and ignored a number of significant dynamic control issues that limit performance. In line with this, this paper presents a neural network (NN)-based binocular tracking scheme for high-performance target tracking and fixation with minimum sensory information. The procedure allows the designer to take into account the physical (Lagrangian dynamics) properties of the vision system in the control law. The design objective is to synthesize a binocular tracking controller that explicitly takes the systems dynamics into account, yet needs no knowledge of dynamic nonlinearities and joint velocity sensory information. The combined neurocontroller-observer scheme can guarantee the uniform ultimate bounds of the tracking, observer, and NN weight estimation errors under fairly general conditions on the controller-observer gains. The controller is tested and verified via simulation tests in the presence of severe target motion changes.

A Scalable Distributed Approach to Mobile Robot Vision

NASA Technical Reports Server (NTRS)

Kuipers, Benjamin; Browning, Robert L.; Gribble, William S.

1997-01-01

This paper documents our progress during the first year of work on our original proposal entitled 'A Scalable Distributed Approach to Mobile Robot Vision'. We are pursuing a strategy for real-time visual identification and tracking of complex objects which does not rely on specialized image-processing hardware. In this system perceptual schemas represent objects as a graph of primitive features. Distributed software agents identify and track these features, using variable-geometry image subwindows of limited size. Active control of imaging parameters and selective processing makes simultaneous real-time tracking of many primitive features tractable. Perceptual schemas operate independently from the tracking of primitive features, so that real-time tracking of a set of image features is not hurt by latency in recognition of the object that those features make up. The architecture allows semantically significant features to be tracked with limited expenditure of computational resources, and allows the visual computation to be distributed across a network of processors. Early experiments are described which demonstrate the usefulness of this formulation, followed by a brief overview of our more recent progress (after the first year).

Real time eye tracking using Kalman extended spatio-temporal context learning

NASA Astrophysics Data System (ADS)

Munir, Farzeen; Minhas, Fayyaz ul Amir Asfar; Jalil, Abdul; Jeon, Moongu

2017-06-01

Real time eye tracking has numerous applications in human computer interaction such as a mouse cursor control in a computer system. It is useful for persons with muscular or motion impairments. However, tracking the movement of the eye is complicated by occlusion due to blinking, head movement, screen glare, rapid eye movements, etc. In this work, we present the algorithmic and construction details of a real time eye tracking system. Our proposed system is an extension of Spatio-Temporal context learning through Kalman Filtering. Spatio-Temporal Context Learning offers state of the art accuracy in general object tracking but its performance suffers due to object occlusion. Addition of the Kalman filter allows the proposed method to model the dynamics of the motion of the eye and provide robust eye tracking in cases of occlusion. We demonstrate the effectiveness of this tracking technique by controlling the computer cursor in real time by eye movements.

The persistence of bifidobacteria populations in a river measured by molecular and culture techniques.

PubMed

Bonjoch, X; Lucena, F; Blanch, A R

2009-10-01

To determine relative to faecal coliforms (FC) and sulfite-reducing clostridia (SRC), the environmental persistence of natural populations of Bifidobacterium spp. enumerated by culturing and quantitative polymerase chain reaction (q-PCR). Dialysis tubing containing river supplemented with overnight cultures of Bifidobacterium adolescentis (BA) and Bifidobacterium dentium (BD) or urban wastewater were suspended in a river for up to 10 days. At intervals, the contents of each dialysis tube were assayed using q-PCR assays for BA and BD, and selective culture media for FC, SRC, total bifidobacteria (TB), sorbitol-fermenting bifidobacteria (SFB) and cultivable BA. Mean summer T(90) values were 251 h for SRC, 92 h for FC, 48 h for BA and BD by q-PCR, and 9 h for TB. Bifidobacterium spp. was the population with the lowest persistence, showing seasonal differences in T(90) when measured by culture techniques or by q-PCR. This difference in relative persistence is because of a longer persistence of molecular targets than cultivable cells. The persistence of a viable bifidobacteria cells is shorter, but the longest persistence of molecular targets. This factor could be used for origin the faecal pollution in water for the development of microbial source tracking (MST).

Detection and tracking of drones using advanced acoustic cameras

NASA Astrophysics Data System (ADS)

Busset, Joël.; Perrodin, Florian; Wellig, Peter; Ott, Beat; Heutschi, Kurt; Rühl, Torben; Nussbaumer, Thomas

2015-10-01

Recent events of drones flying over city centers, official buildings and nuclear installations stressed the growing threat of uncontrolled drone proliferation and the lack of real countermeasure. Indeed, detecting and tracking them can be difficult with traditional techniques. A system to acoustically detect and track small moving objects, such as drones or ground robots, using acoustic cameras is presented. The described sensor, is completely passive, and composed of a 120-element microphone array and a video camera. The acoustic imaging algorithm determines in real-time the sound power level coming from all directions, using the phase of the sound signals. A tracking algorithm is then able to follow the sound sources. Additionally, a beamforming algorithm selectively extracts the sound coming from each tracked sound source. This extracted sound signal can be used to identify sound signatures and determine the type of object. The described techniques can detect and track any object that produces noise (engines, propellers, tires, etc). It is a good complementary approach to more traditional techniques such as (i) optical and infrared cameras, for which the object may only represent few pixels and may be hidden by the blooming of a bright background, and (ii) radar or other echo-localization techniques, suffering from the weakness of the echo signal coming back to the sensor. The distance of detection depends on the type (frequency range) and volume of the noise emitted by the object, and on the background noise of the environment. Detection range and resilience to background noise were tested in both, laboratory environments and outdoor conditions. It was determined that drones can be tracked up to 160 to 250 meters, depending on their type. Speech extraction was also experimentally investigated: the speech signal of a person being 80 to 100 meters away can be captured with acceptable speech intelligibility.

The in vivo activation of persistent nanophosphors for optical imaging of vascularization, tumours and grafted cells

NASA Astrophysics Data System (ADS)

Maldiney, Thomas; Bessière, Aurélie; Seguin, Johanne; Teston, Eliott; Sharma, Suchinder K.; Viana, Bruno; Bos, Adrie J. J.; Dorenbos, Pieter; Bessodes, Michel; Gourier, Didier; Scherman, Daniel; Richard, Cyrille

2014-04-01

Optical imaging for biological applications requires more sensitive tools. Near-infrared persistent luminescence nanoparticles enable highly sensitive in vivo optical detection and complete avoidance of tissue autofluorescence. However, the actual generation of persistent luminescence nanoparticles necessitates ex vivo activation before systemic administration, which prevents long-term imaging in living animals. Here, we introduce a new generation of optical nanoprobes, based on chromium-doped zinc gallate, whose persistent luminescence can be activated in vivo through living tissues using highly penetrating low-energy red photons. Surface functionalization of this photonic probe can be adjusted to favour multiple biomedical applications such as tumour targeting. Notably, we show that cells can endocytose these nanoparticles in vitro and that, after intravenous injection, we can track labelled cells in vivo and follow their biodistribution by a simple whole animal optical detection, opening new perspectives for cell therapy research and for a variety of diagnosis applications.

Filling in the gaps: Anticipatory control of eye movements in chronic mild traumatic brain injury.

PubMed

Diwakar, Mithun; Harrington, Deborah L; Maruta, Jun; Ghajar, Jamshid; El-Gabalawy, Fady; Muzzatti, Laura; Corbetta, Maurizio; Huang, Ming-Xiong; Lee, Roland R

2015-01-01

A barrier in the diagnosis of mild traumatic brain injury (mTBI) stems from the lack of measures that are adequately sensitive in detecting mild head injuries. MRI and CT are typically negative in mTBI patients with persistent symptoms of post-concussive syndrome (PCS), and characteristic difficulties in sustaining attention often go undetected on neuropsychological testing, which can be insensitive to momentary lapses in concentration. Conversely, visual tracking strongly depends on sustained attention over time and is impaired in chronic mTBI patients, especially when tracking an occluded target. This finding suggests deficient internal anticipatory control in mTBI, the neural underpinnings of which are poorly understood. The present study investigated the neuronal bases for deficient anticipatory control during visual tracking in 25 chronic mTBI patients with persistent PCS symptoms and 25 healthy control subjects. The task was performed while undergoing magnetoencephalography (MEG), which allowed us to examine whether neural dysfunction associated with anticipatory control deficits was due to altered alpha, beta, and/or gamma activity. Neuropsychological examinations characterized cognition in both groups. During MEG recordings, subjects tracked a predictably moving target that was either continuously visible or randomly occluded (gap condition). MEG source-imaging analyses tested for group differences in alpha, beta, and gamma frequency bands. The results showed executive functioning, information processing speed, and verbal memory deficits in the mTBI group. Visual tracking was impaired in the mTBI group only in the gap condition. Patients showed greater error than controls before and during target occlusion, and were slower to resynchronize with the target when it reappeared. Impaired tracking concurred with abnormal beta activity, which was suppressed in the parietal cortex, especially the right hemisphere, and enhanced in left caudate and frontal-temporal areas. Regional beta-amplitude demonstrated high classification accuracy (92%) compared to eye-tracking (65%) and neuropsychological variables (80%). These findings show that deficient internal anticipatory control in mTBI is associated with altered beta activity, which is remarkably sensitive given the heterogeneity of injuries.

USING STABLE ISOTOPES TO TRACK BIOMAGNIFICATION OF POLYCHLORINATED BIPHENYLS (PCBS) THROUGH STREAM FOOD WEBS

EPA Science Inventory

Most studies of biomagnification are from lentic systems, which are characterized by organic matter and sediment retention. However, biomagnification studies in streams are rare. This is surprising because PCBs and other persistent organic pollutants are known to biomagnify in ...

TRACKING CHLORDANE COMPOSITIONAL AND CHIRAL PROFILES IN SOIL AND VEGETATION. (R828174)

EPA Science Inventory

The cycling of chlordane and other persistent organic pollutants through the environment must be comprehensively elucidated to assess adequately the human health risks posed from such contaminants. In this study the compositional and chiral profiles of weathered chlordane resi...

DEVELOPMENT OF ANALYTICAL METHODS FOR SPECIFIC LAWN- APPLIED PESTICIDES IN HOUSE DUST

EPA Science Inventory

Many pesticides have been developed for residential outdoor application, particularly for lawn care. Residues from these applications may be tracked into the home, where they become incorporated with house dust and persist for long periods of time. Consequently, potential human...

Recognition of ships for long-term tracking

NASA Astrophysics Data System (ADS)

van den Broek, Sebastiaan P.; Bouma, Henri; Veerman, Henny E. T.; Benoist, Koen W.; den Hollander, Richard J. M.; Schwering, Piet B. W.

2014-06-01

Long-term tracking is important for maritime situational awareness to identify currently observed ships as earlier encounters. In cases of, for example, piracy and smuggling, past location and behavior analysis are useful to determine whether a ship is of interest. Furthermore, it is beneficial to make this assessment with sensors (such as cameras) at a distance, to avoid costs of bringing an own asset closer to the ship for verification. The emphasis of the research presented in this paper, is on the use of several feature extraction and matching methods for recognizing ships from electro-optical imagery within different categories of vessels. We compared central moments, SIFT with localization and SIFT with Fisher Vectors. From the evaluation on imagery of ships, an indication of discriminative power is obtained between and within different categories of ships. This is used to assess the usefulness in persistent tracking, from short intervals (track improvement) to larger intervals (re-identifying ships). The result of this assessment on real data is used in a simulation environment to determine how track continuity is improved. The simulations showed that even limited recognition will improve tracking, connecting both tracks at short intervals as well as over several days.

Model predictive control system and method for integrated gasification combined cycle power generation

DOEpatents

Kumar, Aditya; Shi, Ruijie; Kumar, Rajeeva; Dokucu, Mustafa

2013-04-09

Control system and method for controlling an integrated gasification combined cycle (IGCC) plant are provided. The system may include a controller coupled to a dynamic model of the plant to process a prediction of plant performance and determine a control strategy for the IGCC plant over a time horizon subject to plant constraints. The control strategy may include control functionality to meet a tracking objective and control functionality to meet an optimization objective. The control strategy may be configured to prioritize the tracking objective over the optimization objective based on a coordinate transformation, such as an orthogonal or quasi-orthogonal projection. A plurality of plant control knobs may be set in accordance with the control strategy to generate a sequence of coordinated multivariable control inputs to meet the tracking objective and the optimization objective subject to the prioritization resulting from the coordinate transformation.

Density and persistence analyze on the spreading models multi-regions multi-patchs

NASA Astrophysics Data System (ADS)

Hariyanto, Hanafi, Lukman; Wahyudi, Suhud

2017-08-01

The spread of the virus is widespread in some countries and even can reach some continents. This ever happened in the pandemic H1N1 virus outbreak in 2005 which covers 3 continents, as well as the H5N1 virus that hits several regions in Indonesia. If the virus spreads to the region as a source of the spread, the outbreak will occur due to the movement of infected individuals or vector that moves freely in other regions. The focus of this paper is to analyze the characteristics of the sub-population density, as well as the persistence of individuals moving on the path that connecting two areas of its distribution through mathematical models constructed by the spread of the virus in the three regions. The analysis results showed that the movement of individual sub-population exposure to all of the tracks or individual transfer on another track are having transition due to the genetic evolution of the virus and that causes potential outbreaks in the wider regions.

Feature point based 3D tracking of multiple fish from multi-view images

PubMed Central

Qian, Zhi-Ming

2017-01-01

A feature point based method is proposed for tracking multiple fish in 3D space. First, a simplified representation of the object is realized through construction of two feature point models based on its appearance characteristics. After feature points are classified into occluded and non-occluded types, matching and association are performed, respectively. Finally, the object's motion trajectory in 3D space is obtained through integrating multi-view tracking results. Experimental results show that the proposed method can simultaneously track 3D motion trajectories for up to 10 fish accurately and robustly. PMID:28665966

Feature point based 3D tracking of multiple fish from multi-view images.

PubMed

Qian, Zhi-Ming; Chen, Yan Qiu

2017-01-01

A feature point based method is proposed for tracking multiple fish in 3D space. First, a simplified representation of the object is realized through construction of two feature point models based on its appearance characteristics. After feature points are classified into occluded and non-occluded types, matching and association are performed, respectively. Finally, the object's motion trajectory in 3D space is obtained through integrating multi-view tracking results. Experimental results show that the proposed method can simultaneously track 3D motion trajectories for up to 10 fish accurately and robustly.

Tracking moving targets behind a scattering medium via speckle correlation.

PubMed

Guo, Chengfei; Liu, Jietao; Wu, Tengfei; Zhu, Lei; Shao, Xiaopeng

2018-02-01

Tracking moving targets behind a scattering medium is a challenge, and it has many important applications in various fields. Owing to the multiple scattering, instead of the object image, only a random speckle pattern can be received on the camera when light is passing through highly scattering layers. Significantly, an important feature of a speckle pattern has been found, and it showed the target information can be derived from the speckle correlation. In this work, inspired by the notions used in computer vision and deformation detection, by specific simulations and experiments, we demonstrate a simple object tracking method, in which by using the speckle correlation, the movement of a hidden object can be tracked in the lateral direction and axial direction. In addition, the rotation state of the moving target can also be recognized by utilizing the autocorrelation of a speckle. This work will be beneficial for biomedical applications in the fields of quantitative analysis of the working mechanisms of a micro-object and the acquisition of dynamical information of the micro-object motion.

Growth in the Number of SSN Tracked Orbital Objects

NASA Technical Reports Server (NTRS)

Stansbery, Eugene G.

2004-01-01

The number of objects in earth orbit tracked by the US Space Surveillance Network (SSN) has experienced unprecedented growth since March, 2003. Approximately 2000 orbiting objects have been added to the "Analyst list" of tracked objects. This growth is primarily due to the resumption of full power/full time operation of the AN/FPS-108 Cobra Dane radar located on Shemya Island, AK. Cobra Dane is an L-band (23-cm wavelength) phased array radar which first became operational in 1977. Cobra Dane was a "Collateral Sensor" in the SSN until 1994 when its communication link with the Space Control Center (SCC) was closed. NASA and the Air Force conducted tests in 1999 using Cobra Dane to detect and track small debris. These tests confirmed that the radar was capable of detecting and maintaining orbits on objects as small as 5-cm diameter. Subsequently, Cobra Dane was reconnected to the SSN and resumed full power/full time space surveillance operations on March 4, 2003. This paper will examine the new data and its implications to the understanding of the orbital debris environment and orbital safety.

Audio Tracking in Noisy Environments by Acoustic Map and Spectral Signature.

PubMed

Crocco, Marco; Martelli, Samuele; Trucco, Andrea; Zunino, Andrea; Murino, Vittorio

2018-05-01

A novel method is proposed for generic target tracking by audio measurements from a microphone array. To cope with noisy environments characterized by persistent and high energy interfering sources, a classification map (CM) based on spectral signatures is calculated by means of a machine learning algorithm. Next, the CM is combined with the acoustic map, describing the spatial distribution of sound energy, in order to obtain a cleaned joint map in which contributions from the disturbing sources are removed. A likelihood function is derived from this map and fed to a particle filter yielding the target location estimation on the acoustic image. The method is tested on two real environments, addressing both speaker and vehicle tracking. The comparison with a couple of trackers, relying on the acoustic map only, shows a sharp improvement in performance, paving the way to the application of audio tracking in real challenging environments.

Persistent spatial information in the FEF during object-based short-term memory does not contribute to task performance.

PubMed

Clark, Kelsey L; Noudoost, Behrad; Moore, Tirin

2014-06-01

We previously reported the existence of a persistent spatial signal in the FEF during object-based STM. This persistent activity reflected the location at which the sample appeared, irrespective of the location of upcoming targets. We hypothesized that such a spatial signal could be used to maintain or enhance object-selective memory activity elsewhere in cortex, analogous to the role of a spatial signal during attention. Here, we inactivated a portion of the FEF with GABAa agonist muscimol to test whether the observed activity contributes to object memory performance. We found that, although RTs were slowed for saccades into the inactivated portion of retinotopic space, performance for samples appearing in that region was unimpaired. This contrasts with the devastating effects of the same FEF inactivation on purely spatial working memory, as assessed with the memory-guided saccade task. Thus, in a task in which a significant fraction of FEF neurons displayed persistent, sample location-based activity, disrupting this activity had no impact on task performance.

Tracking and nowcasting convective precipitation cells at European scale for transregional warnings

NASA Astrophysics Data System (ADS)

Meyer, Vera; Tüchler, Lukas

2013-04-01

A transregional overview of the current weather situation is considered as highly valuable information to assist forecasters as well as official authorities for disaster management in their decision making processes. The development of the European-wide radar composite OPERA enables for the first time a coherent object-oriented tracking and nowcasting of intense precipitation cells in real time at continental scale and at a resolution of 2 x 2 km² and 15 minutes. Recently, the object-oriented cell-tracking tool A-TNT (Austrian Thunderstorm Nowcasting Tool) has been developed at ZAMG. A-TNT utilizes the method of ec-TRAM [1]. It consists of two autonomously operating routines, which identify, track and nowcast radar- and lightning-cells separately. The two independent outputs are combined to a coherent storm monitoring and nowcasting in a final step. Within the framework of HAREN (Hazard Assessment based on Rainfall European Nowcasts), which is a project funded by the EC Directorate General for Humanitarian Aid and Civil Protection, A-TNT has been adapted to OPERA radar data. The objective of HAREN is the support of forecasters and official authorities in their decision-making processes concerning precipitation induced hazards with pan-European information. This study will present (1) the general performance of the object-oriented approach for thunderstorm tracking and nowcasting on continental scale giving insight into its current capabilities and limitations and (2) the utilization of object-oriented cell information for automated precipitation warnings carried out within the framework of HAREN. Data collected from April to October 2012 are used to assess the performance of cell-tracking based on radar data. Furthermore, the benefit of additional lightning information provided by the European Cooperation for Lightning Detection (EUCLID) for thunderstorm tracking and nowcasting will be summarized in selected analyses. REFERENCES: [1] Meyer, V. K., H. Höller, and H. D. Betz 2012: Automated thunderstorm tracking and nowcasting: utilization of three-dimensional lightning and radar data. Manuscript accepted for publication in ACPD.

A Real Time AI Approach to Discrimination Boost Phase Optical Sensor Systems in SDI Architectures

NASA Astrophysics Data System (ADS)

Sloggett, David R.

1990-04-01

Interest has been rekindled in the potential utility of Ballistic Missile Defence (BMD) systems 1,2 and their ability to enhance the existing NATO strategic defence posture 3,4. Whereas in the past BMD systems have been thought to be vulnerable to relatively simple offence countermeasures, technological developments that have occurred over the past 20 years offer the potential to solve some of the main criticisms that have bedeviled BMD research since its inception in the early 1950s. One of the key areas where dramatic developments have taken place is in the field of electro-optic sensor technologies where developments in device sensitivity and packing density offer new solutions to threat detection, tracking and discrimination that complement data traditionally associated with radar based systems. Analysis has shown 5 that optical sensor systems can make a significant contribution to threat analysis in the boost and mid course phases of flight of ballistic missile systems. In the Boost phase the large amounts of energy contained within the plume of a ballistic missile system provides a signature that must be detected against cloud and earth backgrounds - necessitating viewing from space. The process of detection is complicated by reflected sunlight and other sources of false alarms. The optical sensor systems must therefore be adaptable and capable of reasoning about the location of the signatures, their persistence and temporal variations. Much of this processing is ideally carried out at the sensor system - in order to eliminate false alarms and reduce the communications bandwidths required to transfer the sensor data to centralised early warning and battle management facilities. In the mid course phase optical sensor systems can be used to detect warm objects against the background of deep space. These sensor systems can form tracks on these objects that can be merged into 3D tracks as data from individual sensor systems are combined. As closely spaced objects are resolved by sensor systems feature data can be extracted on individual objects that can be used by the defence system to attempt to discriminate between warheads, decoys and other penetration aids. This paper reviews work that has arisen from joint US SDIO and UK MOD research programmes into the feasibility of Theatre Missile Defence (TMD) systems that would be suitable for deploy ment and operation in a European theatre. The paper focuses on the problems of threat classification and discrimination in TtD systems and highlights the role of optical sensors. The paper discusses the integration of data derived from optical and radar sensors 6 and expands upon work previously reported into the use of an Artificial Intelligence (AI) approach to object classification and discrimination.

Using LabView for real-time monitoring and tracking of multiple biological objects

NASA Astrophysics Data System (ADS)

Nikolskyy, Aleksandr I.; Krasilenko, Vladimir G.; Bilynsky, Yosyp Y.; Starovier, Anzhelika

2017-04-01

Today real-time studying and tracking of movement dynamics of various biological objects is important and widely researched. Features of objects, conditions of their visualization and model parameters strongly influence the choice of optimal methods and algorithms for a specific task. Therefore, to automate the processes of adaptation of recognition tracking algorithms, several Labview project trackers are considered in the article. Projects allow changing templates for training and retraining the system quickly. They adapt to the speed of objects and statistical characteristics of noise in images. New functions of comparison of images or their features, descriptors and pre-processing methods will be discussed. The experiments carried out to test the trackers on real video files will be presented and analyzed.

Automatic Tracking Algorithm in Coaxial Near-Infrared Laser Ablation Endoscope for Fetus Surgery

NASA Astrophysics Data System (ADS)

Hu, Yan; Yamanaka, Noriaki; Masamune, Ken

2014-07-01

This article reports a stable vessel object tracking method for the treatment of twin-to-twin transfusion syndrome based on our previous 2 DOF endoscope. During the treatment of laser coagulation, it is necessary to focus on the exact position of the target object, however it moves by the mother's respiratory motion and still remains a challenge to obtain and track the position precisely. In this article, an algorithm which uses features from accelerated segment test (FAST) to extract the features and optical flow as the object tracking method, is proposed to deal with above problem. Further, we experimentally simulate the movement due to the mother's respiration, and the results of position errors and similarity verify the effectiveness of the proposed tracking algorithm for laser ablation endoscopy in-vitro and under water considering two influential factors. At average, the errors are about 10 pixels and the similarity over 0.92 are obtained in the experiments.

CTEPP OVERVIEW: A PILOT STUDY OF CHILDREN'S TOTAL EXPOSURE TO PERSISTENT PESTICIDES AND OTHER PERSISTENT ORGANIC POLLUTANTS

EPA Science Inventory

The research study, "Children's Total Exposure to Persistent Pesticides and Other Persistent Organic Pollutants," (CTEPP) is a pilot-scale project involving about 260 children in their everyday surroundings. The objectives of CTEPP are twofold: (1) To measure the agg...

Layered data association using graph-theoretic formulation with applications to tennis ball tracking in monocular sequences.

PubMed

Yan, Fei; Christmas, William; Kittler, Josef

2008-10-01

In this paper, we propose a multilayered data association scheme with graph-theoretic formulation for tracking multiple objects that undergo switching dynamics in clutter. The proposed scheme takes as input object candidates detected in each frame. At the object candidate level, "tracklets'' are "grown'' from sets of candidates that have high probabilities of containing only true positives. At the tracklet level, a directed and weighted graph is constructed, where each node is a tracklet, and the edge weight between two nodes is defined according to the "compatibility'' of the two tracklets. The association problem is then formulated as an all-pairs shortest path (APSP) problem in this graph. Finally, at the path level, by analyzing the APSPs, all object trajectories are identified, and track initiation and track termination are automatically dealt with. By exploiting a special topological property of the graph, we have also developed a more efficient APSP algorithm than the general-purpose ones. The proposed data association scheme is applied to tennis sequences to track tennis balls. Experiments show that it works well on sequences where other data association methods perform poorly or fail completely.

Tri-track: free software for large-scale particle tracking.

PubMed

Vallotton, Pascal; Olivier, Sandra

2013-04-01

The ability to correctly track objects in time-lapse sequences is important in many applications of microscopy. Individual object motions typically display a level of dynamic regularity reflecting the existence of an underlying physics or biology. Best results are obtained when this local information is exploited. Additionally, if the particle number is known to be approximately constant, a large number of tracking scenarios may be rejected on the basis that they are not compatible with a known maximum particle velocity. This represents information of a global nature, which should ideally be exploited too. Some time ago, we devised an efficient algorithm that exploited both types of information. The tracking task was reduced to a max-flow min-cost problem instance through a novel graph structure that comprised vertices representing objects from three consecutive image frames. The algorithm is explained here for the first time. A user-friendly implementation is provided, and the specific relaxation mechanism responsible for the method's effectiveness is uncovered. The software is particularly competitive for complex dynamics such as dense antiparallel flows, or in situations where object displacements are considerable. As an application, we characterize a remarkable vortex structure formed by bacteria engaged in interstitial motility.

