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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.

What's the object of object working memory in infancy? Unraveling 'what' and 'how many'.

PubMed

Kibbe, Melissa M; Leslie, Alan M

2013-06-01

Infants have a bandwidth-limited object working memory (WM) that can both individuate and identify objects in a scene, (answering 'how many?' or 'what?', respectively). Studies of infants' WM for objects have typically looked for limits on either 'how many' or 'what', yielding different estimates of infant capacity. Infants can keep track of about three individuals (regardless of identity), but appear to be much more limited in the number of specific identities they can recall. Why are the limits on 'how many' and 'what' different? Are the limits entirely separate, do they interact, or are they simply two different aspects of the same underlying limit? We sought to unravel these limits in a series of experiments which tested 9- and 12-month-olds' WM for object identities under varying degrees of difficulty. In a violation-of-expectation looking-time task, we hid objects one at a time behind separate screens, and then probed infants' WM for the shape identity of the penultimate object in the sequence. We manipulated the difficulty of the task by varying both the number of objects in hiding locations and the number of means by which infants could detect a shape change to the probed object. We found that 9-month-olds' WM for identities was limited by the number of hiding locations: when the probed object was one of two objects hidden (one in each of two locations), 9-month-olds succeeded, and they did so even though they were given only one means to detect the change. However, when the probed object was one of three objects hidden (one in each of three locations), they failed, even when they were given two means to detect the shape change. Twelve-month-olds, by contrast, succeeded at the most difficult task level. Results show that WM for 'how many' and for 'what' are not entirely separate. Individuated objects are tracked relatively cheaply. Maintaining bindings between indexed objects and identifying featural information incurs a greater attentional/memory cost. This cost reduces with development. We conclude that infant WM supports a small number of featureless object representations that index the current locations of objects. These can have featural information bound to them, but only at substantial cost. Copyright © 2013 Elsevier Inc. All rights reserved.

A projective reconstruction method of underground or hidden structures using atmospheric muon absorption data

NASA Astrophysics Data System (ADS)

Bonechi, L.; D'Alessandro, R.; Mori, N.; Viliani, L.

2015-02-01

Muon absorption radiography is an imaging technique based on the analysis of the attenuation of the cosmic-ray muon flux after traversing an object under examination. While this technique is now reaching maturity in the field of volcanology for the imaging of the innermost parts of the volcanic cones, its applicability to other fields of research has not yet been proved. In this paper we present a study concerning the application of the muon absorption radiography technique to the field of archaeology, and we propose a method for the search of underground cavities and structures hidden a few metres deep in the soil (patent [1]). An original geometric treatment of the reconstructed muon tracks, based on the comparison of the measured flux with a reference simulated flux, and the preliminary results of specific simulations are discussed in details.

Developing Educational Programs: Overcoming the Hidden Curriculum.

ERIC Educational Resources Information Center

Giroux, Henry A.

1978-01-01

What students learn in school is determined more by the hidden curriculum of rigid classroom structures and power relationships than formal curriculum. A less alienating classroom environment must replace these traditional structures, such as tracking, grading, and student powerlessness, if education is really to be reformed. (SJL)

Enhancing Cognition with Video Games: A Multiple Game Training Study

PubMed Central

Oei, Adam C.; Patterson, Michael D.

2013-01-01

Background Previous evidence points to a causal link between playing action video games and enhanced cognition and perception. However, benefits of playing other video games are under-investigated. We examined whether playing non-action games also improves cognition. Hence, we compared transfer effects of an action and other non-action types that required different cognitive demands. Methodology/Principal Findings We instructed 5 groups of non-gamer participants to play one game each on a mobile device (iPhone/iPod Touch) for one hour a day/five days a week over four weeks (20 hours). Games included action, spatial memory, match-3, hidden- object, and an agent-based life simulation. Participants performed four behavioral tasks before and after video game training to assess for transfer effects. Tasks included an attentional blink task, a spatial memory and visual search dual task, a visual filter memory task to assess for multiple object tracking and cognitive control, as well as a complex verbal span task. Action game playing eliminated attentional blink and improved cognitive control and multiple-object tracking. Match-3, spatial memory and hidden object games improved visual search performance while the latter two also improved spatial working memory. Complex verbal span improved after match-3 and action game training. Conclusion/Significance Cognitive improvements were not limited to action game training alone and different games enhanced different aspects of cognition. We conclude that training specific cognitive abilities frequently in a video game improves performance in tasks that share common underlying demands. Overall, these results suggest that many video game-related cognitive improvements may not be due to training of general broad cognitive systems such as executive attentional control, but instead due to frequent utilization of specific cognitive processes during game play. Thus, many video game training related improvements to cognition may be attributed to near-transfer effects. PMID:23516504

Tracking Skill Acquisition with Cognitive Diagnosis Models: A Higher-Order, Hidden Markov Model with Covariates

ERIC Educational Resources Information Center

Wang, Shiyu; Yang, Yan; Culpepper, Steven Andrew; Douglas, Jeffrey A.

2018-01-01

A family of learning models that integrates a cognitive diagnostic model and a higher-order, hidden Markov model in one framework is proposed. This new framework includes covariates to model skill transition in the learning environment. A Bayesian formulation is adopted to estimate parameters from a learning model. The developed methods are…

Factors influencing infants’ ability to update object representations in memory

PubMed Central

Moher, Mariko; Feigenson, Lisa

2013-01-01

Remembering persisting objects over occlusion is critical to representing a stable environment. Infants remember hidden objects at multiple locations and can update their representation of a hidden array when an object is added or subtracted. However, the factors influencing these updating abilities have received little systematic exploration. Here we examined the flexibility of infants’ ability to update object representations. We tested 11-month-olds in a looking-time task in which objects were added to or subtracted from two hidden arrays. Across five experiments, infants successfully updated their representations of hidden arrays when the updating occurred successively at one array before beginning at the other. But when updating required alternating between two arrays, infants failed. However, simply connecting the two arrays with a thin strip of foam-core led infants to succeed. Our results suggest that infants’ construal of an event strongly affects their ability to update memory representations of hidden objects. When construing an event as containing multiple updates to the same array, infants succeed, but when construing the event as requiring the revisiting and updating of previously attended arrays, infants fail. PMID:24049245

Student portfolios and the hidden curriculum on gender: mapping exclusion.

PubMed

Phillips, Christine B

2009-09-01

The hidden curriculum - the norms, values and practices that are transmitted to students through modelling by preceptors and teachers, and decisions about curricular exclusions and inclusions - can be profoundly important in the socialising of trainee doctors. However, tracking the hidden curriculum as it evolves can be challenging for medical schools. This study aimed to explore the content of student e-portfolios on gender issues, a key perspective often taught through a hidden curriculum. Online posts for a gender and medicine e-portfolio task completed by two cohorts of students in Year 3 of a 4-year medical course (n = 167, 66% female) were analysed using a grounded theory approach. A process of gendered 'othering' was applied to both men and women in the medical school using different pedagogical strategies. Curricular emphases on women's health and lack of support for male students to acquire gynaecological examination skills were seen as explicit ways of excluding males. For female medical students, exclusion tended to be implicit, operating through modelling and aphoristic comments about so-called 'female-friendly' career choices and the negative impact of motherhood on career. E-portfolios can be a useful way of tracking the hidden curriculum as it evolves. Responses to gendered exclusion may be developed more readily for the explicit processes impacting on male students than for the implicit processes impacting on female students, which often reflect structural issues related to training and employment.

Tracking problem solving by multivariate pattern analysis and Hidden Markov Model algorithms.

PubMed

Anderson, John R

2012-03-01

Multivariate pattern analysis can be combined with Hidden Markov Model algorithms to track the second-by-second thinking as people solve complex problems. Two applications of this methodology are illustrated with a data set taken from children as they interacted with an intelligent tutoring system for algebra. The first "mind reading" application involves using fMRI activity to track what students are doing as they solve a sequence of algebra problems. The methodology achieves considerable accuracy at determining both what problem-solving step the students are taking and whether they are performing that step correctly. The second "model discovery" application involves using statistical model evaluation to determine how many substates are involved in performing a step of algebraic problem solving. This research indicates that different steps involve different numbers of substates and these substates are associated with different fluency in algebra problem solving. Copyright © 2011 Elsevier Ltd. All rights reserved.

A Novel Extreme Learning Control Framework of Unmanned Surface Vehicles.

PubMed

Wang, Ning; Sun, Jing-Chao; Er, Meng Joo; Liu, Yan-Cheng

2016-05-01

In this paper, an extreme learning control (ELC) framework using the single-hidden-layer feedforward network (SLFN) with random hidden nodes for tracking an unmanned surface vehicle suffering from unknown dynamics and external disturbances is proposed. By combining tracking errors with derivatives, an error surface and transformed states are defined to encapsulate unknown dynamics and disturbances into a lumped vector field of transformed states. The lumped nonlinearity is further identified accurately by an extreme-learning-machine-based SLFN approximator which does not require a priori system knowledge nor tuning input weights. Only output weights of the SLFN need to be updated by adaptive projection-based laws derived from the Lyapunov approach. Moreover, an error compensator is incorporated to suppress approximation residuals, and thereby contributing to the robustness and global asymptotic stability of the closed-loop ELC system. Simulation studies and comprehensive comparisons demonstrate that the ELC framework achieves high accuracy in both tracking and approximation.

Dopamine reward prediction errors reflect hidden state inference across time

PubMed Central

Starkweather, Clara Kwon; Babayan, Benedicte M.; Uchida, Naoshige; Gershman, Samuel J.