Image Tracking for the High Similarity Drug Tablets Based on Light Intensity Reflective Energy and Artificial Neural Network

PubMed Central

Liang, Zhongwei; Zhou, Liang; Liu, Xiaochu; Wang, Xiaogang

2014-01-01

It is obvious that tablet image tracking exerts a notable influence on the efficiency and reliability of high-speed drug mass production, and, simultaneously, it also emerges as a big difficult problem and targeted focus during production monitoring in recent years, due to the high similarity shape and random position distribution of those objectives to be searched for. For the purpose of tracking tablets accurately in random distribution, through using surface fitting approach and transitional vector determination, the calibrated surface of light intensity reflective energy can be established, describing the shape topology and topography details of objective tablet. On this basis, the mathematical properties of these established surfaces have been proposed, and thereafter artificial neural network (ANN) has been employed for classifying those moving targeted tablets by recognizing their different surface properties; therefore, the instantaneous coordinate positions of those drug tablets on one image frame can then be determined. By repeating identical pattern recognition on the next image frame, the real-time movements of objective tablet templates were successfully tracked in sequence. This paper provides reliable references and new research ideas for the real-time objective tracking in the case of drug production practices. PMID:25143781

Robust multiple cue fusion-based high-speed and nonrigid object tracking algorithm for short track speed skating

NASA Astrophysics Data System (ADS)

Liu, Chenguang; Cheng, Heng-Da; Zhang, Yingtao; Wang, Yuxuan; Xian, Min

2016-01-01

This paper presents a methodology for tracking multiple skaters in short track speed skating competitions. Nonrigid skaters move at high speed with severe occlusions happening frequently among them. The camera is panned quickly in order to capture the skaters in a large and dynamic scene. To automatically track the skaters and precisely output their trajectories becomes a challenging task in object tracking. We employ the global rink information to compensate camera motion and obtain the global spatial information of skaters, utilize random forest to fuse multiple cues and predict the blob of each skater, and finally apply a silhouette- and edge-based template-matching and blob-evolving method to labelling pixels to a skater. The effectiveness and robustness of the proposed method are verified through thorough experiments.

Cross-Modal Attention Effects in the Vestibular Cortex during Attentive Tracking of Moving Objects.

PubMed

Frank, Sebastian M; Sun, Liwei; Forster, Lisa; Tse, Peter U; Greenlee, Mark W

2016-12-14

The midposterior fundus of the Sylvian fissure in the human brain is central to the cortical processing of vestibular cues. At least two vestibular areas are located at this site: the parietoinsular vestibular cortex (PIVC) and the posterior insular cortex (PIC). It is now well established that activity in sensory systems is subject to cross-modal attention effects. Attending to a stimulus in one sensory modality enhances activity in the corresponding cortical sensory system, but simultaneously suppresses activity in other sensory systems. Here, we wanted to probe whether such cross-modal attention effects also target the vestibular system. To this end, we used a visual multiple-object tracking task. By parametrically varying the number of tracked targets, we could measure the effect of attentional load on the PIVC and the PIC while holding the perceptual load constant. Participants performed the tracking task during functional magnetic resonance imaging. Results show that, compared with passive viewing of object motion, activity during object tracking was suppressed in the PIVC and enhanced in the PIC. Greater attentional load, induced by increasing the number of tracked targets, was associated with a corresponding increase in the suppression of activity in the PIVC. Activity in the anterior part of the PIC decreased with increasing load, whereas load effects were absent in the posterior PIC. Results of a control experiment show that attention-induced suppression in the PIVC is stronger than any suppression evoked by the visual stimulus per se. Overall, our results suggest that attention has a cross-modal modulatory effect on the vestibular cortex during visual object tracking. In this study we investigate cross-modal attention effects in the human vestibular cortex. We applied the visual multiple-object tracking task because it is known to evoke attentional load effects on neural activity in visual motion-processing and attention-processing areas. Here we demonstrate a load-dependent effect of attention on the activation in the vestibular cortex, despite constant visual motion stimulation. We find that activity in the parietoinsular vestibular cortex is more strongly suppressed the greater the attentional load on the visual tracking task. These findings suggest cross-modal attentional modulation in the vestibular cortex. Copyright © 2016 the authors 0270-6474/16/3612720-09$15.00/0.

A switched systems approach to image-based estimation

NASA Astrophysics Data System (ADS)

Parikh, Anup

With the advent of technological improvements in imaging systems and computational resources, as well as the development of image-based reconstruction techniques, it is necessary to understand algorithm performance when subject to real world conditions. Specifically, this dissertation focuses on the stability and performance of a class of image-based observers in the presence of intermittent measurements, caused by e.g., occlusions, limited FOV, feature tracking losses, communication losses, or finite frame rates. Observers or filters that are exponentially stable under persistent observability may have unbounded error growth during intermittent sensing, even while providing seemingly accurate state estimates. In Chapter 3, dwell time conditions are developed to guarantee state estimation error convergence to an ultimate bound for a class of observers while undergoing measurement loss. Bounds are developed on the unstable growth of the estimation errors during the periods when the object being tracked is not visible. A Lyapunov-based analysis for the switched system is performed to develop an inequality in terms of the duration of time the observer can view the moving object and the duration of time the object is out of the field of view. In Chapter 4, a motion model is used to predict the evolution of the states of the system while the object is not visible. This reduces the growth rate of the bounding function to an exponential and enables the use of traditional switched systems Lyapunov analysis techniques. The stability analysis results in an average dwell time condition to guarantee state error convergence with a known decay rate. In comparison with the results in Chapter 3, the estimation errors converge to zero rather than a ball, with relaxed switching conditions, at the cost of requiring additional information about the motion of the feature. In some applications, a motion model of the object may not be available. Numerous adaptive techniques have been developed to compensate for unknown parameters or functions in system dynamics; however, persistent excitation (PE) conditions are typically required to ensure parameter convergence, i.e., learning. Since the motion model is needed in the predictor, model learning is desired; however, PE is difficult to insure a priori and infeasible to check online for nonlinear systems. Concurrent learning (CL) techniques have been developed to use recorded data and a relaxed excitation condition to ensure convergence. In CL, excitation is only required for a finite period of time, and the recorded data can be checked to determine if it is sufficiently rich. However, traditional CL requires knowledge of state derivatives, which are typically not measured and require extensive filter design and tuning to develop satisfactory estimates. In Chapter 5 of this dissertation, a novel formulation of CL is developed in terms of an integral (ICL), removing the need to estimate state derivatives while preserving parameter convergence properties. Using ICL, an estimator is developed in Chapter 6 for simultaneously estimating the pose of an object as well as learning a model of its motion for use in a predictor when the object is not visible. A switched systems analysis is provided to demonstrate the stability of the estimation and prediction with learning scheme. Dwell time conditions as well as excitation conditions are developed to ensure estimation errors converge to an arbitrarily small bound. Experimental results are provided to illustrate the performance of each of the developed estimation schemes. The dissertation concludes with a discussion of the contributions and limitations of the developed techniques, as well as avenues for future extensions.

Security Applications Of Computer Motion Detection

NASA Astrophysics Data System (ADS)

Bernat, Andrew P.; Nelan, Joseph; Riter, Stephen; Frankel, Harry

1987-05-01

An important area of application of computer vision is the detection of human motion in security systems. This paper describes the development of a computer vision system which can detect and track human movement across the international border between the United States and Mexico. Because of the wide range of environmental conditions, this application represents a stringent test of computer vision algorithms for motion detection and object identification. The desired output of this vision system is accurate, real-time locations for individual aliens and accurate statistical data as to the frequency of illegal border crossings. Because most detection and tracking routines assume rigid body motion, which is not characteristic of humans, new algorithms capable of reliable operation in our application are required. Furthermore, most current detection and tracking algorithms assume a uniform background against which motion is viewed - the urban environment along the US-Mexican border is anything but uniform. The system works in three stages: motion detection, object tracking and object identi-fication. We have implemented motion detection using simple frame differencing, maximum likelihood estimation, mean and median tests and are evaluating them for accuracy and computational efficiency. Due to the complex nature of the urban environment (background and foreground objects consisting of buildings, vegetation, vehicles, wind-blown debris, animals, etc.), motion detection alone is not sufficiently accurate. Object tracking and identification are handled by an expert system which takes shape, location and trajectory information as input and determines if the moving object is indeed representative of an illegal border crossing.

Good Features to Correlate for Visual Tracking

NASA Astrophysics Data System (ADS)

Gundogdu, Erhan; Alatan, A. Aydin

2018-05-01

During the recent years, correlation filters have shown dominant and spectacular results for visual object tracking. The types of the features that are employed in these family of trackers significantly affect the performance of visual tracking. The ultimate goal is to utilize robust features invariant to any kind of appearance change of the object, while predicting the object location as properly as in the case of no appearance change. As the deep learning based methods have emerged, the study of learning features for specific tasks has accelerated. For instance, discriminative visual tracking methods based on deep architectures have been studied with promising performance. Nevertheless, correlation filter based (CFB) trackers confine themselves to use the pre-trained networks which are trained for object classification problem. To this end, in this manuscript the problem of learning deep fully convolutional features for the CFB visual tracking is formulated. In order to learn the proposed model, a novel and efficient backpropagation algorithm is presented based on the loss function of the network. The proposed learning framework enables the network model to be flexible for a custom design. Moreover, it alleviates the dependency on the network trained for classification. Extensive performance analysis shows the efficacy of the proposed custom design in the CFB tracking framework. By fine-tuning the convolutional parts of a state-of-the-art network and integrating this model to a CFB tracker, which is the top performing one of VOT2016, 18% increase is achieved in terms of expected average overlap, and tracking failures are decreased by 25%, while maintaining the superiority over the state-of-the-art methods in OTB-2013 and OTB-2015 tracking datasets.

Durability of Multi-Track Year-Round Elementary School Principals.

ERIC Educational Resources Information Center

Borba, John A.

2000-01-01

A followup study surveyed 79 principals of year-round, multitrack California elementary schools. YRE principal persistence between 1993 and 1998 was lower than that of counterparts in traditional-schedule schools. YRE schools need increased administrative support; their principals need stress management strategies. (Contains 14 references.) (MLH)

Automatic feature-based grouping during multiple object tracking.

PubMed

Erlikhman, Gennady; Keane, Brian P; Mettler, Everett; Horowitz, Todd S; Kellman, Philip J

2013-12-01

Contour interpolation automatically binds targets with distractors to impair multiple object tracking (Keane, Mettler, Tsoi, & Kellman, 2011). Is interpolation special in this regard or can other features produce the same effect? To address this question, we examined the influence of eight features on tracking: color, contrast polarity, orientation, size, shape, depth, interpolation, and a combination (shape, color, size). In each case, subjects tracked 4 of 8 objects that began as undifferentiated shapes, changed features as motion began (to enable grouping), and returned to their undifferentiated states before halting. We found that intertarget grouping improved performance for all feature types except orientation and interpolation (Experiment 1 and Experiment 2). Most importantly, target-distractor grouping impaired performance for color, size, shape, combination, and interpolation. The impairments were, at times, large (>15% decrement in accuracy) and occurred relative to a homogeneous condition in which all objects had the same features at each moment of a trial (Experiment 2), and relative to a "diversity" condition in which targets and distractors had different features at each moment (Experiment 3). We conclude that feature-based grouping occurs for a variety of features besides interpolation, even when irrelevant to task instructions and contrary to the task demands, suggesting that interpolation is not unique in promoting automatic grouping in tracking tasks. Our results also imply that various kinds of features are encoded automatically and in parallel during tracking.

Spatial and visuospatial working memory tests predict performance in classic multiple-object tracking in young adults, but nonspatial measures of the executive do not.

PubMed

Trick, Lana M; Mutreja, Rachna; Hunt, Kelly

2012-02-01

An individual-differences approach was used to investigate the roles of visuospatial working memory and the executive in multiple-object tracking. The Corsi Blocks and Visual Patterns Tests were used to assess visuospatial working memory. Two relatively nonspatial measures of the executive were used: operation span (OSPAN) and reading span (RSPAN). For purposes of comparison, the digit span test was also included (a measure not expected to correlate with tracking). The tests predicted substantial amounts of variance (R (2) = .33), and the visuospatial measures accounted for the majority (R (2) = .30), with each making a significant contribution. Although the executive measures correlated with each other, the RSPAN did not correlate with tracking. The correlation between OSPAN and tracking was similar in magnitude to that between digit span and tracking (p < .05 for both), and when regression was used to partial out shared variance between the two tests, the remaining variance predicted by the OSPAN was minimal (sr ( 2 ) = .029). When measures of spatial memory were included in the regression, the unique variance predicted by the OSPAN became negligible (sr ( 2 ) = .000004). This suggests that the executive, as measured by tests such as the OSPAN, plays little role in explaining individual differences in multiple-object tracking.

Do Algorithms Homogenize Students' Achievements in Secondary School Better than Teachers' Tracking Decisions?

ERIC Educational Resources Information Center

Klapproth, Florian

2015-01-01

Two objectives guided this research. First, this study examined how well teachers' tracking decisions contribute to the homogenization of their students' achievements. Second, the study explored whether teachers' tracking decisions would be outperformed in homogenizing the students' achievements by statistical models of tracking decisions. These…

Information Measures for Statistical Orbit Determination

ERIC Educational Resources Information Center

Mashiku, Alinda K.

2013-01-01

The current Situational Space Awareness (SSA) is faced with a huge task of tracking the increasing number of space objects. The tracking of space objects requires frequent and accurate monitoring for orbit maintenance and collision avoidance using methods for statistical orbit determination. Statistical orbit determination enables us to obtain…

Determination of feature generation methods for PTZ camera object tracking

NASA Astrophysics Data System (ADS)

Doyle, Daniel D.; Black, Jonathan T.

2012-06-01

Object detection and tracking using computer vision (CV) techniques have been widely applied to sensor fusion applications. Many papers continue to be written that speed up performance and increase learning of artificially intelligent systems through improved algorithms, workload distribution, and information fusion. Military application of real-time tracking systems is becoming more and more complex with an ever increasing need of fusion and CV techniques to actively track and control dynamic systems. Examples include the use of metrology systems for tracking and measuring micro air vehicles (MAVs) and autonomous navigation systems for controlling MAVs. This paper seeks to contribute to the determination of select tracking algorithms that best track a moving object using a pan/tilt/zoom (PTZ) camera applicable to both of the examples presented. The select feature generation algorithms compared in this paper are the trained Scale-Invariant Feature Transform (SIFT) and Speeded Up Robust Features (SURF), the Mixture of Gaussians (MoG) background subtraction method, the Lucas- Kanade optical flow method (2000) and the Farneback optical flow method (2003). The matching algorithm used in this paper for the trained feature generation algorithms is the Fast Library for Approximate Nearest Neighbors (FLANN). The BSD licensed OpenCV library is used extensively to demonstrate the viability of each algorithm and its performance. Initial testing is performed on a sequence of images using a stationary camera. Further testing is performed on a sequence of images such that the PTZ camera is moving in order to capture the moving object. Comparisons are made based upon accuracy, speed and memory.

Object Occlusion Detection Using Automatic Camera Calibration for a Wide-Area Video Surveillance System

PubMed Central

Jung, Jaehoon; Yoon, Inhye; Paik, Joonki

2016-01-01

This paper presents an object occlusion detection algorithm using object depth information that is estimated by automatic camera calibration. The object occlusion problem is a major factor to degrade the performance of object tracking and recognition. To detect an object occlusion, the proposed algorithm consists of three steps: (i) automatic camera calibration using both moving objects and a background structure; (ii) object depth estimation; and (iii) detection of occluded regions. The proposed algorithm estimates the depth of the object without extra sensors but with a generic red, green and blue (RGB) camera. As a result, the proposed algorithm can be applied to improve the performance of object tracking and object recognition algorithms for video surveillance systems. PMID:27347978

Probabilistic multi-person localisation and tracking in image sequences

NASA Astrophysics Data System (ADS)

Klinger, T.; Rottensteiner, F.; Heipke, C.

2017-05-01

The localisation and tracking of persons in image sequences in commonly guided by recursive filters. Especially in a multi-object tracking environment, where mutual occlusions are inherent, the predictive model is prone to drift away from the actual target position when not taking context into account. Further, if the image-based observations are imprecise, the trajectory is prone to be updated towards a wrong position. In this work we address both these problems by using a new predictive model on the basis of Gaussian Process Regression, and by using generic object detection, as well as instance-specific classification, for refined localisation. The predictive model takes into account the motion of every tracked pedestrian in the scene and the prediction is executed with respect to the velocities of neighbouring persons. In contrast to existing methods our approach uses a Dynamic Bayesian Network in which the state vector of a recursive Bayes filter, as well as the location of the tracked object in the image, are modelled as unknowns. This allows the detection to be corrected before it is incorporated into the recursive filter. Our method is evaluated on a publicly available benchmark dataset and outperforms related methods in terms of geometric precision and tracking accuracy.

Optical joint correlator for real-time image tracking and retinal surgery

NASA Technical Reports Server (NTRS)

Juday, Richard D. (Inventor)

1991-01-01

A method for tracking an object in a sequence of images is described. Such sequence of images may, for example, be a sequence of television frames. The object in the current frame is correlated with the object in the previous frame to obtain the relative location of the object in the two frames. An optical joint transform correlator apparatus is provided to carry out the process. Such joint transform correlator apparatus forms the basis for laser eye surgical apparatus where an image of the fundus of an eyeball is stabilized and forms the basis for the correlator apparatus to track the position of the eyeball caused by involuntary movement. With knowledge of the eyeball position, a surgical laser can be precisely pointed toward a position on the retina.

Design and implementation of a vision-based hovering and feature tracking algorithm for a quadrotor

NASA Astrophysics Data System (ADS)

Lee, Y. H.; Chahl, J. S.

2016-10-01

This paper demonstrates an approach to the vision-based control of the unmanned quadrotors for hover and object tracking. The algorithms used the Speed Up Robust Features (SURF) algorithm to detect objects. The pose of the object in the image was then calculated in order to pass the pose information to the flight controller. Finally, the flight controller steered the quadrotor to approach the object based on the calculated pose data. The above processes was run using standard onboard resources found in the 3DR Solo quadrotor in an embedded computing environment. The obtained results showed that the algorithm behaved well during its missions, tracking and hovering, although there were significant latencies due to low CPU performance of the onboard image processing system.

An Information Infrastructure for Enrollment Management: Tracking and Understanding Your Students.

ERIC Educational Resources Information Center

Clagett, Craig A.; Kerr, Helen S.

Enrollment management is defined as coordinated effort to influence the size and characteristics of an institution's student body through recruitment, admissions, pricing, financial aid, advising, and other policy choices. Enrollment managers must understand the forces that influence individual decisions about college choice and persistence. One…

Keystone Method: A Learning Paradigm in Mathematics

ERIC Educational Resources Information Center

Siadat, M. Vali; Musial, Paul M.; Sagher, Yoram

2008-01-01

This study reports the effects of an integrated instructional program (the Keystone Method) on the students' performance in mathematics and reading, and tracks students' persistence and retention. The subject of the study was a large group of students in remedial mathematics classes at the college, willing to learn but lacking basic educational…

Get Started and Write: Advice for New Faculty

ERIC Educational Resources Information Center

Smith, M. Cecil

2017-01-01

This paper describes several strategies for organizing, collaborating on, persisting in, and funding professional writing activities that can benefit new tenure track faculty members. Establishing and maintaining a regular program of academic writing is essential to a successful career in higher education, but initiating and maintaining a program…

75 FR 38994 - Office of Postsecondary Education; Overview Information Native American-Serving Nontribal...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-07-07

... undergraduate students that is at least 10 percent Native American at the time of application for a grant; and... students. Invitational Priority 3. Support activities that will improve the institution's persistence and... using State longitudinal data systems to track outcomes for students attending the grantee institution...

Biotic interactions and sunlight affect persistence of fecal indicator bacteria and microbial source tracking genetic markers in the Upper Mississippi River

EPA Science Inventory

Sanitary quality of recreational waters is assessed by enumerating fecal indicator bacteria (FIB) (Escherichia coli and enterococci); organisms present in the gastrointestinal tract of humans and many other animals, hence providing no information about the pollution source. Micro...

Representing Energy. II. Energy Tracking Representations

ERIC Educational Resources Information Center

Scherr, Rachel E.; Close, Hunter G.; Close, Eleanor W.; Vokos, Stamatis

2012-01-01

The Energy Project at Seattle Pacific University has developed representations that embody the substance metaphor and support learners in conserving and tracking energy as it flows from object to object and changes form. Such representations enable detailed modeling of energy dynamics in complex physical processes. We assess student learning by…

Visual perception system and method for a humanoid robot

NASA Technical Reports Server (NTRS)

Chelian, Suhas E. (Inventor); Linn, Douglas Martin (Inventor); Wampler, II, Charles W. (Inventor); Bridgwater, Lyndon (Inventor); Wells, James W. (Inventor); Mc Kay, Neil David (Inventor)

2012-01-01

A robotic system includes a humanoid robot with robotic joints each moveable using an actuator(s), and a distributed controller for controlling the movement of each of the robotic joints. The controller includes a visual perception module (VPM) for visually identifying and tracking an object in the field of view of the robot under threshold lighting conditions. The VPM includes optical devices for collecting an image of the object, a positional extraction device, and a host machine having an algorithm for processing the image and positional information. The algorithm visually identifies and tracks the object, and automatically adapts an exposure time of the optical devices to prevent feature data loss of the image under the threshold lighting conditions. A method of identifying and tracking the object includes collecting the image, extracting positional information of the object, and automatically adapting the exposure time to thereby prevent feature data loss of the image.

Direction information in multiple object tracking is limited by a graded resource.

PubMed

Horowitz, Todd S; Cohen, Michael A

2010-10-01

Is multiple object tracking (MOT) limited by a fixed set of structures (slots), a limited but divisible resource, or both? Here, we answer this question by measuring the precision of the direction representation for tracked targets. The signature of a limited resource is a decrease in precision as the square root of the tracking load. The signature of fixed slots is a fixed precision. Hybrid models predict a rapid decrease to asymptotic precision. In two experiments, observers tracked moving disks and reported target motion direction by adjusting a probe arrow. We derived the precision of representation of correctly tracked targets using a mixture distribution analysis. Precision declined with target load according to the square-root law up to six targets. This finding is inconsistent with both pure and hybrid slot models. Instead, directional information in MOT appears to be limited by a continuously divisible resource.

Real-time optical holographic tracking of multiple objects

NASA Technical Reports Server (NTRS)

Chao, Tien-Hsin; Liu, Hua-Kuang

1989-01-01

A coherent optical correlation technique for real-time simultaneous tracking of several different objects making independent movements is described, and experimental results are presented. An evaluation of this system compared with digital computing systems is made. The real-time processing capability is obtained through the use of a liquid crystal television spatial light modulator and a dichromated gelatin multifocus hololens. A coded reference beam is utilized in the separation of the output correlation plane associated with each input target so that independent tracking can be achieved.

Tracking Object Existence From an Autonomous Patrol Vehicle

NASA Technical Reports Server (NTRS)

Wolf, Michael; Scharenbroich, Lucas

2011-01-01

An autonomous vehicle patrols a large region, during which an algorithm receives measurements of detected potential objects within its sensor range. The goal of the algorithm is to track all objects in the region over time. This problem differs from traditional multi-target tracking scenarios because the region of interest is much larger than the sensor range and relies on the movement of the sensor through this region for coverage. The goal is to know whether anything has changed between visits to the same location. In particular, two kinds of alert conditions must be detected: (1) a previously detected object has disappeared and (2) a new object has appeared in a location already checked. For the time an object is within sensor range, the object can be assumed to remain stationary, changing position only between visits. The problem is difficult because the upstream object detection processing is likely to make many errors, resulting in heavy clutter (false positives) and missed detections (false negatives), and because only noisy, bearings-only measurements are available. This work has three main goals: (1) Associate incoming measurements with known objects or mark them as new objects or false positives, as appropriate. For this, a multiple hypothesis tracker was adapted to this scenario. (2) Localize the objects using multiple bearings-only measurements to provide estimates of global position (e.g., latitude and longitude). A nonlinear Kalman filter extension provides these 2D position estimates using the 1D measurements. (3) Calculate the probability that a suspected object truly exists (in the estimated position), and determine whether alert conditions have been triggered (for new objects or disappeared objects). The concept of a probability of existence was created, and a new Bayesian method for updating this probability at each time step was developed. A probabilistic multiple hypothesis approach is chosen because of its superiority in handling the uncertainty arising from errors in sensors and upstream processes. However, traditional target tracking methods typically assume a stationary detection volume of interest, whereas in this case, one must make adjustments for being able to see only a small portion of the region of interest and understand when an alert situation has occurred. To track object existence inside and outside the vehicle's sensor range, a probability of existence was defined for each hypothesized object, and this value was updated at every time step in a Bayesian manner based on expected characteristics of the sensor and object and whether that object has been detected in the most recent time step. Then, this value feeds into a sequential probability ratio test (SPRT) to determine the status of the object (suspected, confirmed, or deleted). Alerts are sent upon selected status transitions. Additionally, in order to track objects that move in and out of sensor range and update the probability of existence appropriately a variable probability detection has been defined and the hypothesis probability equations have been re-derived to accommodate this change. Unsupervised object tracking is a pervasive issue in automated perception systems. This work could apply to any mobile platform (ground vehicle, sea vessel, air vehicle, or orbiter) that intermittently revisits regions of interest and needs to determine whether anything interesting has changed.

Wireless sensor networks for heritage object deformation detection and tracking algorithm.

PubMed

Xie, Zhijun; Huang, Guangyan; Zarei, Roozbeh; He, Jing; Zhang, Yanchun; Ye, Hongwu

2014-10-31

Deformation is the direct cause of heritage object collapse. It is significant to monitor and signal the early warnings of the deformation of heritage objects. However, traditional heritage object monitoring methods only roughly monitor a simple-shaped heritage object as a whole, but cannot monitor complicated heritage objects, which may have a large number of surfaces inside and outside. Wireless sensor networks, comprising many small-sized, low-cost, low-power intelligent sensor nodes, are more useful to detect the deformation of every small part of the heritage objects. Wireless sensor networks need an effective mechanism to reduce both the communication costs and energy consumption in order to monitor the heritage objects in real time. In this paper, we provide an effective heritage object deformation detection and tracking method using wireless sensor networks (EffeHDDT). In EffeHDDT, we discover a connected core set of sensor nodes to reduce the communication cost for transmitting and collecting the data of the sensor networks. Particularly, we propose a heritage object boundary detecting and tracking mechanism. Both theoretical analysis and experimental results demonstrate that our EffeHDDT method outperforms the existing methods in terms of network traffic and the precision of the deformation detection.

Wireless Sensor Networks for Heritage Object Deformation Detection and Tracking Algorithm

PubMed Central

Xie, Zhijun; Huang, Guangyan; Zarei, Roozbeh; He, Jing; Zhang, Yanchun; Ye, Hongwu

2014-01-01

Deformation is the direct cause of heritage object collapse. It is significant to monitor and signal the early warnings of the deformation of heritage objects. However, traditional heritage object monitoring methods only roughly monitor a simple-shaped heritage object as a whole, but cannot monitor complicated heritage objects, which may have a large number of surfaces inside and outside. Wireless sensor networks, comprising many small-sized, low-cost, low-power intelligent sensor nodes, are more useful to detect the deformation of every small part of the heritage objects. Wireless sensor networks need an effective mechanism to reduce both the communication costs and energy consumption in order to monitor the heritage objects in real time. In this paper, we provide an effective heritage object deformation detection and tracking method using wireless sensor networks (EffeHDDT). In EffeHDDT, we discover a connected core set of sensor nodes to reduce the communication cost for transmitting and collecting the data of the sensor networks. Particularly, we propose a heritage object boundary detecting and tracking mechanism. Both theoretical analysis and experimental results demonstrate that our EffeHDDT method outperforms the existing methods in terms of network traffic and the precision of the deformation detection. PMID:25365458

Actin-based motility propelled by molecular motors

NASA Astrophysics Data System (ADS)

Upadyayula, Sai Pramod; Rangarajan, Murali

2012-09-01

Actin-based motility of Listeria monocytogenes propelled by filament end-tracking molecular motors has been simulated. Such systems may act as potential nanoscale actuators and shuttles useful in sorting and sensing biomolecules. Filaments are modeled as three-dimensional elastic springs distributed on one end of the capsule and persistently attached to the motile bacterial surface through an end-tracking motor complex. Filament distribution is random, and monomer concentration decreases linearly as a function of position on the bacterial surface. Filament growth rate increases with monomer concentration but decreases with the extent of compression. The growing filaments exert push-pull forces on the bacterial surface. In addition to forces, torques arise due to two factors—distribution of motors on the bacterial surface, and coupling of torsion upon growth due to the right-handed helicity of F-actin—causing the motile object to undergo simultaneous translation and rotation. The trajectory of the bacterium is simulated by performing a force and torque balance on the bacterium. All simulations use a fixed value of torsion. Simulations show strong alignment of the filaments and the long axis of the bacterium along the direction of motion. In the absence of torsion, the bacterial surface essentially moves along the direction of the long axis. When a small amount of the torsion is applied to the bacterial surface, the bacterium is seen to move in right-handed helical trajectories, consistent with experimental observations.

Method for targetless tracking subpixel in-plane movements.

PubMed

Espinosa, Julian; Perez, Jorge; Ferrer, Belen; Mas, David

2015-09-01

We present a targetless motion tracking method for detecting planar movements with subpixel accuracy. This method is based on the computation and tracking of the intersection of two nonparallel straight-line segments in the image of a moving object in a scene. The method is simple and easy to implement because no complex structures have to be detected. It has been tested and validated using a lab experiment consisting of a vibrating object that was recorded with a high-speed camera working at 1000 fps. We managed to track displacements with an accuracy of hundredths of pixel or even of thousandths of pixel in the case of tracking harmonic vibrations. The method is widely applicable because it can be used for distance measuring amplitude and frequency of vibrations with a vision system.

Approaches, field considerations and problems associated with radio tracking carnivores

USGS Publications Warehouse

Sargeant, A.B.; Amlaner, C. J.; MacDonald, D.W.

1979-01-01

The adaptation of radio tracking to ecological studies was a major technological advance affecting field investigations of animal movements and behavior. Carnivores have been the recipients of much attention with this new technology and study approaches have varied from simple to complex. Equipment performance has much improved over the years, but users still face many difficulties. The beginning of all radio tracking studies should be a precise definition of objectives. Study objectives dictate type of gear required and field procedures. Field conditions affect equipment performance and investigator ability to gather data. Radio tracking carnivores is demanding and generally requires greater time than anticipated. Problems should be expected and planned for in study design. Radio tracking can be an asset in carnivore studies but caution is needed in its application.

Evaluation of the fidelity of feature descriptor-based specimen tracking for automatic NDE data integration

NASA Astrophysics Data System (ADS)

Radkowski, Rafael; Holland, Stephen; Grandin, Robert

2018-04-01

This research addresses inspection location tracking in the field of nondestructive evaluation (NDE) using a computer vision technique to determine the position and orientation of typical NDE equipment in a test setup. The objective is the tracking accuracy for typical NDE equipment to facilitate automatic NDE data integration. Since the employed tracking technique relies on surface curvatures of an object of interest, the accuracy can be only experimentally determined. We work with flash-thermography and conducted an experiment in which we tracked a specimen and a thermography flash hood, measured the spatial relation between both, and used the relation as input to map thermography data onto a 3D model of the specimen. The results indicate an appropriate accuracy, however, unveiled calibration challenges.

Vision-based object detection and recognition system for intelligent vehicles

NASA Astrophysics Data System (ADS)

Ran, Bin; Liu, Henry X.; Martono, Wilfung

1999-01-01

Recently, a proactive crash mitigation system is proposed to enhance the crash avoidance and survivability of the Intelligent Vehicles. Accurate object detection and recognition system is a prerequisite for a proactive crash mitigation system, as system component deployment algorithms rely on accurate hazard detection, recognition, and tracking information. In this paper, we present a vision-based approach to detect and recognize vehicles and traffic signs, obtain their information, and track multiple objects by using a sequence of color images taken from a moving vehicle. The entire system consist of two sub-systems, the vehicle detection and recognition sub-system and traffic sign detection and recognition sub-system. Both of the sub- systems consist of four models: object detection model, object recognition model, object information model, and object tracking model. In order to detect potential objects on the road, several features of the objects are investigated, which include symmetrical shape and aspect ratio of a vehicle and color and shape information of the signs. A two-layer neural network is trained to recognize different types of vehicles and a parameterized traffic sign model is established in the process of recognizing a sign. Tracking is accomplished by combining the analysis of single image frame with the analysis of consecutive image frames. The analysis of the single image frame is performed every ten full-size images. The information model will obtain the information related to the object, such as time to collision for the object vehicle and relative distance from the traffic sings. Experimental results demonstrated a robust and accurate system in real time object detection and recognition over thousands of image frames.

Space debris tracking based on fuzzy running Gaussian average adaptive particle filter track-before-detect algorithm

NASA Astrophysics Data System (ADS)

Torteeka, Peerapong; Gao, Peng-Qi; Shen, Ming; Guo, Xiao-Zhang; Yang, Da-Tao; Yu, Huan-Huan; Zhou, Wei-Ping; Zhao, You

2017-02-01

Although tracking with a passive optical telescope is a powerful technique for space debris observation, it is limited by its sensitivity to dynamic background noise. Traditionally, in the field of astronomy, static background subtraction based on a median image technique has been used to extract moving space objects prior to the tracking operation, as this is computationally efficient. The main disadvantage of this technique is that it is not robust to variable illumination conditions. In this article, we propose an approach for tracking small and dim space debris in the context of a dynamic background via one of the optical telescopes that is part of the space surveillance network project, named the Asia-Pacific ground-based Optical Space Observation System or APOSOS. The approach combines a fuzzy running Gaussian average for robust moving-object extraction with dim-target tracking using a particle-filter-based track-before-detect method. The performance of the proposed algorithm is experimentally evaluated, and the results show that the scheme achieves a satisfactory level of accuracy for space debris tracking.

Interactive Multiple Object Tracking (iMOT)

PubMed Central

Thornton, Ian M.; Bülthoff, Heinrich H.; Horowitz, Todd S.; Rynning, Aksel; Lee, Seong-Whan

2014-01-01

We introduce a new task for exploring the relationship between action and attention. In this interactive multiple object tracking (iMOT) task, implemented as an iPad app, participants were presented with a display of multiple, visually identical disks which moved independently. The task was to prevent any collisions during a fixed duration. Participants could perturb object trajectories via the touchscreen. In Experiment 1, we used a staircase procedure to measure the ability to control moving objects. Object speed was set to 1°/s. On average participants could control 8.4 items without collision. Individual control strategies were quite variable, but did not predict overall performance. In Experiment 2, we compared iMOT with standard MOT performance using identical displays. Object speed was set to 2°/s. Participants could reliably control more objects (M = 6.6) than they could track (M = 4.0), but performance in the two tasks was positively correlated. In Experiment 3, we used a dual-task design. Compared to single-task baseline, iMOT performance decreased and MOT performance increased when the two tasks had to be completed together. Overall, these findings suggest: 1) There is a clear limit to the number of items that can be simultaneously controlled, for a given speed and display density; 2) participants can control more items than they can track; 3) task-relevant action appears not to disrupt MOT performance in the current experimental context. PMID:24498288

NanoDesign: Concepts and Software for a Nanotechnology Based on Functionalized Fullerenes

NASA Technical Reports Server (NTRS)

Globus, Al; Jaffe, Richard; Chancellor, Marisa K. (Technical Monitor)

1996-01-01

Eric Drexler has proposed a hypothetical nanotechnology based on diamond and investigated the properties of such molecular systems. While attractive, diamonoid nanotechnology is not physically accessible with straightforward extensions of current laboratory techniques. We propose a nanotechnology based on functionalized fullerenes and investigate carbon nanotube based gears with teeth added via a benzyne reaction known to occur with C60. The gears are single-walled carbon nanotubes with appended coenzyme groups for teeth. Fullerenes are in widespread laboratory use and can be functionalized in many ways. Companion papers computationally demonstrate the properties of these gears (they appear to work) and the accessibility of the benzyne/nanotube reaction. This paper describes the molecular design techniques and rationale as well as the software that implements these design techniques. The software is a set of persistent C++ objects controlled by TCL command scripts. The c++/tcl interface is automatically generated by a software system called tcl_c++ developed by the author and described here. The objects keep track of different portions of the molecular machinery to allow different simulation techniques and boundary conditions to be applied as appropriate. This capability has been required to demonstrate (computationally) our gear's feasibility. A new distributed software architecture featuring a WWW universal client, CORBA distributed objects, and agent software is under consideration. The software architecture is intended to eventually enable a widely disbursed group to develop complex simulated molecular machines.

Active illuminated space object imaging and tracking simulation

NASA Astrophysics Data System (ADS)

Yue, Yufang; Xie, Xiaogang; Luo, Wen; Zhang, Feizhou; An, Jianzhu

2016-10-01

Optical earth imaging simulation of a space target in orbit and it's extraction in laser illumination condition were discussed. Based on the orbit and corresponding attitude of a satellite, its 3D imaging rendering was built. General simulation platform was researched, which was adaptive to variable 3D satellite models and relative position relationships between satellite and earth detector system. Unified parallel projection technology was proposed in this paper. Furthermore, we denoted that random optical distribution in laser-illuminated condition was a challenge for object discrimination. Great randomicity of laser active illuminating speckles was the primary factor. The conjunction effects of multi-frame accumulation process and some tracking methods such as Meanshift tracking, contour poid, and filter deconvolution were simulated. Comparison of results illustrates that the union of multi-frame accumulation and contour poid was recommendable for laser active illuminated images, which had capacities of high tracking precise and stability for multiple object attitudes.

Single-organelle tracking by two-photon conversion

NASA Astrophysics Data System (ADS)

Watanabe, Wataru; Shimada, Tomoko; Matsunaga, Sachihiro; Kurihara, Daisuke; Fukui, Kiichi; Shin-Ichi Arimura, Shin-Ichi; Tsutsumi, Nobuhiro; Isobe, Keisuke; Itoh, Kazuyoshi

2007-03-01

Spatial and temporal information about intracellular objects and their dynamics within a living cell are essential for dynamic analysis of such objects in cell biology. A specific intracellular object can be discriminated by photoactivatable fluorescent proteins that exhibit pronounced light-induced spectral changes. Here, we report on selective labeling and tracking of a single organelle by using two-photon conversion of a photoconvertible fluorescent protein with near-infrared femtosecond laser pulses. We performed selective labeling of a single mitochondrion in a living tobacco BY-2 cell using two-photon photoconversion of Kaede. Using this technique, we demonstrated that, in plants, the directed movement of individual mitochondria along the cytoskeletons was mediated by actin filaments, whereas microtubules were not required for the movement of mitochondria. This single-organelle labeling technique enabled us to track the dynamics of a single organelle, revealing the mechanisms involved in organelle dynamics. The technique has potential application in direct tracking of selective cellular and intracellular structures.

Doublet Pulse Coherent Laser Radar for Tracking of Resident Space Objects

NASA Technical Reports Server (NTRS)

Prasad, Narasimha S.; Rudd, Van; Shald, Scott; Sandford, Stephen; Dimarcantonio, Albert

2014-01-01

In this paper, the development of a long range ladar system known as ExoSPEAR at NASA Langley Research Center for tracking rapidly moving resident space objects is discussed. Based on 100 W, nanosecond class, near-IR laser, this ladar system with coherent detection technique is currently being investigated for short dwell time measurements of resident space objects (RSOs) in LEO and beyond for space surveillance applications. This unique ladar architecture is configured using a continuously agile doublet-pulse waveform scheme coupled to a closed-loop tracking and control loop approach to simultaneously achieve mm class range precision and mm/s velocity precision and hence obtain unprecedented track accuracies. Salient features of the design architecture followed by performance modeling and engagement simulations illustrating the dependence of range and velocity precision in LEO orbits on ladar parameters are presented. Estimated limits on detectable optical cross sections of RSOs in LEO orbits are discussed.

One-single physical exercise session after object recognition learning promotes memory persistence through hippocampal noradrenergic mechanisms.

PubMed

da Silva de Vargas, Liane; Neves, Ben-Hur Souto das; Roehrs, Rafael; Izquierdo, Iván; Mello-Carpes, Pâmela

2017-06-30

Previously we showed the involvement of the hippocampal noradrenergic system in the consolidation and persistence of object recognition (OR) memory. Here we show that one-single physical exercise session performed immediately after learning promotes OR memory persistence and increases norepinephrine levels in the hippocampus. Additionally, effects of exercise on memory are avoided by an intra-hippocampal beta-adrenergic antagonist infusion. Taken together, these results suggest that exercise effects on memory can be related to noradrenergic mechanisms and acute physical exercise can be a non-pharmacological intervention to assist memory consolidation and persistence, with few or no side effects. Copyright © 2017 Elsevier B.V. All rights reserved.

Convolutional Deep Belief Networks for Single-Cell/Object Tracking in Computational Biology and Computer Vision.

PubMed

Zhong, Bineng; Pan, Shengnan; Zhang, Hongbo; Wang, Tian; Du, Jixiang; Chen, Duansheng; Cao, Liujuan

2016-01-01

In this paper, we propose deep architecture to dynamically learn the most discriminative features from data for both single-cell and object tracking in computational biology and computer vision. Firstly, the discriminative features are automatically learned via a convolutional deep belief network (CDBN). Secondly, we design a simple yet effective method to transfer features learned from CDBNs on the source tasks for generic purpose to the object tracking tasks using only limited amount of training data. Finally, to alleviate the tracker drifting problem caused by model updating, we jointly consider three different types of positive samples. Extensive experiments validate the robustness and effectiveness of the proposed method.

Convolutional Deep Belief Networks for Single-Cell/Object Tracking in Computational Biology and Computer Vision

PubMed Central

Pan, Shengnan; Zhang, Hongbo; Wang, Tian; Du, Jixiang; Chen, Duansheng; Cao, Liujuan

2016-01-01

In this paper, we propose deep architecture to dynamically learn the most discriminative features from data for both single-cell and object tracking in computational biology and computer vision. Firstly, the discriminative features are automatically learned via a convolutional deep belief network (CDBN). Secondly, we design a simple yet effective method to transfer features learned from CDBNs on the source tasks for generic purpose to the object tracking tasks using only limited amount of training data. Finally, to alleviate the tracker drifting problem caused by model updating, we jointly consider three different types of positive samples. Extensive experiments validate the robustness and effectiveness of the proposed method. PMID:27847827

Multiple object, three-dimensional motion tracking using the Xbox Kinect sensor

NASA Astrophysics Data System (ADS)

Rosi, T.; Onorato, P.; Oss, S.

2017-11-01

In this article we discuss the capability of the Xbox Kinect sensor to acquire three-dimensional motion data of multiple objects. Two experiments regarding fundamental features of Newtonian mechanics are performed to test the tracking abilities of our setup. Particular attention is paid to check and visualise the conservation of linear momentum, angular momentum and energy. In both experiments, two objects are tracked while falling in the gravitational field. The obtained data is visualised in a 3D virtual environment to help students understand the physics behind the performed experiments. The proposed experiments were analysed with a group of university students who are aspirant physics and mathematics teachers. Their comments are presented in this paper.

Real-time optical multiple object recognition and tracking system and method

NASA Technical Reports Server (NTRS)

Chao, Tien-Hsin (Inventor); Liu, Hua Kuang (Inventor)

1987-01-01

The invention relates to an apparatus and associated methods for the optical recognition and tracking of multiple objects in real time. Multiple point spatial filters are employed that pre-define the objects to be recognized at run-time. The system takes the basic technology of a Vander Lugt filter and adds a hololens. The technique replaces time, space and cost-intensive digital techniques. In place of multiple objects, the system can also recognize multiple orientations of a single object. This later capability has potential for space applications where space and weight are at a premium.

The TRacking Adolescents' Individual Lives Survey (TRAILS): Design, Current Status, and Selected Findings

ERIC Educational Resources Information Center

Ormel, Johan; Oldehinkel, Albertine J.; Sijtsema, Jelle; van Oort, Floor; Raven, Dennis; Veenstra, Rene; Vollebergh, Wilma A. M.; Verhulst, Frank C.

2012-01-01

Objectives: The objectives of this study were as follows: to present a concise overview of the sample, outcomes, determinants, non-response and attrition of the ongoing TRacking Adolescents' Individual Lives Survey (TRAILS), which started in 2001; to summarize a selection of recent findings on continuity, discontinuity, risk, and protective…

Attentional Resources in Visual Tracking through Occlusion: The High-Beams Effect

ERIC Educational Resources Information Center

Flombaum, Jonathan I.; Scholl, Brian J.; Pylyshyn, Zenon W.

2008-01-01

A considerable amount of research has uncovered heuristics that the visual system employs to keep track of objects through periods of occlusion. Relatively little work, by comparison, has investigated the online resources that support this processing. We explored how attention is distributed when featurally identical objects become occluded during…

Tracking and Inferring Spatial Rotation by Children and Great Apes

ERIC Educational Resources Information Center

Okamoto-Barth; Sanae; Call, Josep

2008-01-01

Finding hidden objects in space is a fundamental ability that has received considerable research attention from both a developmental and a comparative perspective. Tracking the rotational displacements of containers and hidden objects is a particularly challenging task. This study investigated the ability of 3-, 5-, 7-, and 9-year-old children and…

A theory of phase singularities for image representation and its applications to object tracking and image matching.

PubMed

Qiao, Yu; Wang, Wei; Minematsu, Nobuaki; Liu, Jianzhuang; Takeda, Mitsuo; Tang, Xiaoou

2009-10-01

This paper studies phase singularities (PSs) for image representation. We show that PSs calculated with Laguerre-Gauss filters contain important information and provide a useful tool for image analysis. PSs are invariant to image translation and rotation. We introduce several invariant features to characterize the core structures around PSs and analyze the stability of PSs to noise addition and scale change. We also study the characteristics of PSs in a scale space, which lead to a method to select key scales along phase singularity curves. We demonstrate two applications of PSs: object tracking and image matching. In object tracking, we use the iterative closest point algorithm to determine the correspondences of PSs between two adjacent frames. The use of PSs allows us to precisely determine the motions of tracked objects. In image matching, we combine PSs and scale-invariant feature transform (SIFT) descriptor to deal with the variations between two images and examine the proposed method on a benchmark database. The results indicate that our method can find more correct matching pairs with higher repeatability rates than some well-known methods.

Lateral motion and bending of microtubules studied with a new single-filament tracking routine in living cells.

PubMed

Pallavicini, Carla; Levi, Valeria; Wetzler, Diana E; Angiolini, Juan F; Benseñor, Lorena; Despósito, Marcelo A; Bruno, Luciana

2014-06-17

The cytoskeleton is involved in numerous cellular processes such as migration, division, and contraction and provides the tracks for transport driven by molecular motors. Therefore, it is very important to quantify the mechanical behavior of the cytoskeletal filaments to get a better insight into cell mechanics and organization. It has been demonstrated that relevant mechanical properties of microtubules can be extracted from the analysis of their motion and shape fluctuations. However, tracking individual filaments in living cells is extremely complex due, for example, to the high and heterogeneous background. We introduce a believed new tracking algorithm that allows recovering the coordinates of fluorescent microtubules with ∼9 nm precision in in vitro conditions. To illustrate potential applications of this algorithm, we studied the curvature distributions of fluorescent microtubules in living cells. By performing a Fourier analysis of the microtubule shapes, we found that the curvatures followed a thermal-like distribution as previously reported with an effective persistence length of ∼20 μm, a value significantly smaller than that measured in vitro. We also verified that the microtubule-associated protein XTP or the depolymerization of the actin network do not affect this value; however, the disruption of intermediate filaments decreased the persistence length. Also, we recovered trajectories of microtubule segments in actin or intermediate filament-depleted cells, and observed a significant increase of their motion with respect to untreated cells showing that these filaments contribute to the overall organization of the microtubule network. Moreover, the analysis of trajectories of microtubule segments in untreated cells showed that these filaments presented a slower but more directional motion in the cortex with respect to the perinuclear region, and suggests that the tracking routine would allow mapping the microtubule dynamical organization in cells. Copyright © 2014 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Comparison between goal programming and cointegration approaches in enhanced index tracking

NASA Astrophysics Data System (ADS)

Lam, Weng Siew; Jamaan, Saiful Hafizah Hj.

2013-04-01

Index tracking is a popular form of passive fund management in stock market. Passive management is a buy-and-hold strategy that aims to achieve rate of return similar to the market return. Index tracking problem is a problem of reproducing the performance of a stock market index, without purchasing all of the stocks that make up the index. This can be done by establishing an optimal portfolio that minimizes risk or tracking error. An improved index tracking (enhanced index tracking) is a dual-objective optimization problem, a trade-off between maximizing the mean return and minimizing the tracking error. Enhanced index tracking aims to generate excess return over the return achieved by the index. The objective of this study is to compare the portfolio compositions and performances by using two different approaches in enhanced index tracking problem, which are goal programming and cointegration. The result of this study shows that the optimal portfolios for both approaches are able to outperform the Malaysia market index which is Kuala Lumpur Composite Index. Both approaches give different optimal portfolio compositions. Besides, the cointegration approach outperforms the goal programming approach because the cointegration approach gives higher mean return and lower risk or tracking error. Therefore, the cointegration approach is more appropriate for the investors in Malaysia.

Splitting attention reduces temporal resolution from 7 Hz for tracking one object to <3 Hz when tracking three.

PubMed

Holcombe, Alex O; Chen, Wei-Ying

2013-01-09

Overall performance when tracking moving targets is known to be poorer for larger numbers of targets, but the specific effect on tracking's temporal resolution has never been investigated. We document a broad range of display parameters for which visual tracking is limited by temporal frequency (the interval between when a target is at each location and a distracter moves in and replaces it) rather than by object speed. We tested tracking of one, two, and three moving targets while the eyes remained fixed. Variation of the number of distracters and their speed revealed both speed limits and temporal frequency limits on tracking. The temporal frequency limit fell from 7 Hz with one target to 4 Hz with two targets and 2.6 Hz with three targets. The large size of this performance decrease implies that in the two-target condition participants would have done better by tracking only one of the two targets and ignoring the other. These effects are predicted by serial models involving a single tracking focus that must switch among the targets, sampling the position of only one target at a time. If parallel processing theories are to explain why dividing the tracking resource reduces temporal resolution so markedly, supplemental assumptions will be required.

An algorithm of adaptive scale object tracking in occlusion

NASA Astrophysics Data System (ADS)

Zhao, Congmei

2017-05-01

Although the correlation filter-based trackers achieve the competitive results both on accuracy and robustness, there are still some problems in handling scale variations, object occlusion, fast motions and so on. In this paper, a multi-scale kernel correlation filter algorithm based on random fern detector was proposed. The tracking task was decomposed into the target scale estimation and the translation estimation. At the same time, the Color Names features and HOG features were fused in response level to further improve the overall tracking performance of the algorithm. In addition, an online random fern classifier was trained to re-obtain the target after the target was lost. By comparing with some algorithms such as KCF, DSST, TLD, MIL, CT and CSK, experimental results show that the proposed approach could estimate the object state accurately and handle the object occlusion effectively.

Nonlinear Multiobjective MPC-Based Optimal Operation of a High Consistency Refining System in Papermaking

DOE PAGES

Li, Mingjie; Zhou, Ping; Wang, Hong; ...

2017-09-19

As one of the most important unit in the papermaking industry, the high consistency (HC) refining system is confronted with challenges such as improving pulp quality, energy saving, and emissions reduction in its operation processes. Here in this correspondence, an optimal operation of HC refining system is presented using nonlinear multiobjective model predictive control strategies that aim at set-point tracking objective of pulp quality, economic objective, and specific energy (SE) consumption objective, respectively. First, a set of input and output data at different times are employed to construct the subprocess model of the state process model for the HC refiningmore » system, and then the Wiener-type model can be obtained through combining the mechanism model of Canadian Standard Freeness and the state process model that determines their structures based on Akaike information criterion. Second, the multiobjective optimization strategy that optimizes both the set-point tracking objective of pulp quality and SE consumption is proposed simultaneously, which uses NSGA-II approach to obtain the Pareto optimal set. Furthermore, targeting at the set-point tracking objective of pulp quality, economic objective, and SE consumption objective, the sequential quadratic programming method is utilized to produce the optimal predictive controllers. In conclusion, the simulation results demonstrate that the proposed methods can make the HC refining system provide a better performance of set-point tracking of pulp quality when these predictive controllers are employed. In addition, while the optimal predictive controllers orienting with comprehensive economic objective and SE consumption objective, it has been shown that they have significantly reduced the energy consumption.« less

Nonlinear Multiobjective MPC-Based Optimal Operation of a High Consistency Refining System in Papermaking

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

Li, Mingjie; Zhou, Ping; Wang, Hong

As one of the most important unit in the papermaking industry, the high consistency (HC) refining system is confronted with challenges such as improving pulp quality, energy saving, and emissions reduction in its operation processes. Here in this correspondence, an optimal operation of HC refining system is presented using nonlinear multiobjective model predictive control strategies that aim at set-point tracking objective of pulp quality, economic objective, and specific energy (SE) consumption objective, respectively. First, a set of input and output data at different times are employed to construct the subprocess model of the state process model for the HC refiningmore » system, and then the Wiener-type model can be obtained through combining the mechanism model of Canadian Standard Freeness and the state process model that determines their structures based on Akaike information criterion. Second, the multiobjective optimization strategy that optimizes both the set-point tracking objective of pulp quality and SE consumption is proposed simultaneously, which uses NSGA-II approach to obtain the Pareto optimal set. Furthermore, targeting at the set-point tracking objective of pulp quality, economic objective, and SE consumption objective, the sequential quadratic programming method is utilized to produce the optimal predictive controllers. In conclusion, the simulation results demonstrate that the proposed methods can make the HC refining system provide a better performance of set-point tracking of pulp quality when these predictive controllers are employed. In addition, while the optimal predictive controllers orienting with comprehensive economic objective and SE consumption objective, it has been shown that they have significantly reduced the energy consumption.« less

SU-D-210-05: The Accuracy of Raw and B-Mode Image Data for Ultrasound Speckle Tracking in Radiation Therapy

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

O’Shea, T; Bamber, J; Harris, E

Purpose: For ultrasound speckle tracking there is some evidence that the envelope-detected signal (the main step in B-mode image formation) may be more accurate than raw ultrasound data for tracking larger inter-frame tissue motion. This study investigates the accuracy of raw radio-frequency (RF) versus non-logarithmic compressed envelope-detected (B-mode) data for ultrasound speckle tracking in the context of image-guided radiation therapy. Methods: Transperineal ultrasound RF data was acquired (with a 7.5 MHz linear transducer operating at a 12 Hz frame rate) from a speckle phantom moving with realistic intra-fraction prostate motion derived from a commercial tracking system. A normalised cross-correlation templatemore » matching algorithm was used to track speckle motion at the focus using (i) the RF signal and (ii) the B-mode signal. A range of imaging rates (0.5 to 12 Hz) were simulated by decimating the imaging sequences, therefore simulating larger to smaller inter-frame displacements. Motion estimation accuracy was quantified by comparison with known phantom motion. Results: The differences between RF and B-mode motion estimation accuracy (2D mean and 95% errors relative to ground truth displacements) were less than 0.01 mm for stable and persistent motion types and 0.2 mm for transient motion for imaging rates of 0.5 to 12 Hz. The mean correlation for all motion types and imaging rates was 0.851 and 0.845 for RF and B-mode data, respectively. Data type is expected to have most impact on axial (Superior-Inferior) motion estimation. Axial differences were <0.004 mm for stable and persistent motion and <0.3 mm for transient motion (axial mean errors were lowest for B-mode in all cases). Conclusions: Using the RF or B-mode signal for speckle motion estimation is comparable for translational prostate motion. B-mode image formation may involve other signal-processing steps which also influence motion estimation accuracy. A similar study for respiratory-induced motion would also be prudent. This work is support by Cancer Research UK Programme Grant C33589/A19727.« less

Extracting 3d Semantic Information from Video Surveillance System Using Deep Learning

NASA Astrophysics Data System (ADS)

Zhang, J. S.; Cao, J.; Mao, B.; Shen, D. Q.