2017-01-01

Midbrain dopamine neurons signal reward prediction error (RPE), or actual minus expected reward. The temporal difference (TD) learning model has been a cornerstone in understanding how dopamine RPEs could drive associative learning. Classically, TD learning imparts value to features that serially track elapsed time relative to observable stimuli. In the real world, however, sensory stimuli provide ambiguous information about the hidden state of the environment, leading to the proposal that TD learning might instead compute a value signal based on an inferred distribution of hidden states (a ‘belief state’). In this work, we asked whether dopaminergic signaling supports a TD learning framework that operates over hidden states. We found that dopamine signaling exhibited a striking difference between two tasks that differed only with respect to whether reward was delivered deterministically. Our results favor an associative learning rule that combines cached values with hidden state inference. PMID:28263301

Dopamine reward prediction errors reflect hidden-state inference across time.

PubMed

Starkweather, Clara Kwon; Babayan, Benedicte M; Uchida, Naoshige; Gershman, Samuel J

2017-04-01

Midbrain dopamine neurons signal reward prediction error (RPE), or actual minus expected reward. The temporal difference (TD) learning model has been a cornerstone in understanding how dopamine RPEs could drive associative learning. Classically, TD learning imparts value to features that serially track elapsed time relative to observable stimuli. In the real world, however, sensory stimuli provide ambiguous information about the hidden state of the environment, leading to the proposal that TD learning might instead compute a value signal based on an inferred distribution of hidden states (a 'belief state'). Here we asked whether dopaminergic signaling supports a TD learning framework that operates over hidden states. We found that dopamine signaling showed a notable difference between two tasks that differed only with respect to whether reward was delivered in a deterministic manner. Our results favor an associative learning rule that combines cached values with hidden-state inference.

Central Compact Objects in Kes 79 and RCW 103 as `Hidden' Magnetars with Crustal Activity

NASA Astrophysics Data System (ADS)

Popov, S. B.; Kaurov, A. A.; Kaminker, A. D.

2015-05-01

We propose that observations of `hidden' magnetars in central compact objects can be used to probe crustal activity of neutron stars with large internal magnetic fields. Estimates based on calculations by Perna & Pons, Pons & Rea and Kaminker et al. suggest that central compact objects, which are proposed to be `hidden' magnetars, must demonstrate flux variations on the time scale of months-years. However, the most prominent candidate for the `hidden' magnetars - CXO J1852.6+0040 in Kes 79 - shows constant (within error bars) flux. This can be interpreted by lower variable crustal activity than in typical magnetars. Alternatively, CXO J1852.6+0040 can be in a high state of variable activity during the whole period of observations. Then we consider the source 1E161348 - 5055 in RCW103 as another candidate. Employing a simple 2D-modelling we argue that properties of the source can be explained by the crustal activity of the magnetar type. Thus, this object may be supplemented for the three known candidates for the `hidden' magnetars among central compact objects discussed in literature.

Invisible costs, visible savings.

PubMed

Lefever, G

1999-08-01

By identifying hidden inventory costs, nurse managers can save money for the organization. Some measures include tracking and standardizing supplies, accurately evaluating patients' needs, and making informed purchasing decisions.

The Relationship among Localization Skill, Existence Constancy and Object Permanence.

ERIC Educational Resources Information Center

Townes-Rosenwein, Linda

Two component skills of object permanence were studied: existence constancy -- the infants' ability to expect that an object continues to exist after it is hidden, and localization skill -- infants' ability to search in the correct place for a hidden object. Contradictions within the literature may occur because of task lability caused by failure…

Vehicle and cargo inspection system

NASA Astrophysics Data System (ADS)

Verbinski, Victor V.; Orphan, Victor J.

1997-02-01

Vehicle and Cargo Inspection System (VACIS) is comprised of a 1 Curie 137Cs gamma-ray source in a shield and collimator which produces a fan-shaped beam designed to intercept a vertical array of gama-ray detectors contained in a tower structure. The source and detector modules straddle the vehicle or container being inspected and are mounted on self-propelled trolleys which travel in synchronization along two parallel tracks covering the length of the scanned object. The signals from the gamma-ray detector array are processed and displayed so as to produce a 2D gamma-radiographic image of the object. Testing of the system on a variety of empty and lightly-loaded vehicles and containers has demonstrated the effectiveness of VACIS in detecting hidden contraband. For example, a small sample of cocaine only 1.5 inches thick was readily detected in a container.

Do the Eyes Have It? Using Eye Tracking to Assess Students Cognitive Dimensions

ERIC Educational Resources Information Center

Nisiforou, Efi A.; Laghos, Andrew

2013-01-01

Field dependence/independence (FD/FI) is a significant dimension of cognitive styles. The paper presents results of a study that seeks to identify individuals' level of field independence during visual stimulus tasks processing. Specifically, it examined the relationship between the Hidden Figure Test (HFT) scores and the eye tracking metrics.…

Hidden Communicative Competence: Case Study Evidence Using Eye-Tracking and Video Analysis

ERIC Educational Resources Information Center

Grayson, Andrew; Emerson, Anne; Howard-Jones, Patricia; O'Neil, Lynne

2012-01-01

A facilitated communication (FC) user with an autism spectrum disorder produced sophisticated texts by pointing, with physical support, to letters on a letterboard while their eyes were tracked and while their pointing movements were video recorded. This FC user has virtually no independent means of expression, and is held to have no literacy…

The Haskins Optically Corrected Ultrasound System

ERIC Educational Resources Information Center

Whalen, D. H.; Iskarous, Khalil; Tiede, Mark K.; Ostry, David J.; Lehnert-LeHouillier, Heike; Vatikiotis-Bateson, Eric; Hailey, Donald S.

2005-01-01

The tongue is critical in the production of speech, yet its nature has made it difficult to measure. Not only does its ability to attain complex shapes make it difficult to track, it is also largely hidden from view during speech. The present article describes a new combination of optical tracking and ultrasound imaging that allows for a…

Object Permanence After a 24-Hr Delay and Leaving the Locale of Disappearance: The Role of Memory, Space, and Identity

PubMed Central

Moore, M. Keith; Meltzoff, Andrew N.

2005-01-01

Fourteen-month-old infants saw an object hidden inside a container and were removed from the disappearance locale for 24 hr. Upon their return, they searched correctly for the hidden object, demonstrating object permanence and long-term memory. Control infants who saw no disappearance did not search. In Experiment 2, infants returned to see the container either in the same or a different room. Performance by room-change infants dropped to baseline levels, suggesting that infant search for hidden objects is guided by numerical identity. Infants seek the individual object that disappeared, which exists in its original location, not in a different room. A new behavior, identity-verifying search, was discovered and quantified. Implications are drawn for memory, spatial understanding, object permanence, and object identity. PMID:15238047

Object permanence after a 24-hr delay and leaving the locale of disappearance: the role of memory, space, and identity.

PubMed

Moore, M Keith; Meltzoff, Andrew N

2004-07-01

Fourteen-month-old infants saw an object hidden inside a container and were removed from the disappearance locale for 24 hr. Upon their return, they searched correctly for the hidden object, demonstrating object permanence and long-term memory. Control infants who saw no disappearance did not search. In Experiment 2, infants returned to see the container either in the same or a different room. Performance by room-change infants dropped to baseline levels, suggesting that infant search for hidden objects is guided by numerical identity. Infants seek the individual object that disappeared, which exists in its original location, not in a different room. A new behavior, identity-verifying search, was discovered and quantified. Implications are drawn for memory, spatial understanding, object permanence, and object identity. Copyright 2004 APA, all rights reserved

Chimpanzees (Pan troglodytes) use markers to monitor the movement of a hidden item.

PubMed

Beran, Michael J; Beran, Mary M; Menzel, Charles R

2005-10-01

Four chimpanzees (Pan troglodytes) monitored the movement of hidden items in arrays of opaque cups. A chocolate candy was hidden in an array of four cups and temporarily presented paper markers indicated the location of the candy (which otherwise was not visible). These markers were either non-symbolic or symbolic (lexigram) stimuli that in other contexts acted as a label for the hidden candy, and the array was either rotated 180 degrees after the marker was removed or the array remained in the same location. For three of four chimpanzees, performance was better than chance in all conditions and there was no effect of the type of marker. These experiments indicate that chimpanzees can track the movement of a hidden item in an array of identical cups even when they never see the item itself, but only see a temporarily presented marker for the location of that item. However, there was no benefit to the use of symbolic as opposed to non-symbolic stimuli in this performance.

"Core Knowledges": A Dissociation between Spatiotemporal Knowledge and Contact-Mechanics in a Non-Human Primate?

ERIC Educational Resources Information Center

Santos, Laurie R.

2004-01-01

Human toddlers demonstrate striking failures when searching for hidden objects that interact with other objects, yet successfully locate hidden objects that do not undergo mechanical interactions. This pattern hints at a developmental dissociation between contact-mechanical and spatiotemporal knowledge. Recent studies suggest that adult non-human…

A memory span of one? Object identification in 6.5-month-old infants.

PubMed

Káldy, Zsuzsa; Leslie, Alan M

2005-09-01

Infants' abilities to identify objects based on their perceptual features develop gradually during the first year and possibly beyond. Earlier we reported [Káldy, Z., & Leslie, A. M. (2003). Identification of objects in 9-month-old infants: Integrating 'what' and 'where' information. Developmental Science, 6, 360-373] that infants at 9 months of age are able to use shape information to identify two objects and follow their spatiotemporal trajectories behind occlusion. On the other hand, another recent study suggests that infants at 4-5 months of age cannot identify objects by features and bind them to locations [Mareschal, D., & Johnson, M. H. (2003). The "what" and "where" of object representations in infancy. Cognition, 88, 259-276]. In the current study, we investigated the developmental steps between these two benchmark ages by testing 6.5-month-old infants. Experiment 1 and 2 adapted the paradigm used in our previous studies with 9-month-olds that involves two objects hidden sequentially behind separate occluders. This technique allows us to address object identification and to examine whether only one or both object identities are being tracked. Results of experiment 1 showed that 6.5-month-old infants could identify at least one of two objects based on shape and experiment 2 found that this ability holds for only one, the last object hidden. We propose that at this age, infants' working memory capacity is limited to one occluded object if there is a second intervening hiding. If their attention is distracted by an intervening object during the memory maintenance period, the memory of the first object identity appears to be lost. Results of experiment 3 supported this hypothesis with a simpler one-screen setup. Finally, results of experiment 4 show that temporal decay of the memory trace (without an intervening hiding) by itself cannot explain the observed pattern of results. Taken together, our findings suggest that at six months of age infants can store but a single object representation with bound shape information, most likely in the ventral stream. The memory span of one may be due to immaturity of the neural structures underlying working memory such that intervening items overwrite the existing storage.