2018-04-01

At present, intelligent video analysis technology has been widely used in various fields. Object tracking is one of the important part of intelligent video surveillance, but the traditional target tracking technology based on the pixel coordinate system in images still exists some unavoidable problems. Target tracking based on pixel can't reflect the real position information of targets, and it is difficult to track objects across scenes. Based on the analysis of Zhengyou Zhang's camera calibration method, this paper presents a method of target tracking based on the target's space coordinate system after converting the 2-D coordinate of the target into 3-D coordinate. It can be seen from the experimental results: Our method can restore the real position change information of targets well, and can also accurately get the trajectory of the target in space.

Shape and texture fused recognition of flying targets

NASA Astrophysics Data System (ADS)

Kovács, Levente; Utasi, Ákos; Kovács, Andrea; Szirányi, Tamás

2011-06-01

This paper presents visual detection and recognition of flying targets (e.g. planes, missiles) based on automatically extracted shape and object texture information, for application areas like alerting, recognition and tracking. Targets are extracted based on robust background modeling and a novel contour extraction approach, and object recognition is done by comparisons to shape and texture based query results on a previously gathered real life object dataset. Application areas involve passive defense scenarios, including automatic object detection and tracking with cheap commodity hardware components (CPU, camera and GPS).

Improving Underrepresented Minority Student Persistence in STEM

PubMed Central

Estrada, Mica; Burnett, Myra; Campbell, Andrew G.; Campbell, Patricia B.; Denetclaw, Wilfred F.; Gutiérrez, Carlos G.; Hurtado, Sylvia; John, Gilbert H.; Matsui, John; McGee, Richard; Okpodu, Camellia Moses; Robinson, T. Joan; Summers, Michael F.; Werner-Washburne, Maggie; Zavala, MariaElena

2016-01-01

Members of the Joint Working Group on Improving Underrepresented Minorities (URMs) Persistence in Science, Technology, Engineering, and Mathematics (STEM)—convened by the National Institute of General Medical Sciences and the Howard Hughes Medical Institute—review current data and propose deliberation about why the academic “pathways” leak more for URM than white or Asian STEM students. They suggest expanding to include a stronger focus on the institutional barriers that need to be removed and the types of interventions that “lift” students’ interests, commitment, and ability to persist in STEM fields. Using Kurt Lewin’s planned approach to change, the committee describes five recommendations to increase URM persistence in STEM at the undergraduate level. These recommendations capitalize on known successes, recognize the need for accountability, and are framed to facilitate greater progress in the future. The impact of these recommendations rests upon enacting the first recommendation: to track successes and failures at the institutional level and collect data that help explain the existing trends. PMID:27543633

Genome-Based Infection Tracking Reveals Dynamics of Clostridium difficile Transmission and Disease Recurrence.

PubMed

Kumar, Nitin; Miyajima, Fabio; He, Miao; Roberts, Paul; Swale, Andrew; Ellison, Louise; Pickard, Derek; Smith, Godfrey; Molyneux, Rebecca; Dougan, Gordon; Parkhill, Julian; Wren, Brendan W; Parry, Christopher M; Pirmohamed, Munir; Lawley, Trevor D

2016-03-15

Accurate tracking of Clostridium difficile transmission within healthcare settings is key to its containment but is hindered by the lack of discriminatory power of standard genotyping methods. We describe a whole-genome phylogenetic-based method to track the transmission of individual clones in infected hospital patients from the epidemic C. difficile 027/ST1 lineage, and to distinguish between the 2 causes of recurrent disease, relapse (same strain), or reinfection (different strain). We monitored patients with C. difficile infection in a UK hospital over a 2-year period. We performed whole-genome sequencing and phylogenetic analysis of 108 strains isolated from symptomatic patients. High-resolution phylogeny was integrated with in-hospital transfers and contact data to create an infection network linking individual patients and specific hospital wards. Epidemic C. difficile 027/ST1 caused the majority of infections during our sampling period. Integration of whole-genome single nucleotide polymorphism (SNP) phylogenetic analysis, which accurately discriminated between 27 distinct SNP genotypes, with patient movement and contact data identified 32 plausible transmission events, including ward-based contamination (66%) or direct donor-recipient contact (34%). Highly contagious donors were identified who contributed to the persistence of clones within distinct hospital wards and the spread of clones between wards, especially in areas of intense turnover. Recurrent cases were identified between 4 and 26 weeks, highlighting the limitation of the standard <8-week cutoff used for patient diagnosis and management. Genome-based infection tracking to monitor the persistence and spread of C. difficile within healthcare facilities could inform infection control and patient management. © The Author 2015. Published by Oxford University Press for the Infectious Diseases Society of America.

Analysis of Railroad Track Maintenance Expenditures for Class I Railroads 1962-1977

DOT National Transportation Integrated Search

1982-02-01

This study investigates the decision-making process for railroad track maintenance (T/M) expenditures. The objectives are to (1) describe how Federal track safety standards have influenced this process and (2) try to predict the impact of changes in ...

Airborne sensors for detecting large marine debris at sea.

PubMed

Veenstra, Timothy S; Churnside, James H

2012-01-01

The human eye is an excellent, general-purpose airborne sensor for detecting marine debris larger than 10 cm on or near the surface of the water. Coupled with the human brain, it can adjust for light conditions and sea-surface roughness, track persistence, differentiate color and texture, detect change in movement, and combine all of the available information to detect and identify marine debris. Matching this performance with computers and sensors is difficult at best. However, there are distinct advantages over the human eye and brain that sensors and computers can offer such as the ability to use finer spectral resolution, to work outside the spectral range of human vision, to control the illumination, to process the information in ways unavailable to the human vision system, to provide a more objective and reproducible result, to operate from unmanned aircraft, and to provide a permanent record that can be used for later analysis. Copyright © 2010 Elsevier Ltd. All rights reserved.

Tracking multiple particles in fluorescence time-lapse microscopy images via probabilistic data association.

PubMed

Godinez, William J; Rohr, Karl

2015-02-01

Tracking subcellular structures as well as viral structures displayed as 'particles' in fluorescence microscopy images yields quantitative information on the underlying dynamical processes. We have developed an approach for tracking multiple fluorescent particles based on probabilistic data association. The approach combines a localization scheme that uses a bottom-up strategy based on the spot-enhancing filter as well as a top-down strategy based on an ellipsoidal sampling scheme that uses the Gaussian probability distributions computed by a Kalman filter. The localization scheme yields multiple measurements that are incorporated into the Kalman filter via a combined innovation, where the association probabilities are interpreted as weights calculated using an image likelihood. To track objects in close proximity, we compute the support of each image position relative to the neighboring objects of a tracked object and use this support to recalculate the weights. To cope with multiple motion models, we integrated the interacting multiple model algorithm. The approach has been successfully applied to synthetic 2-D and 3-D images as well as to real 2-D and 3-D microscopy images, and the performance has been quantified. In addition, the approach was successfully applied to the 2-D and 3-D image data of the recent Particle Tracking Challenge at the IEEE International Symposium on Biomedical Imaging (ISBI) 2012.

32 CFR Appendix A to Part 806b - Definitions

Code of Federal Regulations, 2010 CFR

2010-07-01

... exemption for protecting the identity of confidential sources. Cookie: Data created by a Web server that is... (persistent cookie). It provides a way for the Web site to identify users and keep track of their preferences... or is sent to a Web site different from the one you are currently viewing. Defense Data Integrity...

32 CFR Appendix A to Part 806b - Definitions

Code of Federal Regulations, 2011 CFR

2011-07-01

... exemption for protecting the identity of confidential sources. Cookie: Data created by a Web server that is... (persistent cookie). It provides a way for the Web site to identify users and keep track of their preferences... or is sent to a Web site different from the one you are currently viewing. Defense Data Integrity...

USING STABLE ISOTOPES TO TRACK BIOMAGNIFICATION OF POLYCHLORINATED BIPHENYLS (PCBS) THROUGH STREAM FOOD WEBS

EPA Science Inventory

Biomagnification studies of PCBs in streams are rare, even though PCBs are known to biomagnify and persist in aquatic ecosystems. We investigated PCB contamination in Twelve Mile Creek (Clemson, South Carolina, U.S.A.), a stream that received >400,000 lbs. of PCBs from 1955-1978...

Methodology and Implications of Statewide Success Rates of Community College Students.

ERIC Educational Resources Information Center

McConochie, Daniel D.; Rajasekhara, Koosappa

In 1991, the Maryland State Board for Community Colleges developed the "success rate," a reporting index which combined graduation, transfer, and persistence rates. Success rate matrices were produced by tracking first-time, full-time students representing seven cohorts (1980 to 1986) over a 4-year period, and matching entering…

Down the Rabbit Hole: Challenges and Methodological Recommendations in Researching Writing-Related Student Dispositions

ERIC Educational Resources Information Center

Driscoll, Dana Lynn; Gorzelsky, Gwen; Wells, Jennifer; Hayes, Carol; Jones, Ed; Salchak, Steve

2017-01-01

Researching writing-related dispositions is of critical concern for understanding writing transfer and writing development. However, as a field we need better tools and methods for identifying, tracking, and analyzing dispositions. This article describes a failed attempt to code for five key dispositions (attribution, self-efficacy, persistence,…

Honors and the Completion Agenda: Identifying and Duplicating Student Success

ERIC Educational Resources Information Center

Trucker, Jay

2014-01-01

Longitudinal studies that track student persistence each semester serve as the primary measurement of an institution's success or failure. These studies take place at the institutional and state-wide levels as well as nationally through grant-based organizations such as Complete College America. At the Community College of Baltimore County (CCBC),…

Effects of drought on western pond turtle survival and movement patterns

Treesearch

Kathryn L. Purcell; Eric L. McGregor; Kathryn Calderala

2017-01-01

Drought has the ability to affect the persistence of small animal populations, especially those tied to aquatic habitats. We studied the response of western pond turtles Actinemys marmorata to California's worst drought on record. From 2009 through 2015 we used telemetry to track movements and assess survival of 19 western...

Studies on Monitoring and Tracking Genetic Resources: An Executive Summary

PubMed Central

Garrity, George M.; Thompson, Lorraine M.; Ussery, David W.; Paskin, Norman; Baker, Dwight; Desmeth, Philippe; Schindel, D.E.; Ong, P.S.

2009-01-01

The principles underlying fair and equitable sharing of benefits derived from the utilization of genetic resources are set out in Article 15 of the UN Convention on Biological Diversity, which stipulate that access to genetic resources is subject to the prior informed consent of the country where such resources are located and to mutually agreed terms regarding the sharing of benefits that could be derived from such access. One issue of particular concern for provider countries is how to monitor and track genetic resources once they have left the provider country and enter into use in a variety of forms. This report was commissioned to provide a detailed review of advances in DNA sequencing technologies, as those methods apply to identification of genetic resources, and the use of globally unique persistent identifiers for persistently linking to data and other forms of digital documentation that is linked to individual genetic resources. While the report was written for an audience with a mixture of technical, legal, and policy backgrounds it is relevant to the genomics community as it is an example of downstream application of genomics information. PMID:21304641

Tracking Three-Dimensional Fish Behavior with a New Marine Acoustic Telemetry System

NASA Technical Reports Server (NTRS)

Brosnan, Ian G.; McGarry, Louise P.; Greene, Charles H.; Steig, Tracey W.; Johnston, Samuel V.; Ehrenberg, John E.

2015-01-01

The persistent monitoring capability provided by acoustic telemetry systems allows us to study behavior, movement, and resource selection of mobile marine animals. Current marine acoustic telemetry systems are challenged by localization errors and limits in the number of animals that can be tracked simultaneously. We designed a new system to provide detection ranges of up to 1 km, to reduce localization errors to less than 1 m, and to increase to 500 the number of unique tags simultaneously tracked. The design builds on HTIs experience of more than a decade developing acoustic telemetry systems for freshwater environments. A field trial of the prototype system was conducted at the University of Washingtons Friday Harbor Marine Laboratory (Friday Harbor, WA). Copper rockfish (Sebastes caurinus) were selected for field trials of this new system because their high site-fidelity and small home ranges provide ample opportunity to track individual fish behavior while testing our ability to characterize the movements of a species of interest to management authorities.

Sedimentation patterns caused by scallop dredging in a physically dynamic environment.

PubMed

Dale, A C; Boulcott, P; Sherwin, T J

2011-11-01

Scallop dredging grounds in the Firth of Lorn, western Scotland, are juxtaposed with rocky reef habitats raising concerns that reef communities may be impacted by sediment disturbed by nearby scallop dredging. A particle-tracking model of sediment transport and settling is applied at two scales. In the near-field, a suspension of typical sand/gravel-dominated bed sediment is subjected to a steady current across the dredge track. In the far-field, silt particles, which may persist in suspension for multiple tidal cycles, are tracked in the context of a regional model of tidally-driven flow. The principal sedimentary risk to reef habitats is predicted to come from settling sand particles when dredge tracks approach within tens of metres of a reef. The cumulative effect of dredging at the relatively low intensities recorded in this region is not expected to have a significant long-term impact on suspended silt concentrations and settlement in this highly dispersive environment. Copyright © 2011 Elsevier Ltd. All rights reserved.

Selective visual scaling of time-scale processes facilitates broadband learning of isometric force frequency tracking.

PubMed

King, Adam C; Newell, Karl M

2015-10-01

The experiment investigated the effect of selectively augmenting faster time scales of visual feedback information on the learning and transfer of continuous isometric force tracking tasks to test the generality of the self-organization of 1/f properties of force output. Three experimental groups tracked an irregular target pattern either under a standard fixed gain condition or with selectively enhancement in the visual feedback display of intermediate (4-8 Hz) or high (8-12 Hz) frequency components of the force output. All groups reduced tracking error over practice, with the error lowest in the intermediate scaling condition followed by the high scaling and fixed gain conditions, respectively. Selective visual scaling induced persistent changes across the frequency spectrum, with the strongest effect in the intermediate scaling condition and positive transfer to novel feedback displays. The findings reveal an interdependence of the timescales in the learning and transfer of isometric force output frequency structures consistent with 1/f process models of the time scales of motor output variability.

Operational tracking of lava lake surface motion at Kīlauea Volcano, Hawai‘i

USGS Publications Warehouse

Patrick, Matthew R.; Orr, Tim R.

2018-03-08

Surface motion is an important component of lava lake behavior, but previous studies of lake motion have been focused on short time intervals. In this study, we implement the first continuous, real-time operational routine for tracking lava lake surface motion, applying the technique to the persistent lava lake in Halema‘uma‘u Crater at the summit of Kīlauea Volcano, Hawai‘i. We measure lake motion by using images from a fixed thermal camera positioned on the crater rim, transmitting images to the Hawaiian Volcano Observatory (HVO) in real time. We use an existing optical flow toolbox in Matlab to calculate motion vectors, and we track the position of lava upwelling in the lake, as well as the intensity of spattering on the lake surface. Over the past 2 years, real-time tracking of lava lake surface motion at Halema‘uma‘u has been an important part of monitoring the lake’s activity, serving as another valuable tool in the volcano monitoring suite at HVO.

Reproducibility of apatite fission-track length data and thermal history reconstruction

NASA Astrophysics Data System (ADS)

Ketcham, Richard A.; Donelick, Raymond A.; Balestrieri, Maria Laura; Zattin, Massimiliano

2009-07-01

The ability to derive detailed thermal history information from apatite fission-track analysis is predicated on the reliability of track length measurements. However, insufficient attention has been given to whether and how these measurements should be standardized. In conjunction with a fission-track workshop we conducted an experiment in which 11 volunteers measured ~ 50 track lengths on one or two samples. One mount contained Durango apatite with unannealed induced tracks, and one contained apatite from a crystalline rock containing spontaneous tracks with a broad length distribution caused by partial resetting. Results for both mounts showed scatter indicative of differences in measurement technique among the individual analysts. The effects of this variability on thermal history inversion were tested using the HeFTy computer program to model the spontaneous track measurements. A cooling-only scenario and a reheating scenario more consistent with the sample's geological history were posed. When a uniform initial length value from the literature was used, results among analysts were very inconsistent in both scenarios, although normalizing for track angle by projecting all lengths to a c-axis parallel crystallographic orientation improved some aspects of congruency. When the induced track measurement was used as the basis for thermal history inversion congruency among analysts, and agreement with inversions based on data previously collected, was significantly improved. Further improvement was obtained by using c-axis projection. Differences among inversions that persisted could be traced to differential sampling of long- and short-track populations among analysts. The results of this study, while demonstrating the robustness of apatite fission-track thermal history inversion, nevertheless point to the necessity for a standardized length calibration schema that accounts for analyst variation.

Object tracking on mobile devices using binary descriptors

NASA Astrophysics Data System (ADS)

Savakis, Andreas; Quraishi, Mohammad Faiz; Minnehan, Breton

2015-03-01

With the growing ubiquity of mobile devices, advanced applications are relying on computer vision techniques to provide novel experiences for users. Currently, few tracking approaches take into consideration the resource constraints on mobile devices. Designing efficient tracking algorithms and optimizing performance for mobile devices can result in better and more efficient tracking for applications, such as augmented reality. In this paper, we use binary descriptors, including Fast Retina Keypoint (FREAK), Oriented FAST and Rotated BRIEF (ORB), Binary Robust Independent Features (BRIEF), and Binary Robust Invariant Scalable Keypoints (BRISK) to obtain real time tracking performance on mobile devices. We consider both Google's Android and Apple's iOS operating systems to implement our tracking approach. The Android implementation is done using Android's Native Development Kit (NDK), which gives the performance benefits of using native code as well as access to legacy libraries. The iOS implementation was created using both the native Objective-C and the C++ programing languages. We also introduce simplified versions of the BRIEF and BRISK descriptors that improve processing speed without compromising tracking accuracy.

Dynamic Binding of Identity and Location Information: A Serial Model of Multiple Identity Tracking

ERIC Educational Resources Information Center

Oksama, Lauri; Hyona, Jukka

2008-01-01

Tracking of multiple moving objects is commonly assumed to be carried out by a fixed-capacity parallel mechanism. The present study proposes a serial model (MOMIT) to explain performance accuracy in the maintenance of multiple moving objects with distinct identities. A serial refresh mechanism is postulated, which makes recourse to continuous…

Four-Month-Old Infants Individuate and Track Simple Tools Following Functional Demonstrations

ERIC Educational Resources Information Center

Stavans, Maayan; Baillargeon, Renée

2018-01-01

Two experiments examined whether 4-month-olds (n = 120) who were induced to assign two objects to different categories would then be able to take advantage of these contrastive categorical encodings to individuate and track the objects. In each experiment, infants first watched functional demonstrations of two tools, a masher and tongs (Experiment…

Assessing Homegrown Library Collections: Using Google Analytics to Track Use of Screencasts and Flash-Based Learning Objects

ERIC Educational Resources Information Center

Betty, Paul

2009-01-01

Increasing use of screencast and Flash authoring software within libraries is resulting in "homegrown" library collections of digital learning objects and multimedia presentations. The author explores the use of Google Analytics to track usage statistics for interactive Shockwave Flash (.swf) files, the common file output for screencast and Flash…

Hue distinctiveness overrides category in determining performance in multiple object tracking.

PubMed

Sun, Mengdan; Zhang, Xuemin; Fan, Lingxia; Hu, Luming

2018-02-01

The visual distinctiveness between targets and distractors can significantly facilitate performance in multiple object tracking (MOT), in which color is a feature that has been commonly used. However, the processing of color can be more than "visual." Color is continuous in chromaticity, while it is commonly grouped into discrete categories (e.g., red, green). Evidence from color perception suggested that color categories may have a unique role in visual tasks independent of its chromatic appearance. Previous MOT studies have not examined the effect of chromatic and categorical distinctiveness on tracking separately. The current study aimed to reveal how chromatic (hue) and categorical distinctiveness of color between the targets and distractors affects tracking performance. With four experiments, we showed that tracking performance was largely facilitated by the increasing hue distance between the target set and the distractor set, suggesting that perceptual grouping was formed based on hue distinctiveness to aid tracking. However, we found no color categorical effect, because tracking performance was not significantly different when the targets and distractors were from the same or different categories. It was concluded that the chromatic distinctiveness of color overrides category in determining tracking performance, suggesting a dominant role of perceptual feature in MOT.

Self-paced model learning for robust visual tracking

NASA Astrophysics Data System (ADS)

Huang, Wenhui; Gu, Jason; Ma, Xin; Li, Yibin

2017-01-01

In visual tracking, learning a robust and efficient appearance model is a challenging task. Model learning determines both the strategy and the frequency of model updating, which contains many details that could affect the tracking results. Self-paced learning (SPL) has recently been attracting considerable interest in the fields of machine learning and computer vision. SPL is inspired by the learning principle underlying the cognitive process of humans, whose learning process is generally from easier samples to more complex aspects of a task. We propose a tracking method that integrates the learning paradigm of SPL into visual tracking, so reliable samples can be automatically selected for model learning. In contrast to many existing model learning strategies in visual tracking, we discover the missing link between sample selection and model learning, which are combined into a single objective function in our approach. Sample weights and model parameters can be learned by minimizing this single objective function. Additionally, to solve the real-valued learning weight of samples, an error-tolerant self-paced function that considers the characteristics of visual tracking is proposed. We demonstrate the robustness and efficiency of our tracker on a recent tracking benchmark data set with 50 video sequences.

Robust visual object tracking with interleaved segmentation

NASA Astrophysics Data System (ADS)

Abel, Peter; Kieritz, Hilke; Becker, Stefan; Arens, Michael

2017-10-01

In this paper we present a new approach for tracking non-rigid, deformable objects by means of merging an on-line boosting-based tracker and a fast foreground background segmentation. We extend an on-line boosting- based tracker, which uses axes-aligned bounding boxes with fixed aspect-ratio as tracking states. By constructing a confidence map from the on-line boosting-based tracker and unifying this map with a confidence map, which is obtained from a foreground background segmentation algorithm, we build a superior confidence map. For constructing a rough confidence map of a new frame based on on-line boosting, we employ the responses of the strong classifier as well as the single weak classifier responses that were built before during the updating step. This confidence map provides a rough estimation of the object's position and dimension. In order to refine this confidence map, we build a fine, pixel-wisely segmented confidence map and merge both maps together. Our segmentation method is color-histogram-based and provides a fine and fast image segmentation. By means of back-projection and the Bayes' rule, we obtain a confidence value for every pixel. The rough and the fine confidence maps are merged together by building an adaptively weighted sum of both maps. The weights are obtained by utilizing the variances of both confidence maps. Further, we apply morphological operators in the merged confidence map in order to reduce the noise. In the resulting map we estimate the object localization and dimension via continuous adaptive mean shift. Our approach provides a rotated rectangle as tracking states, which enables a more precise description of non-rigid, deformable objects than axes-aligned bounding boxes. We evaluate our tracker on the visual object tracking (VOT) benchmark dataset 2016.

Contralateral delay activity tracks object identity information in visual short term memory.

PubMed

Gao, Zaifeng; Xu, Xiaotian; Chen, Zhibo; Yin, Jun; Shen, Mowei; Shui, Rende

2011-08-11

Previous studies suggested that ERP component contralateral delay activity (CDA) tracks the number of objects containing identity information stored in visual short term memory (VSTM). Later MEG and fMRI studies implied that its neural source lays in superior IPS. However, since the memorized stimuli in previous studies were displayed in distinct spatial locations, hence possibly CDA tracks the object-location information instead. Moreover, a recent study implied the activation in superior IPS reflected the location load. The current research thus explored whether CDA tracks the object-location load or the object-identity load, and its neural sources. Participants were asked to remember one color, four identical colors or four distinct colors. The four-identical-color condition was the critical one because it contains the same amount of identity information as that of one color while the same amount of location information as that of four distinct colors. To ensure the participants indeed selected four colors in the four-identical-color condition, we also split the participants into two groups (low- vs. high-capacity), analyzed late positive component (LPC) in the prefrontal area, and collected participant's subjective-report. Our results revealed that most of the participants selected four identical colors. Moreover, regardless of capacity-group, there was no difference on CDA between one color and four identical colors yet both were lower than 4 distinct colors. Besides, the source of CDA was located in the superior parietal lobule, which is very close to the superior IPS. These results support the statement that CDA tracks the object identity information in VSTM. Copyright © 2011 Elsevier B.V. All rights reserved.

Real-time tracking of objects for a KC-135 microgravity experiment

NASA Technical Reports Server (NTRS)

Littlefield, Mark L.

1994-01-01

The design of a visual tracking system for use on the Extra-Vehicular Activity Helper/Retriever (EVAHR) is discussed. EVAHR is an autonomous robot designed to perform numerous tasks in an orbital microgravity environment. Since the ability to grasp a freely translating and rotating object is vital to the robot's mission, the EVAHR must analyze range image generated by the primary sensor. This allows EVAHR to locate and focus its sensors so that an accurate set of object poses can be determined and a grasp strategy planned. To test the visual tracking system being developed, a mathematical simulation was used to model the space station environment and maintain dynamics on the EVAHR and any other free floating objects. A second phase of the investigation consists of a series of experiments carried out aboard a KC-135 aircraft flying a parabolic trajectory to simulate microgravity.

Advances in image compression and automatic target recognition; Proceedings of the Meeting, Orlando, FL, Mar. 30, 31, 1989

NASA Technical Reports Server (NTRS)

Tescher, Andrew G. (Editor)

1989-01-01

Various papers on image compression and automatic target recognition are presented. Individual topics addressed include: target cluster detection in cluttered SAR imagery, model-based target recognition using laser radar imagery, Smart Sensor front-end processor for feature extraction of images, object attitude estimation and tracking from a single video sensor, symmetry detection in human vision, analysis of high resolution aerial images for object detection, obscured object recognition for an ATR application, neural networks for adaptive shape tracking, statistical mechanics and pattern recognition, detection of cylinders in aerial range images, moving object tracking using local windows, new transform method for image data compression, quad-tree product vector quantization of images, predictive trellis encoding of imagery, reduced generalized chain code for contour description, compact architecture for a real-time vision system, use of human visibility functions in segmentation coding, color texture analysis and synthesis using Gibbs random fields.

Sensor modeling and demonstration of a multi-object spectrometer for performance-driven sensing

NASA Astrophysics Data System (ADS)

Kerekes, John P.; Presnar, Michael D.; Fourspring, Kenneth D.; Ninkov, Zoran; Pogorzala, David R.; Raisanen, Alan D.; Rice, Andrew C.; Vasquez, Juan R.; Patel, Jeffrey P.; MacIntyre, Robert T.; Brown, Scott D.

2009-05-01

A novel multi-object spectrometer (MOS) is being explored for use as an adaptive performance-driven sensor that tracks moving targets. Developed originally for astronomical applications, the instrument utilizes an array of micromirrors to reflect light to a panchromatic imaging array. When an object of interest is detected the individual micromirrors imaging the object are tilted to reflect the light to a spectrometer to collect a full spectrum. This paper will present example sensor performance from empirical data collected in laboratory experiments, as well as our approach in designing optical and radiometric models of the MOS channels and the micromirror array. Simulation of moving vehicles in a highfidelity, hyperspectral scene is used to generate a dynamic video input for the adaptive sensor. Performance-driven algorithms for feature-aided target tracking and modality selection exploit multiple electromagnetic observables to track moving vehicle targets.

Measuring Positions of Objects using Two or More Cameras

NASA Technical Reports Server (NTRS)

Klinko, Steve; Lane, John; Nelson, Christopher

2008-01-01

An improved method of computing positions of objects from digitized images acquired by two or more cameras (see figure) has been developed for use in tracking debris shed by a spacecraft during and shortly after launch. The method is also readily adaptable to such applications as (1) tracking moving and possibly interacting objects in other settings in order to determine causes of accidents and (2) measuring positions of stationary objects, as in surveying. Images acquired by cameras fixed to the ground and/or cameras mounted on tracking telescopes can be used in this method. In this method, processing of image data starts with creation of detailed computer- aided design (CAD) models of the objects to be tracked. By rotating, translating, resizing, and overlaying the models with digitized camera images, parameters that characterize the position and orientation of the camera can be determined. The final position error depends on how well the centroids of the objects in the images are measured; how accurately the centroids are interpolated for synchronization of cameras; and how effectively matches are made to determine rotation, scaling, and translation parameters. The method involves use of the perspective camera model (also denoted the point camera model), which is one of several mathematical models developed over the years to represent the relationships between external coordinates of objects and the coordinates of the objects as they appear on the image plane in a camera. The method also involves extensive use of the affine camera model, in which the distance from the camera to an object (or to a small feature on an object) is assumed to be much greater than the size of the object (or feature), resulting in a truly two-dimensional image. The affine camera model does not require advance knowledge of the positions and orientations of the cameras. This is because ultimately, positions and orientations of the cameras and of all objects are computed in a coordinate system attached to one object as defined in its CAD model.

A database for reproducible manipulation research: CapriDB - Capture, Print, Innovate.

PubMed

Pokorny, Florian T; Bekiroglu, Yasemin; Pauwels, Karl; Butepage, Judith; Scherer, Clara; Kragic, Danica

2017-04-01

We present a novel approach and database which combines the inexpensive generation of 3D object models via monocular or RGB-D camera images with 3D printing and a state of the art object tracking algorithm. Unlike recent efforts towards the creation of 3D object databases for robotics, our approach does not require expensive and controlled 3D scanning setups and aims to enable anyone with a camera to scan, print and track complex objects for manipulation research. The proposed approach results in detailed textured mesh models whose 3D printed replicas provide close approximations of the originals. A key motivation for utilizing 3D printed objects is the ability to precisely control and vary object properties such as the size, material properties and mass distribution in the 3D printing process to obtain reproducible conditions for robotic manipulation research. We present CapriDB - an extensible database resulting from this approach containing initially 40 textured and 3D printable mesh models together with tracking features to facilitate the adoption of the proposed approach.

Visual Sensor Based Abnormal Event Detection with Moving Shadow Removal in Home Healthcare Applications

PubMed Central

Lee, Young-Sook; Chung, Wan-Young

2012-01-01

Vision-based abnormal event detection for home healthcare systems can be greatly improved using visual sensor-based techniques able to detect, track and recognize objects in the scene. However, in moving object detection and tracking processes, moving cast shadows can be misclassified as part of objects or moving objects. Shadow removal is an essential step for developing video surveillance systems. The goal of the primary is to design novel computer vision techniques that can extract objects more accurately and discriminate between abnormal and normal activities. To improve the accuracy of object detection and tracking, our proposed shadow removal algorithm is employed. Abnormal event detection based on visual sensor by using shape features variation and 3-D trajectory is presented to overcome the low fall detection rate. The experimental results showed that the success rate of detecting abnormal events was 97% with a false positive rate of 2%. Our proposed algorithm can allow distinguishing diverse fall activities such as forward falls, backward falls, and falling asides from normal activities. PMID:22368486

Attentional enhancement during multiple-object tracking.

PubMed

Drew, Trafton; McCollough, Andrew W; Horowitz, Todd S; Vogel, Edward K

2009-04-01

What is the role of attention in multiple-object tracking? Does attention enhance target representations, suppress distractor representations, or both? It is difficult to ask this question in a purely behavioral paradigm without altering the very attentional allocation one is trying to measure. In the present study, we used event-related potentials to examine the early visual evoked responses to task-irrelevant probes without requiring an additional detection task. Subjects tracked two targets among four moving distractors and four stationary distractors. Brief probes were flashed on targets, moving distractors, stationary distractors, or empty space. We obtained a significant enhancement of the visually evoked P1 and N1 components (approximately 100-150 msec) for probes on targets, relative to distractors. Furthermore, good trackers showed larger differences between target and distractor probes than did poor trackers. These results provide evidence of early attentional enhancement of tracked target items and also provide a novel approach to measuring attentional allocation during tracking.

An Objective Comparison of Cell Tracking Algorithms

PubMed Central

Ulman, Vladimír; Maška, Martin; Magnusson, Klas E. G.; Ronneberger, Olaf; Haubold, Carsten; Harder, Nathalie; Matula, Pavel; Matula, Petr; Svoboda, David; Radojevic, Miroslav; Smal, Ihor; Rohr, Karl; Jaldén, Joakim; Blau, Helen M.; Dzyubachyk, Oleh; Lelieveldt, Boudewijn; Xiao, Pengdong; Li, Yuexiang; Cho, Siu-Yeung; Dufour, Alexandre C.; Olivo-Marin, Jean-Christophe; Reyes-Aldasoro, Constantino C.; Solis-Lemus, Jose A.; Bensch, Robert; Brox, Thomas; Stegmaier, Johannes; Mikut, Ralf; Wolf, Steffen; Hamprecht, Fred. A.; Esteves, Tiago; Quelhas, Pedro; Demirel, Ömer; Malmström, Lars; Jug, Florian; Tomancak, Pavel; Meijering, Erik; Muñoz-Barrutia, Arrate; Kozubek, Michal; Ortiz-de-Solorzano, Carlos

2017-01-01

We present a combined report on the results of three editions of the Cell Tracking Challenge, an ongoing initiative aimed at promoting the development and objective evaluation of cell tracking algorithms. With twenty-one participating algorithms and a data repository consisting of thirteen datasets of various microscopy modalities, the challenge displays today’s state of the art in the field. We analyze the results using performance measures for segmentation and tracking that rank all participating methods. We also analyze the performance of all algorithms in terms of biological measures and their practical usability. Even though some methods score high in all technical aspects, not a single one obtains fully correct solutions. We show that methods that either take prior information into account using learning strategies or analyze cells in a global spatio-temporal video context perform better than other methods under the segmentation and tracking scenarios included in the challenge. PMID:29083403

An objective comparison of cell-tracking algorithms.

PubMed

Ulman, Vladimír; Maška, Martin; Magnusson, Klas E G; Ronneberger, Olaf; Haubold, Carsten; Harder, Nathalie; Matula, Pavel; Matula, Petr; Svoboda, David; Radojevic, Miroslav; Smal, Ihor; Rohr, Karl; Jaldén, Joakim; Blau, Helen M; Dzyubachyk, Oleh; Lelieveldt, Boudewijn; Xiao, Pengdong; Li, Yuexiang; Cho, Siu-Yeung; Dufour, Alexandre C; Olivo-Marin, Jean-Christophe; Reyes-Aldasoro, Constantino C; Solis-Lemus, Jose A; Bensch, Robert; Brox, Thomas; Stegmaier, Johannes; Mikut, Ralf; Wolf, Steffen; Hamprecht, Fred A; Esteves, Tiago; Quelhas, Pedro; Demirel, Ömer; Malmström, Lars; Jug, Florian; Tomancak, Pavel; Meijering, Erik; Muñoz-Barrutia, Arrate; Kozubek, Michal; Ortiz-de-Solorzano, Carlos

2017-12-01

We present a combined report on the results of three editions of the Cell Tracking Challenge, an ongoing initiative aimed at promoting the development and objective evaluation of cell segmentation and tracking algorithms. With 21 participating algorithms and a data repository consisting of 13 data sets from various microscopy modalities, the challenge displays today's state-of-the-art methodology in the field. We analyzed the challenge results using performance measures for segmentation and tracking that rank all participating methods. We also analyzed the performance of all of the algorithms in terms of biological measures and practical usability. Although some methods scored high in all technical aspects, none obtained fully correct solutions. We found that methods that either take prior information into account using learning strategies or analyze cells in a global spatiotemporal video context performed better than other methods under the segmentation and tracking scenarios included in the challenge.

Astrometry with A-Track Using Gaia DR1 Catalogue

NASA Astrophysics Data System (ADS)

Kılıç, Yücel; Erece, Orhan; Kaplan, Murat

2018-04-01

In this work, we built all sky index files from Gaia DR1 catalogue for the high-precision astrometric field solution and the precise WCS coordinates of the moving objects. For this, we used build-astrometry-index program as a part of astrometry.net code suit. Additionally, we added astrometry.net's WCS solution tool to our previously developed software which is a fast and robust pipeline for detecting moving objects such as asteroids and comets in sequential FITS images, called A-Track. Moreover, MPC module was added to A-Track. This module is linked to an asteroid database to name the found objects and prepare the MPC file to report the results. After these innovations, we tested a new version of the A-Track code on photometrical data taken by the SI-1100 CCD with 1-meter telescope at TÜBİTAK National Observatory, Antalya. The pipeline can be used to analyse large data archives or daily sequential data. The code is hosted on GitHub under the GNU GPL v3 license.

Action-Driven Visual Object Tracking With Deep Reinforcement Learning.

PubMed

Yun, Sangdoo; Choi, Jongwon; Yoo, Youngjoon; Yun, Kimin; Choi, Jin Young

2018-06-01

In this paper, we propose an efficient visual tracker, which directly captures a bounding box containing the target object in a video by means of sequential actions learned using deep neural networks. The proposed deep neural network to control tracking actions is pretrained using various training video sequences and fine-tuned during actual tracking for online adaptation to a change of target and background. The pretraining is done by utilizing deep reinforcement learning (RL) as well as supervised learning. The use of RL enables even partially labeled data to be successfully utilized for semisupervised learning. Through the evaluation of the object tracking benchmark data set, the proposed tracker is validated to achieve a competitive performance at three times the speed of existing deep network-based trackers. The fast version of the proposed method, which operates in real time on graphics processing unit, outperforms the state-of-the-art real-time trackers with an accuracy improvement of more than 8%.

Feature tracking for automated volume of interest stabilization on 4D-OCT images

NASA Astrophysics Data System (ADS)

Laves, Max-Heinrich; Schoob, Andreas; Kahrs, Lüder A.; Pfeiffer, Tom; Huber, Robert; Ortmaier, Tobias

2017-03-01

A common representation of volumetric medical image data is the triplanar view (TV), in which the surgeon manually selects slices showing the anatomical structure of interest. In addition to common medical imaging such as MRI or computed tomography, recent advances in the field of optical coherence tomography (OCT) have enabled live processing and volumetric rendering of four-dimensional images of the human body. Due to the region of interest undergoing motion, it is challenging for the surgeon to simultaneously keep track of an object by continuously adjusting the TV to desired slices. To select these slices in subsequent frames automatically, it is necessary to track movements of the volume of interest (VOI). This has not been addressed with respect to 4DOCT images yet. Therefore, this paper evaluates motion tracking by applying state-of-the-art tracking schemes on maximum intensity projections (MIP) of 4D-OCT images. Estimated VOI location is used to conveniently show corresponding slices and to improve the MIPs by calculating thin-slab MIPs. Tracking performances are evaluated on an in-vivo sequence of human skin, captured at 26 volumes per second. Among investigated tracking schemes, our recently presented tracking scheme for soft tissue motion provides highest accuracy with an error of under 2.2 voxels for the first 80 volumes. Object tracking on 4D-OCT images enables its use for sub-epithelial tracking of microvessels for image-guidance.

Segmentation and tracking in echocardiographic sequences: active contours guided by optical flow estimates

NASA Technical Reports Server (NTRS)

Mikic, I.; Krucinski, S.; Thomas, J. D.

1998-01-01

This paper presents a method for segmentation and tracking of cardiac structures in ultrasound image sequences. The developed algorithm is based on the active contour framework. This approach requires initial placement of the contour close to the desired position in the image, usually an object outline. Best contour shape and position are then calculated, assuming that at this configuration a global energy function, associated with a contour, attains its minimum. Active contours can be used for tracking by selecting a solution from a previous frame as an initial position in a present frame. Such an approach, however, fails for large displacements of the object of interest. This paper presents a technique that incorporates the information on pixel velocities (optical flow) into the estimate of initial contour to enable tracking of fast-moving objects. The algorithm was tested on several ultrasound image sequences, each covering one complete cardiac cycle. The contour successfully tracked boundaries of mitral valve leaflets, aortic root and endocardial borders of the left ventricle. The algorithm-generated outlines were compared against manual tracings by expert physicians. The automated method resulted in contours that were within the boundaries of intraobserver variability.

Effective real-time vehicle tracking using discriminative sparse coding on local patches

NASA Astrophysics Data System (ADS)

Chen, XiangJun; Ye, Feiyue; Ruan, Yaduan; Chen, Qimei

2016-01-01

A visual tracking framework that provides an object detector and tracker, which focuses on effective and efficient visual tracking in surveillance of real-world intelligent transport system applications, is proposed. The framework casts the tracking task as problems of object detection, feature representation, and classification, which is different from appearance model-matching approaches. Through a feature representation of discriminative sparse coding on local patches called DSCLP, which trains a dictionary on local clustered patches sampled from both positive and negative datasets, the discriminative power and robustness has been improved remarkably, which makes our method more robust to a complex realistic setting with all kinds of degraded image quality. Moreover, by catching objects through one-time background subtraction, along with offline dictionary training, computation time is dramatically reduced, which enables our framework to achieve real-time tracking performance even in a high-definition sequence with heavy traffic. Experiment results show that our work outperforms some state-of-the-art methods in terms of speed, accuracy, and robustness and exhibits increased robustness in a complex real-world scenario with degraded image quality caused by vehicle occlusion, image blur of rain or fog, and change in viewpoint or scale.

Semi-automated location identification of catheters in digital chest radiographs

NASA Astrophysics Data System (ADS)

Keller, Brad M.; Reeves, Anthony P.; Cham, Matthew D.; Henschke, Claudia I.; Yankelevitz, David F.

2007-03-01

Localization of catheter tips is the most common task in intensive care unit imaging. In this work, catheters appearing in digital chest radiographs acquired by portable chest x-rays were tracked using a semi-automatic method. Due to the fact that catheters are synthetic objects, its profile does not vary drastically over its length. Therefore, we use forward looking registration with normalized cross-correlation in order to take advantage of a priori information of the catheter profile. The registration is accomplished with a two-dimensional template representative of the catheter to be tracked generated using two seed points given by the user. To validate catheter tracking with this method, we look at two metrics: accuracy and precision. The algorithms results are compared to a ground truth established by catheter midlines marked by expert radiologists. Using 12 objects of interest comprised of naso-gastric, endo-tracheal tubes, and chest tubes, and PICC and central venous catheters, we find that our algorithm can fully track 75% of the objects of interest, with a average tracking accuracy and precision of 85.0%, 93.6% respectively using the above metrics. Such a technique would be useful for physicians wishing to verify the positioning of catheter tips using chest radiographs.

Differential Contributions of Development and Learning to Infants' Knowledge of Object Continuity and Discontinuity

ERIC Educational Resources Information Center

Bertenthal, Bennett I.; Gredeback, Gustaf; Boyer, Ty W.

2013-01-01

Sixty infants divided evenly between 5 and 7 months of age were tested for their knowledge of object continuity versus discontinuity with a predictive tracking task. The stimulus event consisted of a moving ball that was briefly occluded for 20 trials. Both age groups predictively tracked the ball when it disappeared and reappeared via occlusion,…

KENNEDY SPACE CENTER, FLA. - Workers calibrate a tracking telescope, part of the Distant Object Attitude Measurement System (DOAMS), located in Cocoa Beach, Fla. The telescope provides optical support for launches from KSC and Cape Canaveral.

NASA Image and Video Library

2003-09-03

KENNEDY SPACE CENTER, FLA. - Workers calibrate a tracking telescope, part of the Distant Object Attitude Measurement System (DOAMS), located in Cocoa Beach, Fla. The telescope provides optical support for launches from KSC and Cape Canaveral.

Real-time Astrometry Using Phase Congruency

NASA Astrophysics Data System (ADS)

Lambert, A.; Polo, M.; Tang, Y.

Phase congruency is a computer vision technique that proves to perform well for determining the tracks of optical objects (Flewelling, AMOS 2014). We report on a real-time implementation of this using an FPGA and CMOS Image Sensor, with on-sky data. The lightweight instrument can provide tracking update signals to the mount of the telescope, as well as determine abnormal objects in the scene.

Visual Tracking via Sparse and Local Linear Coding.

PubMed

Wang, Guofeng; Qin, Xueying; Zhong, Fan; Liu, Yue; Li, Hongbo; Peng, Qunsheng; Yang, Ming-Hsuan

2015-11-01

The state search is an important component of any object tracking algorithm. Numerous algorithms have been proposed, but stochastic sampling methods (e.g., particle filters) are arguably one of the most effective approaches. However, the discretization of the state space complicates the search for the precise object location. In this paper, we propose a novel tracking algorithm that extends the state space of particle observations from discrete to continuous. The solution is determined accurately via iterative linear coding between two convex hulls. The algorithm is modeled by an optimal function, which can be efficiently solved by either convex sparse coding or locality constrained linear coding. The algorithm is also very flexible and can be combined with many generic object representations. Thus, we first use sparse representation to achieve an efficient searching mechanism of the algorithm and demonstrate its accuracy. Next, two other object representation models, i.e., least soft-threshold squares and adaptive structural local sparse appearance, are implemented with improved accuracy to demonstrate the flexibility of our algorithm. Qualitative and quantitative experimental results demonstrate that the proposed tracking algorithm performs favorably against the state-of-the-art methods in dynamic scenes.

Designs and Algorithms to Map Eye Tracking Data with Dynamic Multielement Moving Objects.

PubMed

Kang, Ziho; Mandal, Saptarshi; Crutchfield, Jerry; Millan, Angel; McClung, Sarah N

2016-01-01

Design concepts and algorithms were developed to address the eye tracking analysis issues that arise when (1) participants interrogate dynamic multielement objects that can overlap on the display and (2) visual angle error of the eye trackers is incapable of providing exact eye fixation coordinates. These issues were addressed by (1) developing dynamic areas of interests (AOIs) in the form of either convex or rectangular shapes to represent the moving and shape-changing multielement objects, (2) introducing the concept of AOI gap tolerance (AGT) that controls the size of the AOIs to address the overlapping and visual angle error issues, and (3) finding a near optimal AGT value. The approach was tested in the context of air traffic control (ATC) operations where air traffic controller specialists (ATCSs) interrogated multiple moving aircraft on a radar display to detect and control the aircraft for the purpose of maintaining safe and expeditious air transportation. In addition, we show how eye tracking analysis results can differ based on how we define dynamic AOIs to determine eye fixations on moving objects. The results serve as a framework to more accurately analyze eye tracking data and to better support the analysis of human performance.

Designs and Algorithms to Map Eye Tracking Data with Dynamic Multielement Moving Objects

PubMed Central

Mandal, Saptarshi

2016-01-01

Design concepts and algorithms were developed to address the eye tracking analysis issues that arise when (1) participants interrogate dynamic multielement objects that can overlap on the display and (2) visual angle error of the eye trackers is incapable of providing exact eye fixation coordinates. These issues were addressed by (1) developing dynamic areas of interests (AOIs) in the form of either convex or rectangular shapes to represent the moving and shape-changing multielement objects, (2) introducing the concept of AOI gap tolerance (AGT) that controls the size of the AOIs to address the overlapping and visual angle error issues, and (3) finding a near optimal AGT value. The approach was tested in the context of air traffic control (ATC) operations where air traffic controller specialists (ATCSs) interrogated multiple moving aircraft on a radar display to detect and control the aircraft for the purpose of maintaining safe and expeditious air transportation. In addition, we show how eye tracking analysis results can differ based on how we define dynamic AOIs to determine eye fixations on moving objects. The results serve as a framework to more accurately analyze eye tracking data and to better support the analysis of human performance. PMID:27725830

Rapid Object Detection Systems, Utilising Deep Learning and Unmanned Aerial Systems (uas) for Civil Engineering Applications

NASA Astrophysics Data System (ADS)

Griffiths, D.; Boehm, J.

2018-05-01

With deep learning approaches now out-performing traditional image processing techniques for image understanding, this paper accesses the potential of rapid generation of Convolutional Neural Networks (CNNs) for applied engineering purposes. Three CNNs are trained on 275 UAS-derived and freely available online images for object detection of 3m2 segments of railway track. These includes two models based on the Faster RCNN object detection algorithm (Resnet and Incpetion-Resnet) as well as the novel onestage Focal Loss network architecture (Retinanet). Model performance was assessed with respect to three accuracy metrics. The first two consisted of Intersection over Union (IoU) with thresholds 0.5 and 0.1. The last assesses accuracy based on the proportion of track covered by object detection proposals against total track length. In under six hours of training (and two hours of manual labelling) the models detected 91.3 %, 83.1 % and 75.6 % of track in the 500 test images acquired from the UAS survey Retinanet, Resnet and Inception-Resnet respectively. We then discuss the potential for such applications of such systems within the engineering field for a range of scenarios.

Adaptive Control of a Utility-Scale Wind Turbine Operating in Region 3

NASA Technical Reports Server (NTRS)

Frost, Susan A.; Balas, Mark J.; Wright, Alan D.

2009-01-01

Adaptive control techniques are well suited to nonlinear applications, such as wind turbines, which are difficult to accurately model and which have effects from poorly known operating environments. The turbulent and unpredictable conditions in which wind turbines operate create many challenges for their operation. In this paper, we design an adaptive collective pitch controller for a high-fidelity simulation of a utility scale, variable-speed horizontal axis wind turbine. The objective of the adaptive pitch controller in Region 3 is to regulate generator speed and reject step disturbances. The control objective is accomplished by collectively pitching the turbine blades. We use an extension of the Direct Model Reference Adaptive Control (DMRAC) approach to track a reference point and to reject persistent disturbances. The turbine simulation models the Controls Advanced Research Turbine (CART) of the National Renewable Energy Laboratory in Golden, Colorado. The CART is a utility-scale wind turbine which has a well-developed and extensively verified simulator. The adaptive collective pitch controller for Region 3 was compared in simulations with a bas celliansesical Proportional Integrator (PI) collective pitch controller. In the simulations, the adaptive pitch controller showed improved speed regulation in Region 3 when compared with the baseline PI pitch controller and it demonstrated robustness to modeling errors.

Introduction of digital object identifiers (DOI) for seismic networks

NASA Astrophysics Data System (ADS)

Evans, Peter; Strollo, Angelo; Clark, Adam; Ahern, Tim; Newman, Rob; Clinton, John; Pequegnat, Catherine; Pedersen, Helle

2015-04-01

Proper attribution for scientific source data is important in promoting transparency and recognising the role of data providers in science. Data sets such as those produced by seismic networks now need to be citable and permanently locatable for research users. Recently the EIDA and IRIS-DMC communities have worked together on development of methods for generation, maintenance and promotion of persistent identifiers for seismic networks. This resulted in a 2014 Recommendation by the International Federation of Digital Seismograph Networks (FDSN) on the use of Digital Object Identifiers (DOI) for seismic networks. These can be cited equivalently to scientific papers, and tools such as DataCite allow the tracking of citations to these datasets. The GEOFON, IRIS and RESIF data centres have now begun to roll-out of these seismic network DOIs. This has involved working with principal investigators to prepare metadata consistent with the FDSN recommendation, preparation of landing pages, and changes to the web sites to promote DOIs where available. This has involved preparing improved descriptions of the data (metadata) and clarifying how individuals and institutions should best be recognised for their contributions to making the data available. We illustrate this process for a few representative networks. We will be in contact with additional network operators to help them establish DOIs for their networks in future.

Videogrammetry Using Projected Circular Targets: Proof-of-Concept Test

NASA Technical Reports Server (NTRS)

Pappa, Richard S.; Black, Jonathan T.

2003-01-01

Videogrammetry is the science of calculating 3D object coordinates as a function of time from image sequences. It expands the method of photogrammetry to multiple time steps enabling the object to be characterized dynamically. Photogrammetry achieves the greatest accuracy with high contrast, solid-colored, circular targets. The high contrast is most often effected using retro-reflective targets attached to the measurement article. Knowledge of the location of each target allows those points to be tracked in a sequence of images, thus yielding dynamic characterization of the overall object. For ultra-lightweight and inflatable gossamer structures (e.g. solar sails, inflatable antennae, sun shields, etc.) where it may be desirable to avoid physically attaching retro-targets, a high-density grid of projected circular targets - called dot projection - is a viable alternative. Over time the object changes shape or position independently of the dots. Dynamic behavior, such as deployment or vibration, can be characterized by tracking the overall 3D shape of the object instead of tracking specific object points. To develop this method, an oscillating rigid object was measured using both retroreflective targets and dot projection. This paper details these tests, compares the results, and discusses the overall accuracy of dot projection videogrammetry.

Videogrammetry Using Projected Circular Targets: Proof-of-Concept Test

NASA Technical Reports Server (NTRS)

Black, Jonathan T.; Pappa, Richard S.