Object Permanence After a 24-Hr Delay and Leaving the Locale of Disappearance: The Role of Memory, Space, and Identity

ERIC Educational Resources Information Center

Moore, M. Keith; Meltzoff, Andrew N.

2004-01-01

Fourteen-month-old infants saw an object hidden inside a container and were removed from the disappearance locale for 24 hr. Upon their return, they searched correctly for the hidden object, demonstrating object permanence and long-term memory. Control infants who saw no disappearance did not search. In Experiment 2, infants returned to see the…

Object permanence in the food-storing coal tit (Periparus ater) and the non-storing great tit (Parus major): Is the mental representation required?

PubMed

Marhounová, Lucie; Frynta, Daniel; Fuchs, Roman; Landová, Eva

2017-05-01

Object permanence is a cognitive ability that enables animals to mentally represent the continuous existence of temporarily hidden objects. Generally, it develops gradually through six qualitative stages, the evolution of which may be connected with some specific ecological and behavioral factors. In birds, the advanced object permanence skills were reported in several storing species of the Corvidae family. In order to test the association between food-storing and achieved performance within the stages, we compared food-storing coal tits (Periparus ater) and nonstoring great tits (Parus major) using an adapted version of Uzgiris & Hunt's Scale 1 tasks. The coal tits significantly outperformed the great tits in searching for completely hidden objects. Most of the great tits could not solve the task when the object disappeared completely. However, the upper limit for both species is likely to be Stage 4. The coal tits could solve problems with simply hidden objects, but they used alternative strategies rather than mental representation when searching for completely hidden objects, especially if choosing between two locations. Our results also suggest that neophobia did not affect the overall performance in the object permanence tasks. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Something Old, Something New: A Developmental Transition from Familiarity to Novelty Preferences with Hidden Objects

ERIC Educational Resources Information Center

Shinskey, Jeanne L.; Munakata, Yuko

2010-01-01

Novelty seeking is viewed as adaptive, and novelty preferences in infancy predict cognitive performance into adulthood. Yet 7-month-olds prefer familiar stimuli to novel ones when searching for hidden objects, in contrast to their strong novelty preferences with visible objects (Shinskey & Munakata, 2005). According to a graded representations…

From detection to deflection: Mitigation techniques for hidden global threats of natural space objects with short warning time

NASA Astrophysics Data System (ADS)

Hussein, Alaa; Rozenheck, Oshri; Entrena Utrilla, Carlos Manuel

2016-09-01

Throughout recorded history, hundreds of Earth impacts have been reported, with some catastrophic localized consequences. Based on the International Space University (ISU) Planetary Defense project named READI, we address the impact event problem by giving recommendations for the development of a planetary defense program. This paper reviews the current detection and tracking techniques and gives a set of recommendations for a better preparation to shield Earth from asteroid and cometary impacts. We also extend the use of current deflection techniques and propose a new compilation of those to deflect medium-sized potentially hazardous objects (PHOs). Using an array of techniques from high-energy lasers to defensive missiles, we present a set of protective layers to defend our planet. The paper focused on threats with a short warning period from discovery to impact with Earth, within few years.

WE-G-213CD-03: A Dual Complementary Verification Method for Dynamic Tumor Tracking on Vero SBRT.

PubMed

Poels, K; Depuydt, T; Verellen, D; De Ridder, M

2012-06-01

to use complementary cine EPID and gimbals log file analysis for in-vivo tracking accuracy monitoring. A clinical prototype of dynamic tracking (DT) was installed on the Vero SBRT system. This prototype version allowed tumor tracking by gimballed linac rotations using an internal-external correspondence model. The DT prototype software allowed the detailed logging of all applied gimbals rotations during tracking. The integration of an EPID on the vero system allowed the acquisition of cine EPID images during DT. We quantified the tracking error on cine EPID (E-EPID) by subtracting the target center (fiducial marker detection) and the field centroid. Dynamic gimbals log file information was combined with orthogonal x-ray verification images to calculate the in-vivo tracking error (E-kVLog). The correlation between E-kVLog and E-EPID was calculated for validation of the gimbals log file. Further, we investigated the sensitivity of the log file tracking error by introducing predefined systematic tracking errors. As an application we calculate gimbals log file tracking error for dynamic hidden target tests to investigate gravity effects and decoupled gimbals rotation from gantry rotation. Finally, calculating complementary cine EPID and log file tracking errors evaluated the clinical accuracy of dynamic tracking. A strong correlation was found between log file and cine EPID tracking error distribution during concurrent measurements (R=0.98). We found sensitivity in the gimbals log files to detect a systematic tracking error up to 0.5 mm. Dynamic hidden target tests showed no gravity influence on tracking performance and high degree of decoupled gimbals and gantry rotation during dynamic arc dynamic tracking. A submillimetric agreement between clinical complementary tracking error measurements was found. Redundancy of the internal gimbals log file with x-ray verification images with complementary independent cine EPID images was implemented to monitor the accuracy of gimballed tumor tracking on Vero SBRT. Research was financially supported by the Flemish government (FWO), Hercules Foundation and BrainLAB AG. © 2012 American Association of Physicists in Medicine.

Hidden Farmworker Labor Camps in North Carolina: An Indicator of Structural Vulnerability

PubMed Central

Summers, Phillip; Quandt, Sara A.; Talton, Jennifer W.; Galván, Leonardo

2015-01-01

Objectives. We used geographic information systems (GIS) to delineate whether farmworker labor camps were hidden and to determine whether hidden camps differed from visible camps in terms of physical and resident characteristics. Methods. We collected data using observation, interview, and public domain GIS data for 180 farmworker labor camps in east central North Carolina. A hidden camp was defined as one that was at least 0.15 miles from an all-weather road or located behind natural or manufactured objects. Hidden camps were compared with visible camps in terms of physical and resident characteristics. Results. More than one third (37.8%) of the farmworker labor camps were hidden. Hidden camps were significantly larger (42.7% vs 17.0% with 21 or more residents; P ≤ .001; and 29.4% vs 13.5% with 3 or more dwellings; P = .002) and were more likely to include barracks (50% vs 19.6%; P ≤ .001) than were visible camps. Conclusions. Poor housing conditions in farmworker labor camps often go unnoticed because they are hidden in the rural landscape, increasing farmworker vulnerability. Policies that promote greater community engagement with farmworker labor camp residents to reduce structural vulnerability should be considered. PMID:26469658

A Hidden Markov Model for Single Particle Tracks Quantifies Dynamic Interactions between LFA-1 and the Actin Cytoskeleton

PubMed Central

Das, Raibatak; Cairo, Christopher W.; Coombs, Daniel

2009-01-01

The extraction of hidden information from complex trajectories is a continuing problem in single-particle and single-molecule experiments. Particle trajectories are the result of multiple phenomena, and new methods for revealing changes in molecular processes are needed. We have developed a practical technique that is capable of identifying multiple states of diffusion within experimental trajectories. We model single particle tracks for a membrane-associated protein interacting with a homogeneously distributed binding partner and show that, with certain simplifying assumptions, particle trajectories can be regarded as the outcome of a two-state hidden Markov model. Using simulated trajectories, we demonstrate that this model can be used to identify the key biophysical parameters for such a system, namely the diffusion coefficients of the underlying states, and the rates of transition between them. We use a stochastic optimization scheme to compute maximum likelihood estimates of these parameters. We have applied this analysis to single-particle trajectories of the integrin receptor lymphocyte function-associated antigen-1 (LFA-1) on live T cells. Our analysis reveals that the diffusion of LFA-1 is indeed approximately two-state, and is characterized by large changes in cytoskeletal interactions upon cellular activation. PMID:19893741

Sound effects: Multimodal input helps infants find displaced objects.

PubMed

Shinskey, Jeanne L

2017-09-01

Before 9 months, infants use sound to retrieve a stationary object hidden by darkness but not one hidden by occlusion, suggesting auditory input is more salient in the absence of visual input. This article addresses how audiovisual input affects 10-month-olds' search for displaced objects. In AB tasks, infants who previously retrieved an object at A subsequently fail to find it after it is displaced to B, especially following a delay between hiding and retrieval. Experiment 1 manipulated auditory input by keeping the hidden object audible versus silent, and visual input by presenting the delay in the light versus dark. Infants succeeded more at B with audible than silent objects and, unexpectedly, more after delays in the light than dark. Experiment 2 presented both the delay and search phases in darkness. The unexpected light-dark difference disappeared. Across experiments, the presence of auditory input helped infants find displaced objects, whereas the absence of visual input did not. Sound might help by strengthening object representation, reducing memory load, or focusing attention. This work provides new evidence on when bimodal input aids object processing, corroborates claims that audiovisual processing improves over the first year of life, and contributes to multisensory approaches to studying cognition. Statement of contribution What is already known on this subject Before 9 months, infants use sound to retrieve a stationary object hidden by darkness but not one hidden by occlusion. This suggests they find auditory input more salient in the absence of visual input in simple search tasks. After 9 months, infants' object processing appears more sensitive to multimodal (e.g., audiovisual) input. What does this study add? This study tested how audiovisual input affects 10-month-olds' search for an object displaced in an AB task. Sound helped infants find displaced objects in both the presence and absence of visual input. Object processing becomes more sensitive to bimodal input as multisensory functions develop across the first year. © 2016 The British Psychological Society.

Improved Leg Tracking Considering Gait Phase and Spline-Based Interpolation during Turning Motion in Walk Tests.

PubMed

Yorozu, Ayanori; Moriguchi, Toshiki; Takahashi, Masaki

2015-09-04

Falling is a common problem in the growing elderly population, and fall-risk assessment systems are needed for community-based fall prevention programs. In particular, the timed up and go test (TUG) is the clinical test most often used to evaluate elderly individual ambulatory ability in many clinical institutions or local communities. This study presents an improved leg tracking method using a laser range sensor (LRS) for a gait measurement system to evaluate the motor function in walk tests, such as the TUG. The system tracks both legs and measures the trajectory of both legs. However, both legs might be close to each other, and one leg might be hidden from the sensor. This is especially the case during the turning motion in the TUG, where the time that a leg is hidden from the LRS is longer than that during straight walking and the moving direction rapidly changes. These situations are likely to lead to false tracking and deteriorate the measurement accuracy of the leg positions. To solve these problems, a novel data association considering gait phase and a Catmull-Rom spline-based interpolation during the occlusion are proposed. From the experimental results with young people, we confirm   that the proposed methods can reduce the chances of false tracking. In addition, we verify the measurement accuracy of the leg trajectory compared to a three-dimensional motion analysis system (VICON).

Optimizing Likelihood Models for Particle Trajectory Segmentation in Multi-State Systems.

PubMed

Young, Dylan Christopher; Scrimgeour, Jan

2018-06-19

Particle tracking offers significant insight into the molecular mechanics that govern the behav- ior of living cells. The analysis of molecular trajectories that transition between different motive states, such as diffusive, driven and tethered modes, is of considerable importance, with even single trajectories containing significant amounts of information about a molecule's environment and its interactions with cellular structures. Hidden Markov models (HMM) have been widely adopted to perform the segmentation of such complex tracks. In this paper, we show that extensive analysis of hidden Markov model outputs using data derived from multi-state Brownian dynamics simulations can be used both for the optimization of the likelihood models used to describe the states of the system and for characterization of the technique's failure mechanisms. This analysis was made pos- sible by the implementation of parallelized adaptive direct search algorithm on a Nvidia graphics processing unit. This approach provides critical information for the visualization of HMM failure and successful design of particle tracking experiments where trajectories contain multiple mobile states. © 2018 IOP Publishing Ltd.

78 FR 17744 - Culturally Significant Objects Imported for Exhibition Determinations: “Maya: Hidden Worlds...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-03-22

... DEPARTMENT OF STATE [Public Notice 8249] Culturally Significant Objects Imported for Exhibition Determinations: ``Maya: Hidden Worlds Revealed'' SUMMARY: Notice is hereby given of the following determinations... Worlds Revealed,'' imported from abroad for temporary exhibition within the United States, are of...

SU-E-J-191: Motion Prediction Using Extreme Learning Machine in Image Guided Radiotherapy

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

Jia, J; Cao, R; Pei, X

Purpose: Real-time motion tracking is a critical issue in image guided radiotherapy due to the time latency caused by image processing and system response. It is of great necessity to fast and accurately predict the future position of the respiratory motion and the tumor location. Methods: The prediction of respiratory position was done based on the positioning and tracking module in ARTS-IGRT system which was developed by FDS Team (www.fds.org.cn). An approach involving with the extreme learning machine (ELM) was adopted to predict the future respiratory position as well as the tumor’s location by training the past trajectories. For themore » training process, a feed-forward neural network with one single hidden layer was used for the learning. First, the number of hidden nodes was figured out for the single layered feed forward network (SLFN). Then the input weights and hidden layer biases of the SLFN were randomly assigned to calculate the hidden neuron output matrix. Finally, the predicted movement were obtained by applying the output weights and compared with the actual movement. Breathing movement acquired from the external infrared markers was used to test the prediction accuracy. And the implanted marker movement for the prostate cancer was used to test the implementation of the tumor motion prediction. Results: The accuracy of the predicted motion and the actual motion was tested. Five volunteers with different breathing patterns were tested. The average prediction time was 0.281s. And the standard deviation of prediction accuracy was 0.002 for the respiratory motion and 0.001 for the tumor motion. Conclusion: The extreme learning machine method can provide an accurate and fast prediction of the respiratory motion and the tumor location and therefore can meet the requirements of real-time tumor-tracking in image guided radiotherapy.« less

Automated tracking, segmentation and trajectory classification of pelvic organs on dynamic MRI.

PubMed

Nekooeimehr, Iman; Lai-Yuen, Susana; Bao, Paul; Weitzenfeld, Alfredo; Hart, Stuart

2016-08-01

Pelvic organ prolapse is a major health problem in women where pelvic floor organs (bladder, uterus, small bowel, and rectum) fall from their normal position and bulge into the vagina. Dynamic Magnetic Resonance Imaging (DMRI) is presently used to analyze the organs' movements from rest to maximum strain providing complementary support for diagnosis. However, there is currently no automated or quantitative approach to measure the movement of the pelvic organs and their correlation with the severity of prolapse. In this paper, a two-stage method is presented to automatically track and segment pelvic organs on DMRI followed by a multiple-object trajectory classification method to improve the diagnosis of pelvic organ prolapse. Organs are first tracked using particle filters and K-means clustering with prior information. Then, they are segmented using the convex hull of the cluster of particles. Finally, the trajectories of the pelvic organs are modeled using a new Coupled Switched Hidden Markov Model (CSHMM) to classify the severity of pelvic organ prolapse. The tracking and segmentation results are validated using Dice Similarity Index (DSI) whereas the classification results are compared with two manual clinical measurements. Results demonstrate that the presented method is able to automatically track and segment pelvic organs with a DSI above 82% for 26 out of 46 cases and DSI above 75% for all 46 tested cases. The accuracy of the trajectory classification model is also better than current manual measurements.

Tumor propagation model using generalized hidden Markov model

NASA Astrophysics Data System (ADS)

Park, Sun Young; Sargent, Dustin

2017-02-01

Tumor tracking and progression analysis using medical images is a crucial task for physicians to provide accurate and efficient treatment plans, and monitor treatment response. Tumor progression is tracked by manual measurement of tumor growth performed by radiologists. Several methods have been proposed to automate these measurements with segmentation, but many current algorithms are confounded by attached organs and vessels. To address this problem, we present a new generalized tumor propagation model considering time-series prior images and local anatomical features using a Hierarchical Hidden Markov model (HMM) for tumor tracking. First, we apply the multi-atlas segmentation technique to identify organs/sub-organs using pre-labeled atlases. Second, we apply a semi-automatic direct 3D segmentation method to label the initial boundary between the lesion and neighboring structures. Third, we detect vessels in the ROI surrounding the lesion. Finally, we apply the propagation model with the labeled organs and vessels to accurately segment and measure the target lesion. The algorithm has been designed in a general way to be applicable to various body parts and modalities. In this paper, we evaluate the proposed algorithm on lung and lung nodule segmentation and tracking. We report the algorithm's performance by comparing the longest diameter and nodule volumes using the FDA lung Phantom data and a clinical dataset.

Uncovering hidden nodes in complex networks in the presence of noise

PubMed Central

Su, Ri-Qi; Lai, Ying-Cheng; Wang, Xiao; Do, Younghae

2014-01-01

Ascertaining the existence of hidden objects in a complex system, objects that cannot be observed from the external world, not only is curiosity-driven but also has significant practical applications. Generally, uncovering a hidden node in a complex network requires successful identification of its neighboring nodes, but a challenge is to differentiate its effects from those of noise. We develop a completely data-driven, compressive-sensing based method to address this issue by utilizing complex weighted networks with continuous-time oscillatory or discrete-time evolutionary-game dynamics. For any node, compressive sensing enables accurate reconstruction of the dynamical equations and coupling functions, provided that time series from this node and all its neighbors are available. For a neighboring node of the hidden node, this condition cannot be met, resulting in abnormally large prediction errors that, counterintuitively, can be used to infer the existence of the hidden node. Based on the principle of differential signal, we demonstrate that, when strong noise is present, insofar as at least two neighboring nodes of the hidden node are subject to weak background noise only, unequivocal identification of the hidden node can be achieved. PMID:24487720

Desktop computer graphics for RMS/payload handling flight design

NASA Technical Reports Server (NTRS)

Homan, D. J.

1984-01-01

A computer program, the Multi-Adaptive Drawings, Renderings and Similitudes (MADRAS) program, is discussed. The modeling program, written for a desktop computer system (the Hewlett-Packard 9845/C), is written in BASIC and uses modular construction of objects while generating both wire-frame and hidden-line drawings from any viewpoint. The dimensions and placement of objects are user definable. Once the hidden-line calculations are made for a particular viewpoint, the viewpoint may be rotated in pan, tilt, and roll without further hidden-line calculations. The use and results of this program are discussed.

Disappearing Decalage: Object Search in Light and Dark at 6 Months

ERIC Educational Resources Information Center

Shinskey, Jeanne L.

2012-01-01

Infants search for an object hidden by an occluder in the light months later than one hidden by darkness. One explanation attributes this decalage to easier action demands in darkness versus occlusion, whereas another attributes it to easier representation demands in darkness versus occlusion. However, search tasks typically confound these two…

Cross-Sensory Correspondences: Heaviness is Dark and Low-Pitched.

PubMed

Walker, Peter; Scallon, Gabrielle; Francis, Brian

2017-07-01

Everyday language reveals how stimuli encoded in one sensory feature domain can possess qualities normally associated with a different domain (e.g., higher pitch sounds are bright, light in weight, sharp, and thin). Such cross-sensory associations appear to reflect crosstalk among aligned (corresponding) feature dimensions, including brightness, heaviness, and sharpness. Evidence for heaviness being one such dimension is very limited, with heaviness appearing primarily as a verbal associate of other feature contrasts (e.g., darker objects and lower pitch sounds are heavier than their opposites). Given the presumed bidirectionality of the crosstalk between corresponding dimensions, heaviness should itself induce the cross-sensory associations observed elsewhere, including with brightness and pitch. Taking care to dissociate effects arising from the size and mass of an object, this is confirmed. When hidden objects varying independently in size and mass are lifted, objects that feel heavier are judged to be darker and to make lower pitch sounds than objects feeling less heavy. These judgements track the changes in perceived heaviness induced by the size-weight illusion. The potential involvement of language, natural scene statistics, and Bayesian processes in correspondences, and the effects they induce, is considered.