2003-01-01

Videogrammetry is the science of calculating 3D object coordinates as a function of time from image sequences. It expands the method of photogrammetry to multiple time steps enabling the object to be characterized dynamically. Photogrammetry achieves the greatest accuracy with high contrast, solid-colored circular targets. The high contrast is most often effected using retro-reflective targets attached to the measurement article. Knowledge of the location of each target allows those points to be tracked in a sequence of images, thus yielding dynamic characterization of the overall object. For ultra-lightweight and inflatable gossamer structures (e.g. solar sails, inflatable antennae, sun shields, etc.) where it may be desirable to avoid physically attaching retro-targets, a high-density grid of projected circular targets - called dot projection - is a viable alternative. Over time the object changes shape or position independently of the dots. Dynamic behavior, such as deployment or vibration, can be characterized by tracking the overall 3D shape of the object instead of tracking specific object points. To develop this method, an oscillating rigid object was measured using both retro- reflective targets and dot projection. This paper details these tests, compares the results, and discusses the overall accuracy of dot projection videogrammetry.

Universal Ontology: Attentive Tracking of Objects and Substances across Languages and over Development

ERIC Educational Resources Information Center

Cacchione, Trix; Indino, Marcello; Fujita, Kazuo; Itakura, Shoji; Matsuno, Toyomi; Schaub, Simone; Amici, Federica

2014-01-01

Previous research has demonstrated that adults are successful at visually tracking rigidly moving items, but experience great difficulties when tracking substance-like "pouring" items. Using a comparative approach, we investigated whether the presence/absence of the grammatical count-mass distinction influences adults and children's…

Object Acquisition and Tracking for Space-Based Surveillance

DTIC Science & Technology

1991-11-27

on multiple image frames, and, accordingly, requires a smaller signal to noise ratio. It is sometimes referred to as track before detect , and can...smaller sensor optics. Both the traditional and track before detect approaches are applicable to systems using scanning sensors, as well as those which use staring sensors.

MOLECULAR TRACKING FECAL CONTAMINATION IN SURFACE WATERS: 16S RDNA VERSUS METAGENOMICS APPROACHES

EPA Science Inventory

Microbial source tracking methods need to be sensitive and exhibit temporal and geographic stability in order to provide meaningful data in field studies. The objective of this study was to use a combination of PCR-based methods to track cow fecal contamination in two watersheds....

Model of ballistic targets' dynamics used for trajectory tracking algorithms

NASA Astrophysics Data System (ADS)

Okoń-FÄ fara, Marta; Kawalec, Adam; Witczak, Andrzej

2017-04-01

There are known only few ballistic object tracking algorithms. To develop such algorithms and to its further testing, it is necessary to implement possibly simple and reliable objects' dynamics model. The article presents the dynamics' model of a tactical ballistic missile (TBM) including the three stages of flight: the boost stage and two passive stages - the ascending one and the descending one. Additionally, the procedure of transformation from the local coordinate system to the polar-radar oriented and the global is presented. The prepared theoretical data may be used to determine the tracking algorithm parameters and to its further verification.

Habitat fragmentation and the persistence of lynx populations in Washington state

Treesearch

Gary M Koehler; Benjamin T. Maletzke; Jeff A. Von Kienast; Keith B. Aubry; Robert B. Wielgus; Robert H. Naney

2008-01-01

Lynx (Lynx canadensis) occur in the northern counties of Washington state, USA; however, current distribution and status of lynx in Washington are poorly understood. During winters 2002-2004 we snow-tracked lynx for 155 km within a 211-km2 area in northern Washington, to develop a model of lynx-habitat relationships that we...

Persistent Target Tracking Using Likelihood Fusion in Wide-Area and Full Motion Video Sequences

DTIC Science & Technology

2012-07-01

624–637, 2010. [33] R. Pelapur, K. Palaniappan, F. Bunyak, and G. Seetharaman, “Vehicle orientation estimation using radon transform-based voting in...pp. 873–880. [37] F. Bunyak, K. Palaniappan, S. K. Nath, and G. Seetharaman, “Flux tensor constrained geodesic active contours with sensor fusion for

Preservice Teachers of High School Mathematics: Success, Failure, and Persistence in the Face of Mathematical Challenges

ERIC Educational Resources Information Center

Sinicrope, Rose; Eppler, Marion; Preston, Ronald V.; Ironsmith, Marsha

2015-01-01

The goal of this study was to identify variables related to success and resilience in an undergraduate, high school mathematics teacher education program. Over a five-year period, we tracked the academic performance and achievement motivation goals of multiple cohorts of students. Students who successfully completed their degrees had higher grade…

An inexpensive programmable illumination microscope with active feedback.

PubMed

Tompkins, Nathan; Fraden, Seth

2016-02-01

We have developed a programmable illumination system capable of tracking and illuminating numerous objects simultaneously using only low-cost and reused optical components. The active feedback control software allows for a closed-loop system that tracks and perturbs objects of interest automatically. Our system uses a static stage where the objects of interest are tracked computationally as they move across the field of view allowing for a large number of simultaneous experiments. An algorithmically determined illumination pattern can be applied anywhere in the field of view with simultaneous imaging and perturbation using different colors of light to enable spatially and temporally structured illumination. Our system consists of a consumer projector, camera, 35-mm camera lens, and a small number of other optical and scaffolding components. The entire apparatus can be assembled for under $4,000.

Multiple Hypothesis Tracking (MHT) for Space Surveillance: Results and Simulation Studies

NASA Astrophysics Data System (ADS)

Singh, N.; Poore, A.; Sheaff, C.; Aristoff, J.; Jah, M.

2013-09-01

With the anticipated installation of more accurate sensors and the increased probability of future collisions between space objects, the potential number of observable space objects is likely to increase by an order of magnitude within the next decade, thereby placing an ever-increasing burden on current operational systems. Moreover, the need to track closely-spaced objects due, for example, to breakups as illustrated by the recent Chinese ASAT test or the Iridium-Kosmos collision, requires new, robust, and autonomous methods for space surveillance to enable the development and maintenance of the present and future space catalog and to support the overall space surveillance mission. The problem of correctly associating a stream of uncorrelated tracks (UCTs) and uncorrelated optical observations (UCOs) into common objects is critical to mitigating the number of UCTs and is a prerequisite to subsequent space catalog maintenance. Presently, such association operations are mainly performed using non-statistical simple fixed-gate association logic. In this paper, we report on the salient features and the performance of a newly-developed statistically-robust system-level multiple hypothesis tracking (MHT) system for advanced space surveillance. The multiple-frame assignment (MFA) formulation of MHT, together with supporting astrodynamics algorithms, provides a new joint capability for space catalog maintenance, UCT/UCO resolution, and initial orbit determination. The MFA-MHT framework incorporates multiple hypotheses for report to system track data association and uses a multi-arc construction to accommodate recently developed algorithms for multiple hypothesis filtering (e.g., AEGIS, CAR-MHF, UMAP, and MMAE). This MHT framework allows us to evaluate the benefits of many different algorithms ranging from single- and multiple-frame data association to filtering and uncertainty quantification. In this paper, it will be shown that the MHT system can provide superior tracking performance compared to existing methods at a lower computational cost, especially for closely-spaced objects, in realistic multi-sensor multi-object tracking scenarios over multiple regimes of space. Specifically, we demonstrate that the prototype MHT system can accurately and efficiently process tens of thousands of UCTs and angles-only UCOs emanating from thousands of objects in LEO, GEO, MEO and HELO, many of which are closely-spaced, in real-time on a single laptop computer, thereby making it well-suited for large-scale breakup and tracking scenarios. This is possible in part because complexity reduction techniques are used to control the runtime of MHT without sacrificing accuracy. We assess the performance of MHT in relation to other tracking methods in multi-target, multi-sensor scenarios ranging from easy to difficult (i.e., widely-spaced objects to closely-spaced objects), using realistic physics and probabilities of detection less than one. In LEO, it is shown that the MHT system is able to address the challenges of processing breakups by analyzing multiple frames of data simultaneously in order to improve association decisions, reduce cross-tagging, and reduce unassociated UCTs. As a result, the multi-frame MHT system can establish orbits up to ten times faster than single-frame methods. Finally, it is shown that in GEO, MEO and HELO, the MHT system is able to address the challenges of processing angles-only optical observations by providing a unified multi-frame framework.

Advantages and challenges in automated apatite fission track counting

NASA Astrophysics Data System (ADS)

Enkelmann, E.; Ehlers, T. A.

2012-04-01

Fission track thermochronometer data are often a core element of modern tectonic and denudation studies. Soon after the development of the fission track methods interest emerged for the developed an automated counting procedure to replace the time consuming labor of counting fission tracks under the microscope. Automated track counting became feasible in recent years with increasing improvements in computer software and hardware. One such example used in this study is the commercial automated fission track counting procedure from Autoscan Systems Pty that has been highlighted through several venues. We conducted experiments that are designed to reliably and consistently test the ability of this fully automated counting system to recognize fission tracks in apatite and a muscovite external detector. Fission tracks were analyzed in samples with a step-wise increase in sample complexity. The first set of experiments used a large (mm-size) slice of Durango apatite cut parallel to the prism plane. Second, samples with 80-200 μm large apatite grains of Fish Canyon Tuff were analyzed. This second sample set is characterized by complexities often found in apatites in different rock types. In addition to the automated counting procedure, the same samples were also analyzed using conventional counting procedures. We found for all samples that the fully automated fission track counting procedure using the Autoscan System yields a larger scatter in the fission track densities measured compared to conventional (manual) track counting. This scatter typically resulted from the false identification of tracks due surface and mineralogical defects, regardless of the image filtering procedure used. Large differences between track densities analyzed with the automated counting persisted between different grains analyzed in one sample as well as between different samples. As a result of these differences a manual correction of the fully automated fission track counts is necessary for each individual surface area and grain counted. This manual correction procedure significantly increases (up to four times) the time required to analyze a sample with the automated counting procedure compared to the conventional approach.

A Fast MEANSHIFT Algorithm-Based Target Tracking System

PubMed Central

Sun, Jian

2012-01-01

Tracking moving targets in complex scenes using an active video camera is a challenging task. Tracking accuracy and efficiency are two key yet generally incompatible aspects of a Target Tracking System (TTS). A compromise scheme will be studied in this paper. A fast mean-shift-based Target Tracking scheme is designed and realized, which is robust to partial occlusion and changes in object appearance. The physical simulation shows that the image signal processing speed is >50 frame/s. PMID:22969397

A Novel Ship-Tracking Method for GF-4 Satellite Sequential Images.

PubMed

Yao, Libo; Liu, Yong; He, You

2018-06-22

The geostationary remote sensing satellite has the capability of wide scanning, persistent observation and operational response, and has tremendous potential for maritime target surveillance. The GF-4 satellite is the first geostationary orbit (GEO) optical remote sensing satellite with medium resolution in China. In this paper, a novel ship-tracking method in GF-4 satellite sequential imagery is proposed. The algorithm has three stages. First, a local visual saliency map based on local peak signal-to-noise ratio (PSNR) is used to detect ships in a single frame of GF-4 satellite sequential images. Second, the accuracy positioning of each potential target is realized by a dynamic correction using the rational polynomial coefficients (RPCs) and automatic identification system (AIS) data of ships. Finally, an improved multiple hypotheses tracking (MHT) algorithm with amplitude information is used to track ships by further removing the false targets, and to estimate ships’ motion parameters. The algorithm has been tested using GF-4 sequential images and AIS data. The results of the experiment demonstrate that the algorithm achieves good tracking performance in GF-4 satellite sequential images and estimates the motion information of ships accurately.

Parallel computation of level set method for 500 Hz visual servo control

NASA Astrophysics Data System (ADS)

Fei, Xianfeng; Igarashi, Yasunobu; Hashimoto, Koichi

2008-11-01

We propose a 2D microorganism tracking system using a parallel level set method and a column parallel vision system (CPV). This system keeps a single microorganism in the middle of the visual field under a microscope by visual servoing an automated stage. We propose a new energy function for the level set method. This function constrains an amount of light intensity inside the detected object contour to control the number of the detected objects. This algorithm is implemented in CPV system and computational time for each frame is 2 [ms], approximately. A tracking experiment for about 25 s is demonstrated. Also we demonstrate a single paramecium can be kept tracking even if other paramecia appear in the visual field and contact with the tracked paramecium.

Research on infrared small-target tracking technology under complex background

NASA Astrophysics Data System (ADS)

Liu, Lei; Wang, Xin; Chen, Jilu; Pan, Tao

2012-10-01

In this paper, some basic principles and the implementing flow charts of a series of algorithms for target tracking are described. On the foundation of above works, a moving target tracking software base on the OpenCV is developed by the software developing platform MFC. Three kinds of tracking algorithms are integrated in this software. These two tracking algorithms are Kalman Filter tracking method and Camshift tracking method. In order to explain the software clearly, the framework and the function are described in this paper. At last, the implementing processes and results are analyzed, and those algorithms for tracking targets are evaluated from the two aspects of subjective and objective. This paper is very significant in the application of the infrared target tracking technology.

Decoupling activation and exhaustion of B cells in spontaneous controllers of HIV infection

PubMed Central

Sciaranghella, Gaia; Tong, Neath; Mahan, Alison E.; Suscovich, Todd J.; Alter, Galit

2013-01-01

Objective To define the impact of chronic viremia and associated immune activation on B-cell exhaustion in HIV infection. Design Progressive HIV infection is marked by B-cell anergy and exhaustion coupled with dramatic hypergammaglobulinemia. Although both upregulation of CD95 and loss of CD21 have been used as markers of infection-associated B-cell dysfunction, little is known regarding the specific profiles of dysfunctional B cells and whether persistent viral replication and its associated immune activation play a central role in driving B-cell dysfunction. Methods Multiparameter flow cytometry was used to define the profile of dysfunctional B cells. The changes in the expression of CD21 and CD95 were tracked on B-cell subpopulations in patients with differential control of viral replication. Results Although the emergence of exhausted, CD21low tissue-like memory B cells followed similar patterns in both progressors and controllers, the frequency of CD21low activated memory B cells was lower in spontaneous controllers. Conclusion Our results suggest that the loss of CD21 and the upregulation of CD95 occur as separate events during the development of B-cell dysfunction. The loss of CD21 is a marker of B-cell exhaustion induced in the absence of appreciable viral replication, whereas the upregulation of CD95 is tightly linked to persistent viral replication and its associated immune activation. Thus, these dysfunctional profiles potentially represent two functionally distinct states within the B-cell compartment. PMID:23135171

Persistent work-life conflict and health satisfaction - A representative longitudinal study in Switzerland

PubMed Central

2011-01-01

Background The objectives of the present study were (1) to track work-life conflict in Switzerland during the years 2002 to 2008 and (2) to analyse the relationship between work-life conflict and health satisfaction, examining whether long-term work-life conflict leads to poor health satisfaction. Methods The study is based on a representative longitudinal database (Swiss Household Panel), covering a six-year period containing seven waves of data collection. The sample includes 1261 persons, with 636 men and 625 women. Data was analysed by multi-level mixed models and analysis of variance with repeated measures. Results In the overall sample, there was no linear increase or decrease of work-life conflict detected, in either its time-based or strain-based form. People with higher education were more often found to have a strong work-life conflict (time- and strain-based), and more men demonstrated a strong time-based work-life conflict than women (12.2% vs. 5%). A negative relationship between work-life conflict and health satisfaction over time was found. People reporting strong work-life conflict at every wave reported lower health satisfaction than people with consistently weak work-life conflict. However, the health satisfaction of those with a continuously strong work-life conflict did not decrease during the study period. Conclusions Both time-based and strain-based work-life conflict are strongly correlated to health satisfaction. However, no evidence was found for a persistent work-life conflict leading to poor health satisfaction. PMID:21529345

Persistent work-life conflict and health satisfaction - a representative longitudinal study in Switzerland.

PubMed

Knecht, Michaela K; Bauer, Georg F; Gutzwiller, Felix; Hämmig, Oliver

2011-04-29

The objectives of the present study were (1) to track work-life conflict in Switzerland during the years 2002 to 2008 and (2) to analyse the relationship between work-life conflict and health satisfaction, examining whether long-term work-life conflict leads to poor health satisfaction. The study is based on a representative longitudinal database (Swiss Household Panel), covering a six-year period containing seven waves of data collection. The sample includes 1261 persons, with 636 men and 625 women. Data was analysed by multi-level mixed models and analysis of variance with repeated measures. In the overall sample, there was no linear increase or decrease of work-life conflict detected, in either its time-based or strain-based form. People with higher education were more often found to have a strong work-life conflict (time- and strain-based), and more men demonstrated a strong time-based work-life conflict than women (12.2% vs. 5%). A negative relationship between work-life conflict and health satisfaction over time was found. People reporting strong work-life conflict at every wave reported lower health satisfaction than people with consistently weak work-life conflict. However, the health satisfaction of those with a continuously strong work-life conflict did not decrease during the study period. Both time-based and strain-based work-life conflict are strongly correlated to health satisfaction. However, no evidence was found for a persistent work-life conflict leading to poor health satisfaction.

Onboard Robust Visual Tracking for UAVs Using a Reliable Global-Local Object Model

PubMed Central

Fu, Changhong; Duan, Ran; Kircali, Dogan; Kayacan, Erdal

2016-01-01

In this paper, we present a novel onboard robust visual algorithm for long-term arbitrary 2D and 3D object tracking using a reliable global-local object model for unmanned aerial vehicle (UAV) applications, e.g., autonomous tracking and chasing a moving target. The first main approach in this novel algorithm is the use of a global matching and local tracking approach. In other words, the algorithm initially finds feature correspondences in a way that an improved binary descriptor is developed for global feature matching and an iterative Lucas–Kanade optical flow algorithm is employed for local feature tracking. The second main module is the use of an efficient local geometric filter (LGF), which handles outlier feature correspondences based on a new forward-backward pairwise dissimilarity measure, thereby maintaining pairwise geometric consistency. In the proposed LGF module, a hierarchical agglomerative clustering, i.e., bottom-up aggregation, is applied using an effective single-link method. The third proposed module is a heuristic local outlier factor (to the best of our knowledge, it is utilized for the first time to deal with outlier features in a visual tracking application), which further maximizes the representation of the target object in which we formulate outlier feature detection as a binary classification problem with the output features of the LGF module. Extensive UAV flight experiments show that the proposed visual tracker achieves real-time frame rates of more than thirty-five frames per second on an i7 processor with 640 × 512 image resolution and outperforms the most popular state-of-the-art trackers favorably in terms of robustness, efficiency and accuracy. PMID:27589769

Failures of Perception in the Low-Prevalence Effect: Evidence From Active and Passive Visual Search

PubMed Central

Hout, Michael C.; Walenchok, Stephen C.; Goldinger, Stephen D.; Wolfe, Jeremy M.

2017-01-01

In visual search, rare targets are missed disproportionately often. This low-prevalence effect (LPE) is a robust problem with demonstrable societal consequences. What is the source of the LPE? Is it a perceptual bias against rare targets or a later process, such as premature search termination or motor response errors? In 4 experiments, we examined the LPE using standard visual search (with eye tracking) and 2 variants of rapid serial visual presentation (RSVP) in which observers made present/absent decisions after sequences ended. In all experiments, observers looked for 2 target categories (teddy bear and butterfly) simultaneously. To minimize simple motor errors, caused by repetitive absent responses, we held overall target prevalence at 50%, with 1 low-prevalence and 1 high-prevalence target type. Across conditions, observers either searched for targets among other real-world objects or searched for specific bears or butterflies among within-category distractors. We report 4 main results: (a) In standard search, high-prevalence targets were found more quickly and accurately than low-prevalence targets. (b) The LPE persisted in RSVP search, even though observers never terminated search on their own. (c) Eye-tracking analyses showed that high-prevalence targets elicited better attentional guidance and faster perceptual decisions. And (d) even when observers looked directly at low-prevalence targets, they often (12%–34% of trials) failed to detect them. These results strongly argue that low-prevalence misses represent failures of perception when early search termination or motor errors are controlled. PMID:25915073

EXors and the stellar birthline

NASA Astrophysics Data System (ADS)

Moody, Mackenzie S. L.; Stahler, Steven W.

2017-04-01

We assess the evolutionary status of EXors. These low-mass, pre-main-sequence stars repeatedly undergo sharp luminosity increases, each a year or so in duration. We place into the HR diagram all EXors that have documented quiescent luminosities and effective temperatures, and thus determine their masses and ages. Two alternate sets of pre-main-sequence tracks are used, and yield similar results. Roughly half of EXors are embedded objects, I.e., they appear observationally as Class I or flat-spectrum infrared sources. We find that these are relatively young and are located close to the stellar birthline in the HR diagram. Optically visible EXors, on the other hand, are situated well below the birthline. They have ages of several Myr, typical of classical T Tauri stars. Judging from the limited data at hand, we find no evidence that binarity companions trigger EXor eruptions; this issue merits further investigation. We draw several general conclusions. First, repetitive luminosity outbursts do not occur in all pre-main-sequence stars, and are not in themselves a sign of extreme youth. They persist, along with other signs of activity, in a relatively small subset of these objects. Second, the very existence of embedded EXors demonstrates that at least some Class I infrared sources are not true protostars, but very young pre-main-sequence objects still enshrouded in dusty gas. Finally, we believe that the embedded pre-main-sequence phase is of observational and theoretical significance, and should be included in a more complete account of early stellar evolution.

Automated Target Acquisition, Recognition and Tracking (ATTRACT). Phase 1

NASA Technical Reports Server (NTRS)

Abdallah, Mahmoud A.

1995-01-01

The primary objective of phase 1 of this research project is to conduct multidisciplinary research that will contribute to fundamental scientific knowledge in several of the USAF critical technology areas. Specifically, neural networks, signal processing techniques, and electro-optic capabilities are utilized to solve problems associated with automated target acquisition, recognition, and tracking. To accomplish the stated objective, several tasks have been identified and were executed.

KENNEDY SPACE CENTER, FLA. - A worker calibrates a tracking telescope, part of the Distant Object Attitude Measurement System (DOAMS), located in Cocoa Beach, Fla. The telescope provides optical support for launches from KSC and Cape Canaveral.

NASA Image and Video Library

2003-09-03

KENNEDY SPACE CENTER, FLA. - A worker calibrates a tracking telescope, part of the Distant Object Attitude Measurement System (DOAMS), located in Cocoa Beach, Fla. The telescope provides optical support for launches from KSC and Cape Canaveral.

Tracking Students' Eye-Movements When Reading Learning Objects on Mobile Phones: A Discourse Analysis of Luganda Language Teacher-Trainees' Reflective Observations

ERIC Educational Resources Information Center

Kabugo, David; Muyinda, Paul B.; Masagazi, Fred. M.; Mugagga, Anthony M.; Mulumba, Mathias B.

2016-01-01

Although eye-tracking technologies such as Tobii-T120/TX and Eye-Tribe are steadily becoming ubiquitous, and while their appropriation in education can aid teachers to collect robust information on how students move their eyes when reading and engaging with different learning objects, many teachers of Luganda language are yet to gain experiences…

Tracking moving identities: after attending the right location, the identity does not come for free.

PubMed

Pinto, Yaïr; Scholte, H Steven; Lamme, V A F

2012-01-01

Although tracking identical moving objects has been studied since the 1980's, only recently the study into tracking moving objects with distinct identities has started (referred to as Multiple Identity Tracking, MIT). So far, only behavioral studies into MIT have been undertaken. These studies have left a fundamental question regarding MIT unanswered, is MIT a one-stage or a two-stage process? According to the one-stage model, after a location has been attended, the identity is released without effort. However, according to the two-stage model, there are two effortful stages in MIT, attending to a location, and attending to the identity of the object at that location. In the current study we investigated this question by measuring brain activity in response to tracking familiar and unfamiliar targets. Familiarity is known to automate effortful processes, so if attention to identify the object is needed, this should become easier. However, if no such attention is needed, familiarity can only affect other processes (such as memory for the target set). Our results revealed that on unfamiliar trials neural activity was higher in both attentional networks, and visual identification networks. These results suggest that familiarity in MIT automates attentional identification processes, thus suggesting that attentional identification is needed in MIT. This then would imply that MIT is essentially a two-stage process, since after attending the location, the identity does not seem to come for free.

Shared processing in multiple object tracking and visual working memory in the absence of response order and task order confounds

PubMed Central

Howe, Piers D. L.

2017-01-01

To understand how the visual system represents multiple moving objects and how those representations contribute to tracking, it is essential that we understand how the processes of attention and working memory interact. In the work described here we present an investigation of that interaction via a series of tracking and working memory dual-task experiments. Previously, it has been argued that tracking is resistant to disruption by a concurrent working memory task and that any apparent disruption is in fact due to observers making a response to the working memory task, rather than due to competition for shared resources. Contrary to this, in our experiments we find that when task order and response order confounds are avoided, all participants show a similar decrease in both tracking and working memory performance. However, if task and response order confounds are not adequately controlled for we find substantial individual differences, which could explain the previous conflicting reports on this topic. Our results provide clear evidence that tracking and working memory tasks share processing resources. PMID:28410383

Significantly improved precision of cell migration analysis in time-lapse video microscopy through use of a fully automated tracking system

PubMed Central

2010-01-01

Background Cell motility is a critical parameter in many physiological as well as pathophysiological processes. In time-lapse video microscopy, manual cell tracking remains the most common method of analyzing migratory behavior of cell populations. In addition to being labor-intensive, this method is susceptible to user-dependent errors regarding the selection of "representative" subsets of cells and manual determination of precise cell positions. Results We have quantitatively analyzed these error sources, demonstrating that manual cell tracking of pancreatic cancer cells lead to mis-calculation of migration rates of up to 410%. In order to provide for objective measurements of cell migration rates, we have employed multi-target tracking technologies commonly used in radar applications to develop fully automated cell identification and tracking system suitable for high throughput screening of video sequences of unstained living cells. Conclusion We demonstrate that our automatic multi target tracking system identifies cell objects, follows individual cells and computes migration rates with high precision, clearly outperforming manual procedures. PMID:20377897

Shared processing in multiple object tracking and visual working memory in the absence of response order and task order confounds.

PubMed

Lapierre, Mark D; Cropper, Simon J; Howe, Piers D L

2017-01-01

To understand how the visual system represents multiple moving objects and how those representations contribute to tracking, it is essential that we understand how the processes of attention and working memory interact. In the work described here we present an investigation of that interaction via a series of tracking and working memory dual-task experiments. Previously, it has been argued that tracking is resistant to disruption by a concurrent working memory task and that any apparent disruption is in fact due to observers making a response to the working memory task, rather than due to competition for shared resources. Contrary to this, in our experiments we find that when task order and response order confounds are avoided, all participants show a similar decrease in both tracking and working memory performance. However, if task and response order confounds are not adequately controlled for we find substantial individual differences, which could explain the previous conflicting reports on this topic. Our results provide clear evidence that tracking and working memory tasks share processing resources.

3-D rigid body tracking using vision and depth sensors.

PubMed

Gedik, O Serdar; Alatan, A Aydn

2013-10-01

In robotics and augmented reality applications, model-based 3-D tracking of rigid objects is generally required. With the help of accurate pose estimates, it is required to increase reliability and decrease jitter in total. Among many solutions of pose estimation in the literature, pure vision-based 3-D trackers require either manual initializations or offline training stages. On the other hand, trackers relying on pure depth sensors are not suitable for AR applications. An automated 3-D tracking algorithm, which is based on fusion of vision and depth sensors via extended Kalman filter, is proposed in this paper. A novel measurement-tracking scheme, which is based on estimation of optical flow using intensity and shape index map data of 3-D point cloud, increases 2-D, as well as 3-D, tracking performance significantly. The proposed method requires neither manual initialization of pose nor offline training, while enabling highly accurate 3-D tracking. The accuracy of the proposed method is tested against a number of conventional techniques, and a superior performance is clearly observed in terms of both objectively via error metrics and subjectively for the rendered scenes.