Searching for confining hidden valleys at LHCb, ATLAS, and CMS

NASA Astrophysics Data System (ADS)

Pierce, Aaron; Shakya, Bibhushan; Tsai, Yuhsin; Zhao, Yue

2018-05-01

We explore strategies for probing hidden valley scenarios exhibiting confinement. Such scenarios lead to a moderate multiplicity of light hidden hadrons for generic showering and hadronization similar to QCD. Their decays are typically soft and displaced, making them challenging to probe with traditional LHC searches. We show that the low trigger requirements and excellent track and vertex reconstruction at LHCb provide a favorable environment to search for such signals. We propose novel search strategies in both muonic and hadronic channels. We also study existing ATLAS and CMS searches and compare them with our proposals at LHCb. We find that the reach at LHCb is generically better in the parameter space we consider here, even with optimistic background estimations for ATLAS and CMS searches. We discuss potential modifications at ATLAS and CMS that might make these experiments competitive with the LHCb reach. Our proposed searches can be applied to general hidden valley models as well as exotic Higgs boson decays, such as in twin Higgs models.

Hidden Broad-line Regions in Seyfert 2 Galaxies: From the Spectropolarimetric Perspective

NASA Astrophysics Data System (ADS)

Du, Pu; Wang, Jian-Min; Zhang, Zhi-Xiang

2017-05-01

The hidden broad-line regions (BLRs) in Seyfert 2 galaxies, which display broad emission lines (BELs) in their polarized spectra, are a key piece of evidence in support of the unified model for active galactic nuclei (AGNs). However, the detailed kinematics and geometry of hidden BLRs are still not fully understood. The virial factor obtained from reverberation mapping of type 1 AGNs may be a useful diagnostic of the nature of hidden BLRs in type 2 objects. In order to understand the hidden BLRs, we compile six type 2 objects from the literature with polarized BELs and dynamical measurements of black hole masses. All of them contain pseudobulges. We estimate their virial factors, and find the average value is 0.60 and the standard deviation is 0.69, which agree well with the value of type 1 AGNs with pseudobulges. This study demonstrates that (1) the geometry and kinematics of BLR are similar in type 1 and type 2 AGNs of the same bulge type (pseudobulges), and (2) the small values of virial factors in Seyfert 2 galaxies suggest that, similar to type 1 AGNs, BLRs tend to be very thick disks in type 2 objects.

Hidden Broad-line Regions in Seyfert 2 Galaxies: From the Spectropolarimetric Perspective

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

Du, Pu; Wang, Jian-Min; Zhang, Zhi-Xiang, E-mail: dupu@ihep.ac.cn

2017-05-01

The hidden broad-line regions (BLRs) in Seyfert 2 galaxies, which display broad emission lines (BELs) in their polarized spectra, are a key piece of evidence in support of the unified model for active galactic nuclei (AGNs). However, the detailed kinematics and geometry of hidden BLRs are still not fully understood. The virial factor obtained from reverberation mapping of type 1 AGNs may be a useful diagnostic of the nature of hidden BLRs in type 2 objects. In order to understand the hidden BLRs, we compile six type 2 objects from the literature with polarized BELs and dynamical measurements of blackmore » hole masses. All of them contain pseudobulges. We estimate their virial factors, and find the average value is 0.60 and the standard deviation is 0.69, which agree well with the value of type 1 AGNs with pseudobulges. This study demonstrates that (1) the geometry and kinematics of BLR are similar in type 1 and type 2 AGNs of the same bulge type (pseudobulges), and (2) the small values of virial factors in Seyfert 2 galaxies suggest that, similar to type 1 AGNs, BLRs tend to be very thick disks in type 2 objects.« less

Young Infants' Reasoning about Hidden Objects: Evidence from Violation-of-Expectation Tasks with Test Trials Only

ERIC Educational Resources Information Center

Wang, Su-hua; Baillargeon, Renee; Brueckner, Laura

2004-01-01

The present research examined alternative accounts of prior violation-of-expectation (VOE) reports that young infants can represent and reason about hidden objects. According to these accounts, young infants' apparent success in these VOE tasks reflects only novelty and familiarity preferences induced by the habituation or familiarization trials…

Hidden School Dropout among Immigrant Students: A Cross-Sectional Study

ERIC Educational Resources Information Center

Makarova, Elena; Herzog, Walter

2013-01-01

Actual school dropout among immigrant youth has been addressed in a number of studies, but research on hidden school dropout among immigrant students is rare. Thus, the objective of this paper is to analyze hidden school dropout among primary school students with an immigrant background. The analyses were performed using survey data of 1186…

Using an auditory sensory substitution device to augment vision: evidence from eye movements.

PubMed

Wright, Thomas D; Margolis, Aaron; Ward, Jamie

2015-03-01

Sensory substitution devices convert information normally associated with one sense into another sense (e.g. converting vision into sound). This is often done to compensate for an impaired sense. The present research uses a multimodal approach in which both natural vision and sound-from-vision ('soundscapes') are simultaneously presented. Although there is a systematic correspondence between what is seen and what is heard, we introduce a local discrepancy between the signals (the presence of a target object that is heard but not seen) that the participant is required to locate. In addition to behavioural responses, the participants' gaze is monitored with eye-tracking. Although the target object is only presented in the auditory channel, behavioural performance is enhanced when visual information relating to the non-target background is presented. In this instance, vision may be used to generate predictions about the soundscape that enhances the ability to detect the hidden auditory object. The eye-tracking data reveal that participants look for longer in the quadrant containing the auditory target even when they subsequently judge it to be located elsewhere. As such, eye movements generated by soundscapes reveal the knowledge of the target location that does not necessarily correspond to the actual judgment made. The results provide a proof of principle that multimodal sensory substitution may be of benefit to visually impaired people with some residual vision and, in normally sighted participants, for guiding search within complex scenes.

KSC-2012-2582

NASA Image and Video Library

2012-04-09

CAPE CANAVERAL, Fla. – Aboard NASA’s Freedom Star boat, from left, Boatswain Allan Gravina at the wheel, Captain Mike Nicholas hidden, Aerospace Technician Darin Schuster and Marine Operations Manager Joe Chaput, all with United Space Alliance, monitor the progress as NASA’s Mobile Aerospace Reconnaissance System, or MARS, secured on the boat, is being prepared for a day of testing in the Atlantic Ocean off the coast of Port Canaveral in Florida. MARS, run by NASA’s Langley Research Center in Hampton, Va., with its spatial, hyperspectral, thermal, and directed energy capabilities will be used for thermal imaging testing for the upcoming SpaceX Falcon 9 and Dragon capsule test flight to the International Space Station. During today’s test, the MARS X-band radar and kineto tracking mount KTM were tested to ensure that they were synchronized to receive a rocket launch feed. The radar was used to identify an object to see if the KTM could lock on to and track it. The MARS team performed maintenance on the system, confirmed communications links, and tested the design of the mounting system and environmental enclosure. Photo credit: NASA/Cory Huston

Foliage penetration by using 4-D point cloud data

NASA Astrophysics Data System (ADS)

Méndez Rodríguez, Javier; Sánchez-Reyes, Pedro J.; Cruz-Rivera, Sol M.

2012-06-01

Real-time awareness and rapid target detection are critical for the success of military missions. New technologies capable of detecting targets concealed in forest areas are needed in order to track and identify possible threats. Currently, LAser Detection And Ranging (LADAR) systems are capable of detecting obscured targets; however, tracking capabilities are severely limited. Now, a new LADAR-derived technology is under development to generate 4-D datasets (3-D video in a point cloud format). As such, there is a new need for algorithms that are able to process data in real time. We propose an algorithm capable of removing vegetation and other objects that may obfuscate concealed targets in a real 3-D environment. The algorithm is based on wavelets and can be used as a pre-processing step in a target recognition algorithm. Applications of the algorithm in a real-time 3-D system could help make pilots aware of high risk hidden targets such as tanks and weapons, among others. We will be using a 4-D simulated point cloud data to demonstrate the capabilities of our algorithm.

Searching for possible hidden chambers in the Pyramid of the Sun

NASA Astrophysics Data System (ADS)

Alfaro, R.; Belmont, E.; Grabski, V.; Manzanilla, L.; Martinez-Davalos, A.; Menchaca-Rocha, A.; Moreno, M.; Sandoval, A.

The Pyramid of the Sun, at Teotihuacan, Mexico, is being searched for possible hidden chambers, using a muon tracking technique inspired in the experiment carried out by Luis Alvarez over 30 years ago at the Chephren Pyramid, in Giza. A fortunate similarity between this monument and the Pyramid of the Sun is a tunnel, running 8 m below the base and ending close to the symmetry axis, which permits the use muon attenuation measurements. A brief account of the project, including planning, detector design, construction and simulations, as well as the current status of the project is presented

Standoff detection of hidden objects using backscattered ultra-intense laser-produced x-rays

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

Kuwabara, H.; Mori, Y.; Kitagawa, Y.

2013-08-28

Ultra-intense laser-produced sub-ps X-ray pulses can detect backscattered signals from objects hidden in aluminium containers. Coincident measurements using primary X-rays enable differentiation among acrylic, copper, and lead blocks inside the container. Backscattering reveals the shapes of the objects, while their material composition can be identified from the modification methods of the energy spectra of backscattered X-ray beams. This achievement is an important step toward more effective homeland security.