Persistent Identifiers, Discoverability and Open Science (Communication)

NASA Astrophysics Data System (ADS)

Murphy, Fiona; Lehnert, Kerstin; Hanson, Brooks

2016-04-01

Early in 2016, the American Geophysical Union announced it was incorporating ORCIDs into its submission workflows. This was accompanied by a strong statement supporting the use of other persistent identifiers - such as IGSNs, and the CrossRef open registry 'funding data'. This was partly in response to funders' desire to track and manage their outputs. However the more compelling argument, and the reason why the AGU has also signed up to the Center for Open Science's Transparency and Openness Promotion (TOP) Guidelines (http://cos.io/top), is that ultimately science and scientists will be the richer for these initiatives due to increased opportunities for interoperability, reproduceability and accreditation. The AGU has appealed to the wider community to engage with these initiatives, recognising that - unlike the introduction of Digital Object Identifiers (DOIs) for articles by CrossRef - full, enriched use of persistent identifiers throughout the scientific process requires buy-in from a range of scholarly communications stakeholders. At the same time, across the general research landscape, initiatives such as Project CRediT (contributor roles taxonomy), Publons (reviewer acknowledgements) and the forthcoming CrossRef DOI Event Tracker are contributing to our understanding and accreditation of contributions and impact. More specifically for earth science and scientists, the cross-functional Coalition for Publishing Data in the Earth and Space Sciences (COPDESS) was formed in October 2014 and is working to 'provide an organizational framework for Earth and space science publishers and data facilities to jointly implement and promote common policies and procedures for the publication and citation of data across Earth Science journals'. Clearly, the judicious integration of standards, registries and persistent identifiers such as ORCIDs and International Geo Sample Numbers (IGSNs) to the research and research output processes is key to the success of this venture. However these also give rise to a number of logistical, technological and cultural challenges. This poster seeks to identify and progress our understanding of these. The authors are keen to build knowledge from the gathering of case studies (successful or otherwise) and hear from potential collaborators in order to develop a robust structure that will empower both earth science and earth scientists and enable more nuanced, trustworthy, interoperable research in the near future.

Textual and shape-based feature extraction and neuro-fuzzy classifier for nuclear track recognition

NASA Astrophysics Data System (ADS)

Khayat, Omid; Afarideh, Hossein

2013-04-01

Track counting algorithms as one of the fundamental principles of nuclear science have been emphasized in the recent years. Accurate measurement of nuclear tracks on solid-state nuclear track detectors is the aim of track counting systems. Commonly track counting systems comprise a hardware system for the task of imaging and software for analysing the track images. In this paper, a track recognition algorithm based on 12 defined textual and shape-based features and a neuro-fuzzy classifier is proposed. Features are defined so as to discern the tracks from the background and small objects. Then, according to the defined features, tracks are detected using a trained neuro-fuzzy system. Features and the classifier are finally validated via 100 Alpha track images and 40 training samples. It is shown that principle textual and shape-based features concomitantly yield a high rate of track detection compared with the single-feature based methods.

An inexpensive programmable illumination microscope with active feedback

PubMed Central

Tompkins, Nathan; Fraden, Seth

2016-01-01

We have developed a programmable illumination system capable of tracking and illuminating numerous objects simultaneously using only low-cost and reused optical components. The active feedback control software allows for a closed-loop system that tracks and perturbs objects of interest automatically. Our system uses a static stage where the objects of interest are tracked computationally as they move across the field of view allowing for a large number of simultaneous experiments. An algorithmically determined illumination pattern can be applied anywhere in the field of view with simultaneous imaging and perturbation using different colors of light to enable spatially and temporally structured illumination. Our system consists of a consumer projector, camera, 35-mm camera lens, and a small number of other optical and scaffolding components. The entire apparatus can be assembled for under $4,000. PMID:27642182

Short-Term Persistence of "DSM-IV" ADHD Diagnoses: Influence of Context, Age, and Gender

ERIC Educational Resources Information Center

Bauermeister, Jose J.; Bird, Hector R.; Shrout, Patrick E.; Chavez, Ligia; Ramirez, Rafael; Canino, Glorisa

2011-01-01

Objective: Little is known about the effect of social context and gender on persistence of "attention-deficit/hyperactivity disorder" (ADHD) in children of early and middle school years. The study compared persistence of "DSM-IV" ADHD and ADHD not otherwise specified (NOS) over 2 years in two groups of Puerto Rican children.…

Effect of cessation of beef cattle pasture-feedlot type backgrounding operation on the persistence of antibiotic resistance genes in the environment

USDA-ARS?s Scientific Manuscript database

Introduction It is not known how removal of cattle from a backgrounding operation will affect the persistence of antibiotic resistance genes (ARGs) in the environment. Our objective was to investigate the effect of destocking on the persistence and distribution of ARGs in the backgrounding environm...

Towards practical control design using neural computation

NASA Technical Reports Server (NTRS)

Troudet, Terry; Garg, Sanjay; Mattern, Duane; Merrill, Walter

1991-01-01

The objective is to develop neural network based control design techniques which address the issue of performance/control effort tradeoff. Additionally, the control design needs to address the important issue if achieving adequate performance in the presence of actuator nonlinearities such as position and rate limits. These issues are discussed using the example of aircraft flight control. Given a set of pilot input commands, a feedforward net is trained to control the vehicle within the constraints imposed by the actuators. This is achieved by minimizing an objective function which is the sum of the tracking errors, control input rates and control input deflections. A tradeoff between tracking performance and control smoothness is obtained by varying, adaptively, the weights of the objective function. The neurocontroller performance is evaluated in the presence of actuator dynamics using a simulation of the vehicle. Appropriate selection of the different weights in the objective function resulted in the good tracking of the pilot commands and smooth neurocontrol. An extension of the neurocontroller design approach is proposed to enhance its practicality.

A Computational Model of Spatial Development

NASA Astrophysics Data System (ADS)

Hiraki, Kazuo; Sashima, Akio; Phillips, Steven

Psychological experiments on children's development of spatial knowledge suggest experience at self-locomotion with visual tracking as important factors. Yet, the mechanism underlying development is unknown. We propose a robot that learns to mentally track a target object (i.e., maintaining a representation of an object's position when outside the field-of-view) as a model for spatial development. Mental tracking is considered as prediction of an object's position given the previous environmental state and motor commands, and the current environment state resulting from movement. Following Jordan & Rumelhart's (1992) forward modeling architecture the system consists of two components: an inverse model of sensory input to desired motor commands; and a forward model of motor commands to desired sensory input (goals). The robot was tested on the `three cups' paradigm (where children are required to select the cup containing the hidden object under various movement conditions). Consistent with child development, without the capacity for self-locomotion the robot's errors are self-center based. When given the ability of self-locomotion the robot responds allocentrically.

On position/force tracking control problem of cooperative robot manipulators using adaptive fuzzy backstepping approach.

PubMed

Baigzadehnoe, Barmak; Rahmani, Zahra; Khosravi, Alireza; Rezaie, Behrooz

2017-09-01

In this paper, the position and force tracking control problem of cooperative robot manipulator system handling a common rigid object with unknown dynamical models and unknown external disturbances is investigated. The universal approximation properties of fuzzy logic systems are employed to estimate the unknown system dynamics. On the other hand, by defining new state variables based on the integral and differential of position and orientation errors of the grasped object, the error system of coordinated robot manipulators is constructed. Subsequently by defining the appropriate change of coordinates and using the backstepping design strategy, an adaptive fuzzy backstepping position tracking control scheme is proposed for multi-robot manipulator systems. By utilizing the properties of internal forces, extra terms are also added to the control signals to consider the force tracking problem. Moreover, it is shown that the proposed adaptive fuzzy backstepping position/force control approach ensures all the signals of the closed loop system uniformly ultimately bounded and tracking errors of both positions and forces can converge to small desired values by proper selection of the design parameters. Finally, the theoretic achievements are tested on the two three-link planar robot manipulators cooperatively handling a common object to illustrate the effectiveness of the proposed approach. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Motion-compensated speckle tracking via particle filtering

NASA Astrophysics Data System (ADS)

Liu, Lixin; Yagi, Shin-ichi; Bian, Hongyu

2015-07-01

Recently, an improved motion compensation method that uses the sum of absolute differences (SAD) has been applied to frame persistence utilized in conventional ultrasonic imaging because of its high accuracy and relative simplicity in implementation. However, high time consumption is still a significant drawback of this space-domain method. To seek for a more accelerated motion compensation method and verify if it is possible to eliminate conventional traversal correlation, motion-compensated speckle tracking between two temporally adjacent B-mode frames based on particle filtering is discussed. The optimal initial density of particles, the least number of iterations, and the optimal transition radius of the second iteration are analyzed from simulation results for the sake of evaluating the proposed method quantitatively. The speckle tracking results obtained using the optimized parameters indicate that the proposed method is capable of tracking the micromotion of speckle throughout the region of interest (ROI) that is superposed with global motion. The computational cost of the proposed method is reduced by 25% compared with that of the previous algorithm and further improvement is necessary.

Resolving occlusion and segmentation errors in multiple video object tracking

NASA Astrophysics Data System (ADS)

Cheng, Hsu-Yung; Hwang, Jenq-Neng

2009-02-01

In this work, we propose a method to integrate the Kalman filter and adaptive particle sampling for multiple video object tracking. The proposed framework is able to detect occlusion and segmentation error cases and perform adaptive particle sampling for accurate measurement selection. Compared with traditional particle filter based tracking methods, the proposed method generates particles only when necessary. With the concept of adaptive particle sampling, we can avoid degeneracy problem because the sampling position and range are dynamically determined by parameters that are updated by Kalman filters. There is no need to spend time on processing particles with very small weights. The adaptive appearance for the occluded object refers to the prediction results of Kalman filters to determine the region that should be updated and avoids the problem of using inadequate information to update the appearance under occlusion cases. The experimental results have shown that a small number of particles are sufficient to achieve high positioning and scaling accuracy. Also, the employment of adaptive appearance substantially improves the positioning and scaling accuracy on the tracking results.

Visual tracking using neuromorphic asynchronous event-based cameras.

PubMed

Ni, Zhenjiang; Ieng, Sio-Hoi; Posch, Christoph; Régnier, Stéphane; Benosman, Ryad

2015-04-01

This letter presents a novel computationally efficient and robust pattern tracking method based on a time-encoded, frame-free visual data. Recent interdisciplinary developments, combining inputs from engineering and biology, have yielded a novel type of camera that encodes visual information into a continuous stream of asynchronous, temporal events. These events encode temporal contrast and intensity locally in space and time. We show that the sparse yet accurately timed information is well suited as a computational input for object tracking. In this letter, visual data processing is performed for each incoming event at the time it arrives. The method provides a continuous and iterative estimation of the geometric transformation between the model and the events representing the tracked object. It can handle isometry, similarities, and affine distortions and allows for unprecedented real-time performance at equivalent frame rates in the kilohertz range on a standard PC. Furthermore, by using the dimension of time that is currently underexploited by most artificial vision systems, the method we present is able to solve ambiguous cases of object occlusions that classical frame-based techniques handle poorly.

Color Feature-Based Object Tracking through Particle Swarm Optimization with Improved Inertia Weight

PubMed Central

Guo, Siqiu; Zhang, Tao; Song, Yulong

2018-01-01

This paper presents a particle swarm tracking algorithm with improved inertia weight based on color features. The weighted color histogram is used as the target feature to reduce the contribution of target edge pixels in the target feature, which makes the algorithm insensitive to the target non-rigid deformation, scale variation, and rotation. Meanwhile, the influence of partial obstruction on the description of target features is reduced. The particle swarm optimization algorithm can complete the multi-peak search, which can cope well with the object occlusion tracking problem. This means that the target is located precisely where the similarity function appears multi-peak. When the particle swarm optimization algorithm is applied to the object tracking, the inertia weight adjustment mechanism has some limitations. This paper presents an improved method. The concept of particle maturity is introduced to improve the inertia weight adjustment mechanism, which could adjust the inertia weight in time according to the different states of each particle in each generation. Experimental results show that our algorithm achieves state-of-the-art performance in a wide range of scenarios. PMID:29690610

Color Feature-Based Object Tracking through Particle Swarm Optimization with Improved Inertia Weight.

PubMed

Guo, Siqiu; Zhang, Tao; Song, Yulong; Qian, Feng

2018-04-23

This paper presents a particle swarm tracking algorithm with improved inertia weight based on color features. The weighted color histogram is used as the target feature to reduce the contribution of target edge pixels in the target feature, which makes the algorithm insensitive to the target non-rigid deformation, scale variation, and rotation. Meanwhile, the influence of partial obstruction on the description of target features is reduced. The particle swarm optimization algorithm can complete the multi-peak search, which can cope well with the object occlusion tracking problem. This means that the target is located precisely where the similarity function appears multi-peak. When the particle swarm optimization algorithm is applied to the object tracking, the inertia weight adjustment mechanism has some limitations. This paper presents an improved method. The concept of particle maturity is introduced to improve the inertia weight adjustment mechanism, which could adjust the inertia weight in time according to the different states of each particle in each generation. Experimental results show that our algorithm achieves state-of-the-art performance in a wide range of scenarios.

Study of moving object detecting and tracking algorithm for video surveillance system

NASA Astrophysics Data System (ADS)

Wang, Tao; Zhang, Rongfu

2010-10-01

This paper describes a specific process of moving target detecting and tracking in the video surveillance.Obtain high-quality background is the key to achieving differential target detecting in the video surveillance.The paper is based on a block segmentation method to build clear background,and using the method of background difference to detecing moving target,after a series of treatment we can be extracted the more comprehensive object from original image,then using the smallest bounding rectangle to locate the object.In the video surveillance system, the delay of camera and other reasons lead to tracking lag,the model of Kalman filter based on template matching was proposed,using deduced and estimated capacity of Kalman,the center of smallest bounding rectangle for predictive value,predicted the position in the next moment may appare,followed by template matching in the region as the center of this position,by calculate the cross-correlation similarity of current image and reference image,can determine the best matching center.As narrowed the scope of searching,thereby reduced the searching time,so there be achieve fast-tracking.

Emotional-volitional components of operator reliability. [sensorimotor function testing under stress

NASA Technical Reports Server (NTRS)

Mileryan, Y. A.

1975-01-01

Sensorimotor function testing in a tracking task under stressfull working conditions established a psychological characterization for a successful aviation pilot: Motivation significantly increased the reliability and effectiveness of their work. Their acitivities were aimed at suppressing weariness and the feeling of fear caused by the stress factors; they showed patience, endurance, persistence, and a capacity for lengthy volitional efforts.

Examining the Use of Online Storytelling as a Motivation for Young Learners to Practice Narrative Skills

ERIC Educational Resources Information Center

Beckmann Wells, Patricia

2013-01-01

The purpose of this exploratory study was to examine the use of online storytelling as a motivation for young learners to practice narrative skills, measured through active choice, persistence and mental effort (Pintrich & Schunk, 2002). Web analytics was used to track 24 home schooled participants of an online application to teach a 21st…

Understanding Web Activity Patterns among Teachers, Students and Teacher Candidates

ERIC Educational Resources Information Center

Kimmons, Royce; Clark, B.; Lim, M.

2017-01-01

This study sought to understand generational and role differences in web usage of teachers, teacher candidates and K-12 students in a state in the USA (n = 2261). The researchers employed unique methods, which included using a custom-built persistent web browser to track user behaviours free of self-report, self-selection and perception bias.…

A Multination Study of Socioeconomic Inequality in Expectations for Progression to Higher Education: The Role of Between-School Tracking and Ability Stratification

ERIC Educational Resources Information Center

Parker, Philip D.; Jerrim, John; Schoon, Ingrid; Marsh, Herbert W.

2016-01-01

Persistent inequalities in educational expectations across societies are a growing concern. Recent research has explored the extent to which inequalities in education are due to primary effects (i.e., achievement differentials) versus secondary effects (i.e., choice behaviors net of achievement). We explore educational expectations in order to…

Analyzing Student Aid Packaging To Improve Low-Income and Minority Student Access, Retention and Degree Completion. AIR 1999 Annual Forum Paper.

ERIC Educational Resources Information Center

Fenske, Robert H.; Porter, John D.; DuBrock, Caryl P.

This study examined the persistence of and financial aid to needy students, underrepresented minority students, and women students, especially those majoring in science, engineering, and mathematics at a large public research university. An institutional student tracking and student financial aid database was used to follow four freshmen cohorts…

Characteristics of US Students That Pursued a STEM Major and Factors That Predicted Their Persistence in Degree Completion

ERIC Educational Resources Information Center

Mau, Wei-Cheng J.

2016-01-01

Low participation and completion rates in the science, technology, engineering, or mathematics (STEM) careers are a world-wide concern. This study tracked American college students over a 5-year period and identifies factors that lead to choosing a STEM major and in turn successfully earning a STEM degree. Characteristics of female and minority…

Portfolio optimization in enhanced index tracking with goal programming approach

NASA Astrophysics Data System (ADS)

Siew, Lam Weng; Jaaman, Saiful Hafizah Hj.; Ismail, Hamizun bin

2014-09-01

Enhanced index tracking is a popular form of passive fund management in stock market. Enhanced index tracking aims to generate excess return over the return achieved by the market index without purchasing all of the stocks that make up the index. This can be done by establishing an optimal portfolio to maximize the mean return and minimize the risk. The objective of this paper is to determine the portfolio composition and performance using goal programming approach in enhanced index tracking and comparing it to the market index. Goal programming is a branch of multi-objective optimization which can handle decision problems that involve two different goals in enhanced index tracking, a trade-off between maximizing the mean return and minimizing the risk. The results of this study show that the optimal portfolio with goal programming approach is able to outperform the Malaysia market index which is FTSE Bursa Malaysia Kuala Lumpur Composite Index because of higher mean return and lower risk without purchasing all the stocks in the market index.

Reallocating attention during multiple object tracking.

PubMed

Ericson, Justin M; Christensen, James C

2012-07-01

Wolfe, Place, and Horowitz (Psychonomic Bulletin & Review 14:344-349, 2007) found that participants were relatively unaffected by selecting and deselecting targets while performing a multiple object tracking task, such that maintaining tracking was possible for longer durations than the few seconds typically studied. Though this result was generally consistent with other findings on tracking duration (Franconeri, Jonathon, & Scimeca Psychological Science 21:920-925, 2010), it was inconsistent with research involving cuing paradigms, specifically precues (Pylyshyn & Annan Spatial Vision 19:485-504, 2006). In the present research, we broke down the addition and removal of targets into separate conditions and incorporated a simple performance model to evaluate the costs associated with the selection and deselection of moving targets. Across three experiments, we demonstrated evidence against a cost being associated with any shift in attention, but rather that varying the type of cue used for target deselection produces no additional cost to performance and that hysteresis effects are not induced by a reduction in tracking load.

Eye on the B-ALL: B-cell receptor repertoires reveal persistence of numerous B-lymphoblastic leukemia subclones from diagnosis to relapse

PubMed Central

Bashford-Rogers, R J M; Nicolaou, K A; Bartram, J; Goulden, N J; Loizou, L; Koumas, L; Chi, J; Hubank, M; Kellam, P; Costeas, P A; Vassiliou, G S

2016-01-01

The strongest predictor of relapse in B-cell acute lymphoblastic leukemia (B-ALL) is the level of persistence of tumor cells after initial therapy. The high mutation rate of the B-cell receptor (BCR) locus allows high-resolution tracking of the architecture, evolution and clonal dynamics of B-ALL. Using longitudinal BCR repertoire sequencing, we find that the BCR undergoes an unexpectedly high level of clonal diversification in B-ALL cells through both somatic hypermutation and secondary rearrangements, which can be used for tracking the subclonal composition of the disease and detect minimal residual disease with unprecedented sensitivity. We go on to investigate clonal dynamics of B-ALL using BCR phylogenetic analyses of paired diagnosis-relapse samples and find that large numbers of small leukemic subclones present at diagnosis re-emerge at relapse alongside a dominant clone. Our findings suggest that in all informative relapsed patients, the survival of large numbers of clonogenic cells beyond initial chemotherapy is a surrogate for inherent partial chemoresistance or inadequate therapy, providing an increased opportunity for subsequent emergence of fully resistant clones. These results frame early cytoreduction as an important determinant of long-term outcome. PMID:27211266

Automated Sampling Procedures Supported by High Persistence of Bacterial Fecal Indicators and Bacteroidetes Genetic Microbial Source Tracking Markers in Municipal Wastewater during Short-Term Storage at 5°C

PubMed Central

Mayer, R. E.; Vierheilig, J.; Egle, L.; Reischer, G. H.; Saracevic, E.; Mach, R. L.; Kirschner, A. K. T.; Zessner, M.; Farnleitner, A. H.

2015-01-01

Because of high diurnal water quality fluctuations in raw municipal wastewater, the use of proportional autosampling over a period of 24 h at municipal wastewater treatment plants (WWTPs) to evaluate carbon, nitrogen, and phosphorus removal has become a standard in many countries. Microbial removal or load estimation at municipal WWTPs, however, is still based on manually recovered grab samples. The goal of this study was to establish basic knowledge regarding the persistence of standard bacterial fecal indicators and Bacteroidetes genetic microbial source tracking markers in municipal wastewater in order to evaluate their suitability for automated sampling, as the potential lack of persistence is the main argument against such procedures. Raw and secondary treated wastewater of municipal origin from representative and well-characterized biological WWTPs without disinfection (organic carbon and nutrient removal) was investigated in microcosm experiments at 5 and 21°C with a total storage time of 32 h (including a 24-h autosampling component and an 8-h postsampling phase). Vegetative Escherichia coli and enterococci, as well as Clostridium perfringens spores, were selected as indicators for cultivation-based standard enumeration. Molecular analysis focused on total (AllBac) and human-associated genetic Bacteroidetes (BacHum-UCD, HF183 TaqMan) markers by using quantitative PCR, as well as 16S rRNA gene-based next-generation sequencing. The microbial parameters showed high persistence in both raw and treated wastewater at 5°C under the storage conditions used. Surprisingly, and in contrast to results obtained with treated wastewater, persistence of the microbial markers in raw wastewater was also high at 21°C. On the basis of our results, 24-h autosampling procedures with 5°C storage conditions can be recommended for the investigation of fecal indicators or Bacteroidetes genetic markers at municipal WWTPs. Such autosampling procedures will contribute to better understanding and monitoring of municipal WWTPs as sources of fecal pollution in water resources. PMID:26002900

Methods and apparatus for extraction and tracking of objects from multi-dimensional sequence data

NASA Technical Reports Server (NTRS)

Hill, Matthew L. (Inventor); Chang, Yuan-Chi (Inventor); Li, Chung-Sheng (Inventor); Castelli, Vittorio (Inventor); Bergman, Lawrence David (Inventor)

2008-01-01

An object tracking technique is provided which, given: (i) a potentially large data set; (ii) a set of dimensions along which the data has been ordered; and (iii) a set of functions for measuring the similarity between data elements, a set of objects are produced. Each of these objects is defined by a list of data elements. Each of the data elements on this list contains the probability that the data element is part of the object. The method produces these lists via an adaptive, knowledge-based search function which directs the search for high-probability data elements. This serves to reduce the number of data element combinations evaluated while preserving the most flexibility in defining the associations of data elements which comprise an object.

Methods and apparatus for extraction and tracking of objects from multi-dimensional sequence data

NASA Technical Reports Server (NTRS)

Hill, Matthew L. (Inventor); Chang, Yuan-Chi (Inventor); Li, Chung-Sheng (Inventor); Castelli, Vittorio (Inventor); Bergman, Lawrence David (Inventor)

2005-01-01

An object tracking technique is provided which, given: (i) a potentially large data set; (ii) a set of dimensions along which the data has been ordered; and (iii) a set of functions for measuring the similarity between data elements, a set of objects are produced. Each of these objects is defined by a list of data elements. Each of the data elements on this list contains the probability that the data element is part of the object. The method produces these lists via an adaptive, knowledge-based search function which directs the search for high-probability data elements. This serves to reduce the number of data element combinations evaluated while preserving the most flexibility in defining the associations of data elements which comprise an object.

Associating optical measurements of MEO and GEO objects using Population-Based Meta-Heuristic methods

NASA Astrophysics Data System (ADS)

Zittersteijn, M.; Vananti, A.; Schildknecht, T.; Dolado Perez, J. C.; Martinot, V.

2016-11-01

Currently several thousands of objects are being tracked in the MEO and GEO regions through optical means. The problem faced in this framework is that of Multiple Target Tracking (MTT). The MTT problem quickly becomes an NP-hard combinatorial optimization problem. This means that the effort required to solve the MTT problem increases exponentially with the number of tracked objects. In an attempt to find an approximate solution of sufficient quality, several Population-Based Meta-Heuristic (PBMH) algorithms are implemented and tested on simulated optical measurements. These first results show that one of the tested algorithms, namely the Elitist Genetic Algorithm (EGA), consistently displays the desired behavior of finding good approximate solutions before reaching the optimum. The results further suggest that the algorithm possesses a polynomial time complexity, as the computation times are consistent with a polynomial model. With the advent of improved sensors and a heightened interest in the problem of space debris, it is expected that the number of tracked objects will grow by an order of magnitude in the near future. This research aims to provide a method that can treat the association and orbit determination problems simultaneously, and is able to efficiently process large data sets with minimal manual intervention.

An efficient fully unsupervised video object segmentation scheme using an adaptive neural-network classifier architecture.

PubMed

Doulamis, A; Doulamis, N; Ntalianis, K; Kollias, S

2003-01-01

In this paper, an unsupervised video object (VO) segmentation and tracking algorithm is proposed based on an adaptable neural-network architecture. The proposed scheme comprises: 1) a VO tracking module and 2) an initial VO estimation module. Object tracking is handled as a classification problem and implemented through an adaptive network classifier, which provides better results compared to conventional motion-based tracking algorithms. Network adaptation is accomplished through an efficient and cost effective weight updating algorithm, providing a minimum degradation of the previous network knowledge and taking into account the current content conditions. A retraining set is constructed and used for this purpose based on initial VO estimation results. Two different scenarios are investigated. The first concerns extraction of human entities in video conferencing applications, while the second exploits depth information to identify generic VOs in stereoscopic video sequences. Human face/ body detection based on Gaussian distributions is accomplished in the first scenario, while segmentation fusion is obtained using color and depth information in the second scenario. A decision mechanism is also incorporated to detect time instances for weight updating. Experimental results and comparisons indicate the good performance of the proposed scheme even in sequences with complicated content (object bending, occlusion).

Auditory abilities of speakers who persisted, or recovered, from stuttering

PubMed Central

Howell, Peter; Davis, Stephen; Williams, Sheila M.

2006-01-01

Objective The purpose of this study was to see whether participants who persist in their stutter have poorer sensitivity in a backward masking task compared to those participants who recover from their stutter. Design The auditory sensitivity of 30 children who stutter was tested on absolute threshold, simultaneous masking, backward masking with a broadband and with a notched noise masker. The participants had been seen and diagnosed as stuttering at least 1 year before their 12th birthday. The participants were assessed again at age 12 plus to establish whether their stutter had persisted or recovered. Persistence or recovery was based on participant's, parent's and researcher's assessment and Riley's [Riley, G. D. (1994). Stuttering severity instrument for children and adults (3rd ed.). Austin, TX: Pro-Ed.] Stuttering Severity Instrument-3. Based on this assessment, 12 speakers had persisted and 18 had recovered from stuttering. Results Thresholds differed significantly between persistent and recovered groups for the broadband backward-masked stimulus (thresholds being higher for the persistent group). Conclusions Backward masking performance at teenage is one factor that distinguishes speakers who persist in their stutter from those who recover.

 Education objectives: Readers of this article should: (1) explain why auditory factors have been implicated in stuttering; (2) summarise the work that has examined whether peripheral, and/or central, hearing are problems in stuttering; (3) explain how the hearing ability of persistent and recovered stutterers may differ; (4) discuss how hearing disorders have been implicated in other language disorders. PMID:16920188

Simultaneous Tracking of Multiple Points Using a Wiimote

ERIC Educational Resources Information Center

Skeffington, Alex; Scully, Kyle

2012-01-01

This paper reviews the construction of an inexpensive motion tracking and data logging system, which can be used for a wide variety of teaching experiments ranging from entry-level physics courses to advanced courses. The system utilizes an affordable infrared camera found in a Nintendo Wiimote to track IR LEDs mounted to the objects to be…

Encoding of Others' Beliefs without Overt Instruction

ERIC Educational Resources Information Center

Cohen, Adam S.; German, Tamsin C.

2009-01-01

Under what conditions do people automatically encode and track the mental states of others? A recent investigation showed that when subjects are instructed to track the location of an object but are not instructed to track a belief about that location in a non-verbal false-belief task, they respond more slowly to questions about an agent's belief,…

Providing the Persistent Data Storage in a Software Engineering Environment Using Java/COBRA and a DBMS

NASA Technical Reports Server (NTRS)

Dhaliwal, Swarn S.

1997-01-01

An investigation was undertaken to build the software foundation for the WHERE (Web-based Hyper-text Environment for Requirements Engineering) project. The TCM (Toolkit for Conceptual Modeling) was chosen as the foundation software for the WHERE project which aims to provide an environment for facilitating collaboration among geographically distributed people involved in the Requirements Engineering process. The TCM is a collection of diagram and table editors and has been implemented in the C++ programming language. The C++ implementation of the TCM was translated into Java in order to allow the editors to be used for building various functionality of the WHERE project; the WHERE project intends to use the Web as its communication back- bone. One of the limitations of the translated software (TcmJava), which militated against its use in the WHERE project, was persistent data management mechanisms which it inherited from the original TCM; it was designed to be used in standalone applications. Before TcmJava editors could be used as a part of the multi-user, geographically distributed applications of the WHERE project, a persistent storage mechanism must be built which would allow data communication over the Internet, using the capabilities of the Web. An approach involving features of Java, CORBA (Common Object Request Broker), the Web, a middle-ware (Java Relational Binding (JRB)), and a database server was used to build the persistent data management infrastructure for the WHERE project. The developed infrastructure allows a TcmJava editor to be downloaded and run from a network host by using a JDK 1.1 (Java Developer's Kit) compatible Web-browser. The aforementioned editor establishes connection with a server by using the ORB (Object Request Broker) software and stores/retrieves data in/from the server. The server consists of a CORBA object or objects depending upon whether the data is to be made persistent on a single server or multiple servers. The CORBA object providing the persistent data server is implemented using the Java progranu-ning language. It uses the JRB to store/retrieve data in/from a relational database server. The persistent data management system provides transaction and user management facilities which allow multi-user, distributed access to the stored data in a secure manner.

Automated segmentation and tracking of non-rigid objects in time-lapse microscopy videos of polymorphonuclear neutrophils.

PubMed

Brandes, Susanne; Mokhtari, Zeinab; Essig, Fabian; Hünniger, Kerstin; Kurzai, Oliver; Figge, Marc Thilo

2015-02-01

Time-lapse microscopy is an important technique to study the dynamics of various biological processes. The labor-intensive manual analysis of microscopy videos is increasingly replaced by automated segmentation and tracking methods. These methods are often limited to certain cell morphologies and/or cell stainings. In this paper, we present an automated segmentation and tracking framework that does not have these restrictions. In particular, our framework handles highly variable cell shapes and does not rely on any cell stainings. Our segmentation approach is based on a combination of spatial and temporal image variations to detect moving cells in microscopy videos. This method yields a sensitivity of 99% and a precision of 95% in object detection. The tracking of cells consists of different steps, starting from single-cell tracking based on a nearest-neighbor-approach, detection of cell-cell interactions and splitting of cell clusters, and finally combining tracklets using methods from graph theory. The segmentation and tracking framework was applied to synthetic as well as experimental datasets with varying cell densities implying different numbers of cell-cell interactions. We established a validation framework to measure the performance of our tracking technique. The cell tracking accuracy was found to be >99% for all datasets indicating a high accuracy for connecting the detected cells between different time points. Copyright © 2014 Elsevier B.V. All rights reserved.

Robust multiperson detection and tracking for mobile service and social robots.

PubMed

Li, Liyuan; Yan, Shuicheng; Yu, Xinguo; Tan, Yeow Kee; Li, Haizhou

2012-10-01

This paper proposes an efficient system which integrates multiple vision models for robust multiperson detection and tracking for mobile service and social robots in public environments. The core technique is a novel maximum likelihood (ML)-based algorithm which combines the multimodel detections in mean-shift tracking. First, a likelihood probability which integrates detections and similarity to local appearance is defined. Then, an expectation-maximization (EM)-like mean-shift algorithm is derived under the ML framework. In each iteration, the E-step estimates the associations to the detections, and the M-step locates the new position according to the ML criterion. To be robust to the complex crowded scenarios for multiperson tracking, an improved sequential strategy to perform the mean-shift tracking is proposed. Under this strategy, human objects are tracked sequentially according to their priority order. To balance the efficiency and robustness for real-time performance, at each stage, the first two objects from the list of the priority order are tested, and the one with the higher score is selected. The proposed method has been successfully implemented on real-world service and social robots. The vision system integrates stereo-based and histograms-of-oriented-gradients-based human detections, occlusion reasoning, and sequential mean-shift tracking. Various examples to show the advantages and robustness of the proposed system for multiperson tracking from mobile robots are presented. Quantitative evaluations on the performance of multiperson tracking are also performed. Experimental results indicate that significant improvements have been achieved by using the proposed method.

Feasibility of real-time location systems in monitoring recovery after major abdominal surgery.

PubMed

Dorrell, Robert D; Vermillion, Sarah A; Clark, Clancy J

2017-12-01

Early mobilization after major abdominal surgery decreases postoperative complications and length of stay, and has become a key component of enhanced recovery pathways. However, objective measures of patient movement after surgery are limited. Real-time location systems (RTLS), typically used for asset tracking, provide a novel approach to monitoring in-hospital patient activity. The current study investigates the feasibility of using RTLS to objectively track postoperative patient mobilization. The real-time location system employs a meshed network of infrared and RFID sensors and detectors that sample device locations every 3 s resulting in over 1 million data points per day. RTLS tracking was evaluated systematically in three phases: (1) sensitivity and specificity of the tracking device using simulated patient scenarios, (2) retrospective passive movement analysis of patient-linked equipment, and (3) prospective observational analysis of a patient-attached tracking device. RTLS tracking detected a simulated movement out of a room with sensitivity of 91% and specificity 100%. Specificity decreased to 75% if time out of room was less than 3 min. All RTLS-tagged patient-linked equipment was identified for 18 patients, but measurable patient movement associated with equipment was detected for only 2 patients (11%) with 1-8 out-of-room walks per day. Ten patients were prospectively monitored using RTLS badges following major abdominal surgery. Patient movement was recorded using patient diaries, direct observation, and an accelerometer. Sensitivity and specificity of RTLS patient tracking were both 100% in detecting out-of-room ambulation and correlated well with direct observation and patient-reported ambulation. Real-time location systems are a novel technology capable of objectively and accurately monitoring patient movement and provide an innovative approach to promoting early mobilization after surgery.

Integrated track stability assessment and monitoring system (ITSAMS).

DOT National Transportation Integrated Search

2006-10-01

The overall objective of project is to continue the development of remote sensing : technologies that can be integrated and deployed in a mobile inspection vehicle i.e. Integrated : Track Stability Assessment and Monitoring System (ITSAMS).

Automated track video inspection pilot project.

DOT National Transportation Integrated Search

2013-09-01

This project had two main objectives. The first was to improve the safety of transit workers, specifically right-of-way safety for rail transit : workers through demonstration of advanced track inspection techniques that limit the inspectors expos...

Acoustic detection and monitoring for transportation infrastructure security.

DOT National Transportation Integrated Search

2009-09-01

Acoustical methods have been extensively used to locate, identify, and track objects underwater. Some of these applications include detecting and tracking submarines, marine mammal detection and identification, detection of mines and ship wrecks and ...

Image sequence analysis workstation for multipoint motion analysis

NASA Astrophysics Data System (ADS)

Mostafavi, Hassan

1990-08-01

This paper describes an application-specific engineering workstation designed and developed to analyze motion of objects from video sequences. The system combines the software and hardware environment of a modem graphic-oriented workstation with the digital image acquisition, processing and display techniques. In addition to automation and Increase In throughput of data reduction tasks, the objective of the system Is to provide less invasive methods of measurement by offering the ability to track objects that are more complex than reflective markers. Grey level Image processing and spatial/temporal adaptation of the processing parameters is used for location and tracking of more complex features of objects under uncontrolled lighting and background conditions. The applications of such an automated and noninvasive measurement tool include analysis of the trajectory and attitude of rigid bodies such as human limbs, robots, aircraft in flight, etc. The system's key features are: 1) Acquisition and storage of Image sequences by digitizing and storing real-time video; 2) computer-controlled movie loop playback, freeze frame display, and digital Image enhancement; 3) multiple leading edge tracking in addition to object centroids at up to 60 fields per second from both live input video or a stored Image sequence; 4) model-based estimation and tracking of the six degrees of freedom of a rigid body: 5) field-of-view and spatial calibration: 6) Image sequence and measurement data base management; and 7) offline analysis software for trajectory plotting and statistical analysis.

Representation of 3-Dimenstional Objects by the Rat Perirhinal Cortex

PubMed Central

Burke, S.N.; Maurer, A.P.; Hartzell, A.L.; Nematollahi, S.; Uprety, A.; Wallace, J.L.; Barnes, C.A.

2012-01-01

The perirhinal cortex (PRC) is known to play an important role in object recognition. Little is known, however, regarding the activity of PRC neurons during the presentation of stimuli that are commonly used for recognition memory tasks in rodents, that is, 3-dimensional objects. Rats in the present study were exposed to 3-dimensional objects while they traversed a circular track for food reward. Under some behavioral conditions the track contained novel objects, familiar objects, or no objects. Approximately 38% of PRC neurons demonstrated ‘object fields’ (a selective increase in firing at the location of one or more objects). Although the rats spent more time exploring the objects when they were novel compared to familiar, indicating successful recognition memory, the proportion of object fields and the firing rates of PRC neurons were not affected by the rats’ previous experience with the objects. Together these data indicate that the activity of PRC cells is powerfully affected by the presence of objects while animals navigate through an environment, but under these conditions, the firing patterns are not altered by the relative novelty of objects during successful object recognition. PMID:22987680

Compartmentalization and Transmission of Multiple Epstein-Barr Virus Strains in Asymptomatic Carriers

PubMed Central

Sitki-Green, Diane; Covington, Mary; Raab-Traub, Nancy

2003-01-01

Infection with the Epstein-Barr virus (EBV) is often subclinical in the presence of a healthy immune response; thus, asymptomatic infection is largely uncharacterized. This study analyzed the nature of EBV infection in 20 asymptomatic immunocompetent hosts over time through the identification of EBV strain variants in the peripheral blood and oral cavity. A heteroduplex tracking assay specific for the EBV gene LMP1 precisely identified the presence of multiple EBV strains in each subject. The strains present in the peripheral blood and oral cavity were often completely discordant, indicating the existence of distinct infections, and the strains present and their relative abundance changed considerably between time points. The possible transmission of strains between the oral cavity and peripheral blood compartments could be tracked within subjects, suggesting that reactivation in the oral cavity and subsequent reinfection of B lymphocytes that reenter the periphery contribute to the maintenance of persistence. In addition, distinct virus strains persisted in the oral cavity over many time points, suggesting an important role for epithelial cells in the maintenance of persistence. Asymptomatic individuals without tonsillar tissue, which is believed to be an important source of virus for the oral cavity, also exhibited multiple strains and a cyclic pattern of transmission between compartments. This study revealed that the majority of patients with infectious mononucleosis were infected with multiple strains of EBV that were also compartmentalized, suggesting that primary infection involves the transmission of multiple strains. Both the primary and carrier states of infection with EBV are more complex than previously thought. PMID:12525618

Compartmentalization and transmission of multiple epstein-barr virus strains in asymptomatic carriers.

PubMed

Sitki-Green, Diane; Covington, Mary; Raab-Traub, Nancy

2003-02-01

Infection with the Epstein-Barr virus (EBV) is often subclinical in the presence of a healthy immune response; thus, asymptomatic infection is largely uncharacterized. This study analyzed the nature of EBV infection in 20 asymptomatic immunocompetent hosts over time through the identification of EBV strain variants in the peripheral blood and oral cavity. A heteroduplex tracking assay specific for the EBV gene LMP1 precisely identified the presence of multiple EBV strains in each subject. The strains present in the peripheral blood and oral cavity were often completely discordant, indicating the existence of distinct infections, and the strains present and their relative abundance changed considerably between time points. The possible transmission of strains between the oral cavity and peripheral blood compartments could be tracked within subjects, suggesting that reactivation in the oral cavity and subsequent reinfection of B lymphocytes that reenter the periphery contribute to the maintenance of persistence. In addition, distinct virus strains persisted in the oral cavity over many time points, suggesting an important role for epithelial cells in the maintenance of persistence. Asymptomatic individuals without tonsillar tissue, which is believed to be an important source of virus for the oral cavity, also exhibited multiple strains and a cyclic pattern of transmission between compartments. This study revealed that the majority of patients with infectious mononucleosis were infected with multiple strains of EBV that were also compartmentalized, suggesting that primary infection involves the transmission of multiple strains. Both the primary and carrier states of infection with EBV are more complex than previously thought.

Specialization of Perceptual Processes.

DTIC Science & Technology

1994-09-01

population rose and fell, furniture was rearranged, a small mountain range was built in part of the lab (really), carpets were shampooed , and oce lighting...common task is the tracking of moving objects. Coombs [22] implemented a system 44 for xating and tracking objects using a stereo eye/ head system...be a person (person?). Finally, a motion unit is used to detect foot gestures. A pair of nod-of-the- head detectors were implemented and tested, but

Automation of Hessian-Based Tubularity Measure Response Function in 3D Biomedical Images.

PubMed

Dzyubak, Oleksandr P; Ritman, Erik L

2011-01-01

The blood vessels and nerve trees consist of tubular objects interconnected into a complex tree- or web-like structure that has a range of structural scale 5 μm diameter capillaries to 3 cm aorta. This large-scale range presents two major problems; one is just making the measurements, and the other is the exponential increase of component numbers with decreasing scale. With the remarkable increase in the volume imaged by, and resolution of, modern day 3D imagers, it is almost impossible to make manual tracking of the complex multiscale parameters from those large image data sets. In addition, the manual tracking is quite subjective and unreliable. We propose a solution for automation of an adaptive nonsupervised system for tracking tubular objects based on multiscale framework and use of Hessian-based object shape detector incorporating National Library of Medicine Insight Segmentation and Registration Toolkit (ITK) image processing libraries.

Bi-Objective Optimal Control Modification Adaptive Control for Systems with Input Uncertainty

NASA Technical Reports Server (NTRS)

Nguyen, Nhan T.

2012-01-01

This paper presents a new model-reference adaptive control method based on a bi-objective optimal control formulation for systems with input uncertainty. A parallel predictor model is constructed to relate the predictor error to the estimation error of the control effectiveness matrix. In this work, we develop an optimal control modification adaptive control approach that seeks to minimize a bi-objective linear quadratic cost function of both the tracking error norm and predictor error norm simultaneously. The resulting adaptive laws for the parametric uncertainty and control effectiveness uncertainty are dependent on both the tracking error and predictor error, while the adaptive laws for the feedback gain and command feedforward gain are only dependent on the tracking error. The optimal control modification term provides robustness to the adaptive laws naturally from the optimal control framework. Simulations demonstrate the effectiveness of the proposed adaptive control approach.

Attentive Tracking Disrupts Feature Binding in Visual Working Memory

PubMed Central

Fougnie, Daryl; Marois, René

2009-01-01

One of the most influential theories in visual cognition proposes that attention is necessary to bind different visual features into coherent object percepts (Treisman & Gelade, 1980). While considerable evidence supports a role for attention in perceptual feature binding, whether attention plays a similar function in visual working memory (VWM) remains controversial. To test the attentional requirements of VWM feature binding, here we gave participants an attention-demanding multiple object tracking task during the retention interval of a VWM task. Results show that the tracking task disrupted memory for color-shape conjunctions above and beyond any impairment to working memory for object features, and that this impairment was larger when the VWM stimuli were presented at different spatial locations. These results demonstrate that the role of visuospatial attention in feature binding is not unique to perception, but extends to the working memory of these perceptual representations as well. PMID:19609460

Remote Safety Monitoring for Elderly Persons Based on Omni-Vision Analysis

PubMed Central

Xiang, Yun; Tang, Yi-ping; Ma, Bao-qing; Yan, Hang-chen; Jiang, Jun; Tian, Xu-yuan

2015-01-01

Remote monitoring service for elderly persons is important as the aged populations in most developed countries continue growing. To monitor the safety and health of the elderly population, we propose a novel omni-directional vision sensor based system, which can detect and track object motion, recognize human posture, and analyze human behavior automatically. In this work, we have made the following contributions: (1) we develop a remote safety monitoring system which can provide real-time and automatic health care for the elderly persons and (2) we design a novel motion history or energy images based algorithm for motion object tracking. Our system can accurately and efficiently collect, analyze, and transfer elderly activity information and provide health care in real-time. Experimental results show that our technique can improve the data analysis efficiency by 58.5% for object tracking. Moreover, for the human posture recognition application, the success rate can reach 98.6% on average. PMID:25978761

Adaptive Shape Kernel-Based Mean Shift Tracker in Robot Vision System

PubMed Central

2016-01-01

This paper proposes an adaptive shape kernel-based mean shift tracker using a single static camera for the robot vision system. The question that we address in this paper is how to construct such a kernel shape that is adaptive to the object shape. We perform nonlinear manifold learning technique to obtain the low-dimensional shape space which is trained by training data with the same view as the tracking video. The proposed kernel searches the shape in the low-dimensional shape space obtained by nonlinear manifold learning technique and constructs the adaptive kernel shape in the high-dimensional shape space. It can improve mean shift tracker performance to track object position and object contour and avoid the background clutter. In the experimental part, we take the walking human as example to validate that our method is accurate and robust to track human position and describe human contour. PMID:27379165

The stability of weight status through the early to middle childhood years in Australia: a longitudinal study.

PubMed

Wheaton, Nikita; Millar, Lynne; Allender, Steven; Nichols, Melanie

2015-04-28

To investigate the sociodemographic and behavioural factors associated with incidence, persistence or remission of obesity in a longitudinal sample of Australian children aged 4-10 years. Nationally representative Longitudinal Study of Australian Children (LSAC). The sample for this analysis included all children in the Kinder cohort (aged 4-5 years at wave 1) who participated in all four waves of LSAC (wave 1, 2004, aged 4-5 years; wave 2, 2006, aged 6-7 years; wave 3, 2008, aged 8-9 years and wave 4, 2010, aged 10-11 years). Of the 4983 children who participated in the baseline (wave 1) survey, 4169 (83.7%) children completed all four waves of data collection. Movement of children between weight status categories over time and individual-level predictors of weight status change (sociodemographic characteristics, selected dietary and activity behaviours). The study found tracking of weight status across this period of childhood. There was an inverse association observed between socioeconomic position and persistence of overweight/obesity. Sugar-sweetened beverages and fruit and vegetable intake and screen time appeared to be important predictors of stronger tracking. Overweight and obesity established early in childhood tracks strongly to the middle childhood years in Australia, particularly among children of lower socioeconomic position and children participating in some unhealthy behaviour patterns. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Research on target tracking algorithm based on spatio-temporal context

NASA Astrophysics Data System (ADS)

Li, Baiping; Xu, Sanmei; Kang, Hongjuan

2017-07-01

In this paper, a novel target tracking algorithm based on spatio-temporal context is proposed. During the tracking process, the camera shaking or occlusion may lead to the failure of tracking. The proposed algorithm can solve this problem effectively. The method use the spatio-temporal context algorithm as the main research object. We get the first frame's target region via mouse. Then the spatio-temporal context algorithm is used to get the tracking targets of the sequence of frames. During this process a similarity measure function based on perceptual hash algorithm is used to judge the tracking results. If tracking failed, reset the initial value of Mean Shift algorithm for the subsequent target tracking. Experiment results show that the proposed algorithm can achieve real-time and stable tracking when camera shaking or target occlusion.

Track-to-track association for object matching in an inter-vehicle communication system

NASA Astrophysics Data System (ADS)

Yuan, Ting; Roth, Tobias; Chen, Qi; Breu, Jakob; Bogdanovic, Miro; Weiss, Christian A.

2015-09-01

Autonomous driving poses unique challenges for vehicle environment perception due to the complex driving environment the autonomous vehicle finds itself in and differentiates from remote vehicles. Due to inherent uncertainty of the traffic environments and incomplete knowledge due to sensor limitation, an autonomous driving system using only local onboard sensor information is generally not sufficiently enough for conducting a reliable intelligent driving with guaranteed safety. In order to overcome limitations of the local (host) vehicle sensing system and to increase the likelihood of correct detections and classifications, collaborative information from cooperative remote vehicles could substantially facilitate effectiveness of vehicle decision making process. Dedicated Short Range Communication (DSRC) system provides a powerful inter-vehicle wireless communication channel to enhance host vehicle environment perceiving capability with the aid of transmitted information from remote vehicles. However, there is a major challenge before one can fuse the DSRC-transmitted remote information and host vehicle Radar-observed information (in the present case): the remote DRSC data must be correctly associated with the corresponding onboard Radar data; namely, an object matching problem. Direct raw data association (i.e., measurement-to-measurement association - M2MA) is straightforward but error-prone, due to inherent uncertain nature of the observation data. The uncertainties could lead to serious difficulty in matching decision, especially, using non-stationary data. In this study, we present an object matching algorithm based on track-to-track association (T2TA) and evaluate the proposed approach with prototype vehicles in real traffic scenarios. To fully exploit potential of the DSRC system, only GPS position data from remote vehicle are used in fusion center (at host vehicle), i.e., we try to get what we need from the least amount of information; additional feature information can help the data association but are not currently considered. Comparing to M2MA, benefits of the T2TA object matching approach are: i) tracks taking into account important statistical information can provide more reliable inference results; ii) the track-formed smoothed trajectories can be used for an easier shape matching; iii) each local vehicle can design its own tracker and sends only tracks to fusion center to alleviate communication constraints. A real traffic study with different driving environments, based on a statistical hypothesis test, shows promising object matching results of significant practical implications.

Rossi X-Ray Timing Explorer Observations of the First Transient Z Source XTE J1701-462: Shedding New Light on Mass Accretion in Luminous Neutron Star X-Ray Binaries

NASA Astrophysics Data System (ADS)

Homan, Jeroen; van der Klis, Michiel; Wijnands, Rudy; Belloni, Tomaso; Fender, Rob; Klein-Wolt, Marc; Casella, Piergiorgio; Méndez, Mariano; Gallo, Elena; Lewin, Walter H. G.; Gehrels, Neil

2007-02-01

We report on the first 10 weeks of RXTE observations of the X-ray transient XTE J1701-462 and conclude that it had all the characteristics of the neutron star Z sources, i.e., the brightest persistent neutron star low-mass X-ray binaries. These include the typical Z-shaped tracks traced out in X-ray color diagrams and the variability components detected in the power spectra, such as kHz QPOs and normal and horizontal branch oscillations. XTE J1701-462 is the first transient Z source and provides unique insights into mass accretion rate (m˙) and luminosity dependencies in neutron star X-ray binaries. As its overall luminosity decreased, we observed a switch between two types of Z source behavior, with the branches of the Z track changing their shape and/or orientation. We interpret this as an extreme case of the more moderate long-term changes seen in the persistent Z sources and suggest that they result from changes in m˙. We also suggest that the Cyg-like Z sources (Cyg X-2, GX 5-1, and GX 340+0) are substantially more luminous (>50%) than the Sco-like Z sources (Sco X-1, GX 17+2, and GX 349+2). Adopting a possible explanation for the behavior of kHz QPOs, which involves a prompt as well as a filtered response to changes in m˙, we further propose that changes in m˙ can explain both movement along the Z track and changes in the shape of the Z track. We discuss some consequences of this and consider the possibility that the branches of the Z will smoothly evolve into the branches observed in X-ray color diagrams of the less luminous atoll sources, although not in a way that was previously suggested.

Should I Stay or Should I Leave: The Question of Tenure Track Faculty Job Satisfaction at Institutions of Higher Education

ERIC Educational Resources Information Center

Maahs-Fladung, Cathy A.

2009-01-01

The purpose of this study was to explore how tenure procedures at institutions of higher education, workload, confidence in support of teaching and research objectives, climate, culture, collegiality and salary affect job satisfaction of tenure track faculty. The study compares three different cohort groups composed of tenure-track faculty from…

[Survivability and morphologic anomalies in higher plants wolffia arrhiza following exposure to heavy ions of the galactic space radiation].

PubMed

Nevzgodina, L V; Kaminskaia, E V; Maksimova, E N; Fatsius, R; Sherrer, K; Shtraukh, V

2000-01-01

Experimental data on the effects of spaceflight factors, space radiation in particular, on higher plant Wolffia arrhiza firstly exposed in the "Bioblock" assembly and measurements made by physical track detectors of heavy ions (HI) are presented. Death of individual Wolffia plants and morphologic anomalies were the basic evaluation criteria. The peculiar feature of this biological object consists in the possibility to reveal delayed effects after 1-2 months since space flight as Wolffia has a high rate of vegetative reproduction. German investigators through microscopic examination of track detectors performed identification of individual plants affected by HI. With specially developed software and a coordinate system of supposition of biolayers and track detectors with the accuracy of 1 micron, tracks and even separate sections of individual HI tracks were determined in biological objects. Thereafter each Wolffia plant hit by HI was examined and data were compared with other variants. As a result, correlation between Wolffia death rate and morphologic anomalies were determined at different times post flight and topography of HI tracks was found. It is hypothesized that morphological anomalies in Walffia were caused by direct hits of plant germs by heavy ions or close passage of particles.