Mother-Child Communication about Location: Giving and Following Directions for Finding Hidden Objects

ERIC Educational Resources Information Center

Plumert, Jodie M.; Haggerty, Kathryn A.; Mickunas, Andrew; Herzog, Lauren; Shadrick, Courtney

2012-01-01

We conducted 2 experiments to examine how mothers structure directions to young children for finding hidden objects and how young children use these directions to guide their searches. In Experiment 1, we examined the reference frames mothers use to communicate with their 2.5-, 3-, and 3.5-year-old children about location by asking mothers to…

When Height Carries Weight: Communicating Hidden Object Properties for Joint Action.

PubMed

Schmitz, Laura; Vesper, Cordula; Sebanz, Natalie; Knoblich, Günther

2018-06-24

In the absence of pre-established communicative conventions, people create novel communication systems to successfully coordinate their actions toward a joint goal. In this study, we address two types of such novel communication systems: sensorimotor communication, where the kinematics of instrumental actions are systematically modulated, versus symbolic communication. We ask which of the two systems co-actors preferentially create when aiming to communicate about hidden object properties such as weight. The results of three experiments consistently show that actors who knew the weight of an object transmitted this weight information to their uninformed co-actors by systematically modulating their instrumental actions, grasping objects of particular weights at particular heights. This preference for sensorimotor communication was reduced in a fourth experiment where co-actors could communicate with weight-related symbols. Our findings demonstrate that the use of sensorimotor communication extends beyond the communication of spatial locations to non-spatial, hidden object properties. © 2018 The Authors. Cognitive Science - A Multidisciplinary Journal published by Wiley Periodicals, Inc. on behalf of Cognitive Science Society.

Hand gesture recognition in confined spaces with partial observability and occultation constraints

NASA Astrophysics Data System (ADS)

Shirkhodaie, Amir; Chan, Alex; Hu, Shuowen

2016-05-01

Human activity detection and recognition capabilities have broad applications for military and homeland security. These tasks are very complicated, however, especially when multiple persons are performing concurrent activities in confined spaces that impose significant obstruction, occultation, and observability uncertainty. In this paper, our primary contribution is to present a dedicated taxonomy and kinematic ontology that are developed for in-vehicle group human activities (IVGA). Secondly, we describe a set of hand-observable patterns that represents certain IVGA examples. Thirdly, we propose two classifiers for hand gesture recognition and compare their performance individually and jointly. Finally, we present a variant of Hidden Markov Model for Bayesian tracking, recognition, and annotation of hand motions, which enables spatiotemporal inference to human group activity perception and understanding. To validate our approach, synthetic (graphical data from virtual environment) and real physical environment video imagery are employed to verify the performance of these hand gesture classifiers, while measuring their efficiency and effectiveness based on the proposed Hidden Markov Model for tracking and interpreting dynamic spatiotemporal IVGA scenarios.

Intelligent data analysis to model and understand live cell time-lapse sequences.

PubMed

Paterson, Allan; Ashtari, M; Ribé, D; Stenbeck, G; Tucker, A

2012-01-01

One important aspect of cellular function, which is at the basis of tissue homeostasis, is the delivery of proteins to their correct destinations. Significant advances in live cell microscopy have allowed tracking of these pathways by following the dynamics of fluorescently labelled proteins in living cells. This paper explores intelligent data analysis techniques to model the dynamic behavior of proteins in living cells as well as to classify different experimental conditions. We use a combination of decision tree classification and hidden Markov models. In particular, we introduce a novel approach to "align" hidden Markov models so that hidden states from different models can be cross-compared. Our models capture the dynamics of two experimental conditions accurately with a stable hidden state for control data and multiple (less stable) states for the experimental data recapitulating the behaviour of particle trajectories within live cell time-lapse data. In addition to having successfully developed an automated framework for the classification of protein transport dynamics from live cell time-lapse data our model allows us to understand the dynamics of a complex trafficking pathway in living cells in culture.

Two-dimensional hidden semantic information model for target saliency detection and eyetracking identification

NASA Astrophysics Data System (ADS)

Wan, Weibing; Yuan, Lingfeng; Zhao, Qunfei; Fang, Tao

2018-01-01

Saliency detection has been applied to the target acquisition case. This paper proposes a two-dimensional hidden Markov model (2D-HMM) that exploits the hidden semantic information of an image to detect its salient regions. A spatial pyramid histogram of oriented gradient descriptors is used to extract features. After encoding the image by a learned dictionary, the 2D-Viterbi algorithm is applied to infer the saliency map. This model can predict fixation of the targets and further creates robust and effective depictions of the targets' change in posture and viewpoint. To validate the model with a human visual search mechanism, two eyetrack experiments are employed to train our model directly from eye movement data. The results show that our model achieves better performance than visual attention. Moreover, it indicates the plausibility of utilizing visual track data to identify targets.

Robust Hidden Markov Model based intelligent blood vessel detection of fundus images.

PubMed

Hassan, Mehdi; Amin, Muhammad; Murtza, Iqbal; Khan, Asifullah; Chaudhry, Asmatullah

2017-11-01

In this paper, we consider the challenging problem of detecting retinal vessel networks. Precise detection of retinal vessel networks is vital for accurate eye disease diagnosis. Most of the blood vessel tracking techniques may not properly track vessels in presence of vessels' occlusion. Owing to problem in sensor resolution or acquisition of fundus images, it is possible that some part of vessel may occlude. In this scenario, it becomes a challenging task to accurately trace these vital vessels. For this purpose, we have proposed a new robust and intelligent retinal vessel detection technique on Hidden Markov Model. The proposed model is able to successfully track vessels in the presence of occlusion. The effectiveness of the proposed technique is evaluated on publically available standard DRIVE dataset of the fundus images. The experiments show that the proposed technique not only outperforms the other state of the art methodologies of retinal blood vessels segmentation, but it is also capable of accurate occlusion handling in retinal vessel networks. The proposed technique offers better average classification accuracy, sensitivity, specificity, and area under the curve (AUC) of 95.7%, 81.0%, 97.0%, and 90.0% respectively, which shows the usefulness of the proposed technique. Copyright © 2017 Elsevier B.V. All rights reserved.

Making the Case for Demographic Data in Extension Programming

ERIC Educational Resources Information Center

Curtis, Katherine J.; Verdoff, Daniel; Rizzo, Bill; Beaudoin, James

2012-01-01

Understanding one's community is essential for effective Extension programming across all program areas. The use of current and reliable demographic data is crucial for Extension to develop effective education and programming to track change and to uncover hidden community characteristics. We discuss what demographic data are, present…

Automated Proton Track Identification in MicroBooNE Using Gradient Boosted Decision Trees

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

Woodruff, Katherine

MicroBooNE is a liquid argon time projection chamber (LArTPC) neutrino experiment that is currently running in the Booster Neutrino Beam at Fermilab. LArTPC technology allows for high-resolution, three-dimensional representations of neutrino interactions. A wide variety of software tools for automated reconstruction and selection of particle tracks in LArTPCs are actively being developed. Short, isolated proton tracks, the signal for low- momentum-transfer neutral current (NC) elastic events, are easily hidden in a large cosmic background. Detecting these low-energy tracks will allow us to probe interesting regions of the proton's spin structure. An effective method for selecting NC elastic events is tomore » combine a highly efficient track reconstruction algorithm to find all candidate tracks with highly accurate particle identification using a machine learning algorithm. We present our work on particle track classification using gradient tree boosting software (XGBoost) and the performance on simulated neutrino data.« less

Understanding the Effects of One's Actions upon Hidden Objects and the Development of Search Behaviour in 7-Month-Old Infants

ERIC Educational Resources Information Center

O'Connor, Richard J.; Russell, James

2015-01-01

Infants' understanding of how their actions affect the visibility of hidden objects may be a crucial aspect of the development of search behaviour. To investigate this possibility, 7-month-old infants took part in a two-day training study. At the start of the first session, and at the end of the second, all infants performed a search task with a…

Matrix Determination of Reflectance of Hidden Object via Indirect Photography

DTIC Science & Technology

2012-03-01

the hidden object. This thesis provides an alternative method of processing the camera images by modeling the system as a set of transport and...Distribution Function ( BRDF ). Figure 1. Indirect photography with camera field of view dictated by point of illumination. 3 1.3 Research Focus In an...would need to be modeled using radiometric principles. A large amount of the improvement in this process was due to the use of a blind

Monitour: Tracking global routes of electronic waste.

PubMed

Lee, David; Offenhuber, Dietmar; Duarte, Fábio; Biderman, Assaf; Ratti, Carlo

2018-02-01

Many nations seek to control or prevent the inflow of waste electronic and electrical equipment, but such flows are difficult to track due to undocumented, often illegal global trade in e-waste. We apply wireless GPS location trackers to this problem, detecting potential cases of non-compliant recycling operations in the United States as well as the global trajectories of exported e-waste. By planting hidden trackers inside discarded computer monitors and printers, we tracked dozens of devices being sent overseas to various ports in Asia, flows likely unreported in official trade data. We discuss how location tracking enables new ways to monitor, regulate, and enforce rules on the international movement of hazardous electronic waste materials, and the limitations of such methods. Copyright © 2017 Elsevier Ltd. All rights reserved.

Hierarchically Structured Non-Intrusive Sign Language Recognition. Chapter 2

NASA Technical Reports Server (NTRS)

Zieren, Jorg; Zieren, Jorg; Kraiss, Karl-Friedrich

2007-01-01

This work presents a hierarchically structured approach at the nonintrusive recognition of sign language from a monocular frontal view. Robustness is achieved through sophisticated localization and tracking methods, including a combined EM/CAMSHIFT overlap resolution procedure and the parallel pursuit of multiple hypotheses about hands position and movement. This allows handling of ambiguities and automatically corrects tracking errors. A biomechanical skeleton model and dynamic motion prediction using Kalman filters represents high level knowledge. Classification is performed by Hidden Markov Models. 152 signs from German sign language were recognized with an accuracy of 97.6%.

Post processing of optically recognized text via second order hidden Markov model

NASA Astrophysics Data System (ADS)

Poudel, Srijana

In this thesis, we describe a postprocessing system on Optical Character Recognition(OCR) generated text. Second Order Hidden Markov Model (HMM) approach is used to detect and correct the OCR related errors. The reason for choosing the 2nd order HMM is to keep track of the bigrams so that the model can represent the system more accurately. Based on experiments with training data of 159,733 characters and testing of 5,688 characters, the model was able to correct 43.38 % of the errors with a precision of 75.34 %. However, the precision value indicates that the model introduced some new errors, decreasing the correction percentage to 26.4%.

Object permanence in domestic dogs (Canis lupus familiaris) and gray wolves (Canis lupus).

PubMed

Fiset, Sylvain; Plourde, Vickie

2013-05-01

Recent evidence suggests that phylogenetic constraints exerted on dogs by the process of domestication have altered the ability of dogs to represent the physical world and the displacement of objects. In this study, invisible (Experiment 1) and visible (Experiment 2) displacement problems were administered to determine whether domestic dogs' and gray wolves' cognitive capacities to infer the position of a hidden object differ. The results revealed that adult dogs and wolves performed similarly in searching for disappearing objects: Both species succeeded the visible displacement tasks but failed the invisible displacement problems. We conclude that physical cognition for finding hidden objects in domestic dogs and gray wolves is alike and unrelated to the process of domestication.

Solving the "Hidden Line" Problem

NASA Technical Reports Server (NTRS)

1984-01-01

David Hedgley Jr., a mathematician at Dryden Flight Research Center, has developed an accurate computer program that considers whether a line in a graphic model of a three dimensional object should or should not be visible. The Hidden Line Computer Code, program automatically removes superfluous lines and permits the computer to display an object from specific viewpoints, just as the human eye would see it. Users include Rowland Institute for Science in Cambridge, MA, several departments of Lockheed Georgia Co., and Nebraska Public Power District (NPPD).

Reading from Scratch - A Vision-System for Reading Data on Micro-structured Surfaces

NASA Astrophysics Data System (ADS)

Dragon, Ralf; Becker, Christian; Rosenhahn, Bodo; Ostermann, Jörn

Labeling and marking industrial manufactured objects gets increasingly important nowadays because of novel material properties and plagiarism. As part of the Collaborative Research Center 653 which investigates micro-structured metallic surfaces for inherent mechanical data storage, we research into a stable and reliable optical readout of the written data. Since this comprises a qualitative surface reconstruction, we use directed illumination to make the micro structures visible. Then we apply a spectral analysis to obtain image partitioning and perform signal tracking enhanced by a customized Hidden Markov Model. In this paper, we derive the algorithms used and demonstrate reading data from a surface with 1.6kbit/cm2 from a micro-structured groove which varies by only 3μ m in depth (thus a “scratch”). We demonstrate the system’s robustness with experiments with real and artificially-rendered surfaces.

SILHOUETTE - HIDDEN LINE COMPUTER CODE WITH GENERALIZED SILHOUETTE SOLUTION

NASA Technical Reports Server (NTRS)

Hedgley, D. R.

1994-01-01

Flexibility in choosing how to display computer-generated three-dimensional drawings has become increasingly important in recent years. A major consideration is the enhancement of the realism and aesthetics of the presentation. A polygonal representation of objects, even with hidden lines removed, is not always desirable. A more pleasing pictorial representation often can be achieved by removing some of the remaining visible lines, thus creating silhouettes (or outlines) of selected surfaces of the object. Additionally, it should be noted that this silhouette feature allows warped polygons. This means that any polygon can be decomposed into constituent triangles. Considering these triangles as members of the same family will present a polygon with no interior lines, and thus removes the restriction of flat polygons. SILHOUETTE is a program for calligraphic drawings that can render any subset of polygons as a silhouette with respect to itself. The program is flexible enough to be applicable to every class of object. SILHOUETTE offers all possible combinations of silhouette and nonsilhouette specifications for an arbitrary solid. Thus, it is possible to enhance the clarity of any three-dimensional scene presented in two dimensions. Input to the program can be line segments or polygons. Polygons designated with the same number will be drawn as a silhouette of those polygons. SILHOUETTE is written in FORTRAN 77 and requires a graphics package such as DI-3000. The program has been implemented on a DEC VAX series computer running VMS and used 65K of virtual memory without a graphics package linked in. The source code is intended to be machine independent. This program is available on a 5.25 inch 360K MS-DOS format diskette (standard distribution) and is also available on a 9-track 1600 BPI ASCII CARD IMAGE magnetic tape. SILHOUETTE was developed in 1986 and was last updated in 1992.

Hidden Figures Tour Kennedy Space Center Visitor Complex

NASA Image and Video Library

2016-12-12

Cast and crew members of the upcoming motion picture "Hidden Figures" participate in a question and answer session at the Kennedy Space Center Visitor Complex. From the left are Pharrell Williams, musician and producer of “Hidden Figures," Taraji P. Henson, who portrays Katherine Johnson in the film, Janelle Monáe, who portrays Mary Jackson, and Octavia Spencer, who portrays Dorothy Vaughan. They are seated in front of the original consoles of the Mercury Mission Control room with the world map that was used to follow the path of capsules between tracking stations. The movie is based on the book of the same title, by Margot Lee Shetterly. It chronicles the lives of Katherine Johnson, Dorothy Vaughan and Mary Jackson, three African-American women who worked for NASA as human "computers.” Their mathematical calculations were crucial to the success of Project Mercury missions including John Glenn’s orbital flight aboard Friendship 7 in 1962. The film is due in theaters in January 2017.

A Hidden Markov Model for Analysis of Frontline Veterinary Data for Emerging Zoonotic Disease Surveillance

PubMed Central

Robertson, Colin; Sawford, Kate; Gunawardana, Walimunige S. N.; Nelson, Trisalyn A.; Nathoo, Farouk; Stephen, Craig

2011-01-01

Surveillance systems tracking health patterns in animals have potential for early warning of infectious disease in humans, yet there are many challenges that remain before this can be realized. Specifically, there remains the challenge of detecting early warning signals for diseases that are not known or are not part of routine surveillance for named diseases. This paper reports on the development of a hidden Markov model for analysis of frontline veterinary sentinel surveillance data from Sri Lanka. Field veterinarians collected data on syndromes and diagnoses using mobile phones. A model for submission patterns accounts for both sentinel-related and disease-related variability. Models for commonly reported cattle diagnoses were estimated separately. Region-specific weekly average prevalence was estimated for each diagnoses and partitioned into normal and abnormal periods. Visualization of state probabilities was used to indicate areas and times of unusual disease prevalence. The analysis suggests that hidden Markov modelling is a useful approach for surveillance datasets from novel populations and/or having little historical baselines. PMID:21949763

Holographic quantitative imaging of sample hidden by turbid medium or occluding objects

NASA Astrophysics Data System (ADS)

Bianco, V.; Miccio, L.; Merola, F.; Memmolo, P.; Gennari, O.; Paturzo, Melania; Netti, P. A.; Ferraro, P.

2015-03-01

Digital Holography (DH) numerical procedures have been developed to allow imaging through turbid media. A fluid is considered turbid when dispersed particles provoke strong light scattering, thus destroying the image formation by any standard optical system. Here we show that sharp amplitude imaging and phase-contrast mapping of object hidden behind turbid medium and/or occluding objects are possible in harsh noise conditions and with a large field-of view by Multi-Look DH microscopy. In particular, it will be shown that both amplitude imaging and phase-contrast mapping of cells hidden behind a flow of Red Blood Cells can be obtained. This allows, in a noninvasive way, the quantitative evaluation of living processes in Lab on Chip platforms where conventional microscopy techniques fail. The combination of this technique with endoscopic imaging can pave the way for the holographic blood vessel inspection, e.g. to look for settled cholesterol plaques as well as blood clots for a rapid diagnostics of blood diseases.

Optimization of Artificial Neural Network using Evolutionary Programming for Prediction of Cascading Collapse Occurrence due to the Hidden Failure Effect

NASA Astrophysics Data System (ADS)

Idris, N. H.; Salim, N. A.; Othman, M. M.; Yasin, Z. M.

2018-03-01

This paper presents the Evolutionary Programming (EP) which proposed to optimize the training parameters for Artificial Neural Network (ANN) in predicting cascading collapse occurrence due to the effect of protection system hidden failure. The data has been collected from the probability of hidden failure model simulation from the historical data. The training parameters of multilayer-feedforward with backpropagation has been optimized with objective function to minimize the Mean Square Error (MSE). The optimal training parameters consists of the momentum rate, learning rate and number of neurons in first hidden layer and second hidden layer is selected in EP-ANN. The IEEE 14 bus system has been tested as a case study to validate the propose technique. The results show the reliable prediction of performance validated through MSE and Correlation Coefficient (R).

Object permanence in cats (Felis catus): an ecological approach to the study of invisible displacements.

PubMed

Dumas, C

1992-12-01

A single invisible displacement object permanence task was administered to 19 cats (Felis catus). In this task, cats watched a target object from behind a transparent panel. However, cats had to walk around an opaque panel to reach the object. While cats were behind the opaque panel, the object was hidden behind one of two screens. As cats did not perceive the disappearance of the object behind the target screen, the object was invisibly hidden. Results showed that cats solved this task with great flexibility, which markedly contrasts with what has been observed in previous research. The discussion emphasizes the difference between the typical Piagetian task in which the information necessary to succeed must be dealt with in retrospective way, whereas in our task cats had to anticipate a new position of the object. The ecological relevance of this new task is also discussed.

Image segmentation using hidden Markov Gauss mixture models.

PubMed

Pyun, Kyungsuk; Lim, Johan; Won, Chee Sun; Gray, Robert M

2007-07-01

Image segmentation is an important tool in image processing and can serve as an efficient front end to sophisticated algorithms and thereby simplify subsequent processing. We develop a multiclass image segmentation method using hidden Markov Gauss mixture models (HMGMMs) and provide examples of segmentation of aerial images and textures. HMGMMs incorporate supervised learning, fitting the observation probability distribution given each class by a Gauss mixture estimated using vector quantization with a minimum discrimination information (MDI) distortion. We formulate the image segmentation problem using a maximum a posteriori criteria and find the hidden states that maximize the posterior density given the observation. We estimate both the hidden Markov parameter and hidden states using a stochastic expectation-maximization algorithm. Our results demonstrate that HMGMM provides better classification in terms of Bayes risk and spatial homogeneity of the classified objects than do several popular methods, including classification and regression trees, learning vector quantization, causal hidden Markov models (HMMs), and multiresolution HMMs. The computational load of HMGMM is similar to that of the causal HMM.

Topography of hidden objects using THz digital holography with multi-beam interferences.

PubMed

Valzania, Lorenzo; Zolliker, Peter; Hack, Erwin

2017-05-15

We present a method for the separation of the signal scattered from an object hidden behind a THz-transparent sample in the framework of THz digital holography in reflection. It combines three images of different interference patterns to retrieve the amplitude and phase distribution of the object beam. Comparison of simulated with experimental images obtained from a metallic resolution target behind a Teflon plate demonstrates that the interference patterns can be described in the simple form of three-beam interference. Holographic reconstructions after the application of the method show a considerable improvement compared to standard reconstructions exclusively based on Fourier transform phase retrieval.

The Professional Values of Program Directors and Head Athletic Trainers: The Impact of the Hidden Curriculum

ERIC Educational Resources Information Center

Peer, Kimberly S.; Schlabach, Gretchen A.

2011-01-01

Context: Athletic training education programs (ATEPs) promote the development of foundational behaviors of professional practice. Situated in the context of professional values, ATEPs are challenged to identify outcome measures for these behaviors. These values are tacitly reflected as part of the hidden curriculum. Objective: To ascertain the…

Functional Evaluation of Hidden Figures Object Analysis in Children with Autistic Disorder

ERIC Educational Resources Information Center

Malisza, Krisztina L.; Clancy, Christine; Shiloff, Deborah; Foreman, Derek; Holden, Jeanette; Jones, Cheryl; Paulson, K.; Summers, Randy; Yu, C. T.; Chudley, Albert E.

2011-01-01

Functional magnetic resonance imaging (fMRI) during performance of a hidden figures task (HFT) was used to compare differences in brain function in children diagnosed with autism disorder (AD) compared to children with attention-deficit/hyperactivity disorder (ADHD) and typical controls (TC). Overall greater functional MRI activity was observed in…

Multispectral THz-VIS passive imaging system for hidden threats visualization

NASA Astrophysics Data System (ADS)

Kowalski, Marcin; Palka, Norbert; Szustakowski, Mieczyslaw

2013-10-01

Terahertz imaging, is the latest entry into the crowded field of imaging technologies. Many applications are emerging for the relatively new technology. THz radiation penetrates deep into nonpolar and nonmetallic materials such as paper, plastic, clothes, wood, and ceramics that are usually opaque at optical wavelengths. The T-rays have large potential in the field of hidden objects detection because it is not harmful to humans. The main difficulty in the THz imaging systems is low image quality thus it is justified to combine THz images with the high-resolution images from a visible camera. An imaging system is usually composed of various subsystems. Many of the imaging systems use imaging devices working in various spectral ranges. Our goal is to build a system harmless to humans for screening and detection of hidden objects using a THz and VIS cameras.

Array heterogeneity prevents catastrophic forgetting in infants

PubMed Central

Zosh, Jennifer M.; Feigenson, Lisa

2015-01-01

Working memory is limited in adults and infants. But unlike adults, infants whose working memory capacity is exceeded often fail in a particularly striking way: they do not represent any of the presented objects, rather than simply remembering as many objects as they can and ignoring anything further (Feigenson & Carey 2003, 2005). Here we explored the nature of this “catastrophic forgetting,” asking whether stimuli themselves modulate the way in which infants’ memory fails. We showed 13-month old infants object arrays that either were within or that exceeded working memory capacity—but, unlike previous experiments, presented objects with contrasting features. Although previous studies have repeatedly documented infants’ failure to represent four identical hidden objects, in Experiments 1 and 2 we found that infants who saw four contrasting objects hidden, and then retrieved just two of the four, successfully continued searching for the missing objects. Perceptual contrast between objects sufficed to drive this success; infants succeeded regardless of whether the different objects were contrastively labeled, and regardless of whether the objects were semantically familiar or completely novel. In Experiment 3 we explored the nature of this surprising success, asking whether array heterogeneity actually expanded infants’ working memory capacity or rather prevented catastrophic forgetting. We found that infants successfully continued searching after seeing four contrasting objects hidden and retrieving two of them, but not after retrieving three of them. This suggests that, like adults, infants were able to remember up to, but not beyond, the limits of their working memory capacity when representing heterogeneous arrays. PMID:25543889

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.

Gaze as a biometric

NASA Astrophysics Data System (ADS)

Yoon, Hong-Jun; Carmichael, Tandy R.; Tourassi, Georgia

2014-03-01

Two people may analyze a visual scene in two completely different ways. Our study sought to determine whether human gaze may be used to establish the identity of an individual. To accomplish this objective we investigated the gaze pattern of twelve individuals viewing still images with different spatial relationships. Specifically, we created 5 visual "dotpattern" tests to be shown on a standard computer monitor. These tests challenged the viewer's capacity to distinguish proximity, alignment, and perceptual organization. Each test included 50 images of varying difficulty (total of 250 images). Eye-tracking data were collected from each individual while taking the tests. The eye-tracking data were converted into gaze velocities and analyzed with Hidden Markov Models to develop personalized gaze profiles. Using leave-one-out cross-validation, we observed that these personalized profiles could differentiate among the 12 users with classification accuracy ranging between 53% and 76%, depending on the test. This was statistically significantly better than random guessing (i.e., 8.3% or 1 out of 12). Classification accuracy was higher for the tests where the users' average gaze velocity per case was lower. The study findings support the feasibility of using gaze as a biometric or personalized biomarker. These findings could have implications in Radiology training and the development of personalized e-learning environments.

A drift chamber tracking system for muon scattering tomography applications

NASA Astrophysics Data System (ADS)

Burns, J.; Quillin, S.; Stapleton, M.; Steer, C.; Snow, S.

2015-10-01

Muon scattering tomography (MST) allows the identification of shielded high atomic number (high-Z) materials by measuring the scattering angle of cosmic ray muons passing through an inspection region. Cosmic ray muons scatter to a greater degree due to multiple Coulomb scattering in high-Z materials than low-Z materials, which can be measured as the angular difference between the incoming and outgoing trajectories of each muon. Measurements of trajectory are achieved by placing position sensitive particle tracking detectors above and below the inspection volume. By localising scattering information, the point at which a series of muons scatter can be used to reconstruct an image, differentiating high, medium and low density objects. MST is particularly useful for differentiating between materials of varying density in volumes that are difficult to inspect visually or by other means. This paper will outline the experimental work undertaken to develop a prototype MST system based on drift chamber technology. The planar drift chambers used in this prototype measure the longitudinal interaction position of an ionising particle from the time taken for elections, liberated in the argon (92.5%), carbon dioxide (5%), methane (2.5%) gas mixture, to reach a central anode wire. Such a system could be used to enhance the detection of shielded radiological material hidden within regular shipping cargo.

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

Yoon, Hong-Jun; Carmichael, Tandy; Tourassi, Georgia

Two people may analyze a visual scene in two completely different ways. Our study sought to determine whether human gaze may be used to establish the identity of an individual. To accomplish this objective we investigated the gaze pattern of twelve individuals viewing different still images with different spatial relationships. Specifically, we created 5 visual dot-pattern tests to be shown on a standard computer monitor. These tests challenged the viewer s capacity to distinguish proximity, alignment, and perceptual organization. Each test included 50 images of varying difficulty (total of 250 images). Eye-tracking data were collected from each individual while takingmore » the tests. The eye-tracking data were converted into gaze velocities and analyzed with Hidden Markov Models to develop personalized gaze profiles. Using leave-one-out cross-validation, we observed that these personalized profiles could differentiate among the 12 users with classification accuracy ranging between 53% and 76%, depending on the test. This was statistically significantly better than random guessing (i.e., 8.3% or 1 out of 12). Classification accuracy was higher for the tests where the users average gaze velocity per case was lower. The study findings support the feasibility of using gaze as a biometric or personalized biomarker. These findings could have implications in Radiology training and the development of personalized e-learning environments.« less

Factors affecting infants' manual search for occluded objects and the genesis of object permanence.

PubMed

Moore, M Keith; Meltzoff, Andrew N

2008-04-01

Two experiments systematically examined factors that influence infants' manual search for hidden objects (N=96). Experiment 1 used a new procedure to assess infants' search for partially versus totally occluded objects. Results showed that 8.75-month-old infants solved partial occlusions by removing the occluder and uncovering the object, but these same infants failed to use this skill on total occlusions. Experiment 2 used sound-producing objects to provide a perceptual clue to the objects' hidden location. Sound clues significantly increased the success rate on total occlusions for 10-month-olds, but not for 8.75-month-olds. An identity development account is offered for why infants succeed on partial occlusions earlier than total occlusions and why sound helps only the older infants. We propose a mechanism for how infants use object identity as a basis for developing a notion of permanence. Implications are drawn for understanding the dissociation between looking time and search assessments of object permanence.

Hidden Markov model tracking of continuous gravitational waves from a binary neutron star with wandering spin. II. Binary orbital phase tracking

NASA Astrophysics Data System (ADS)

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

2017-11-01

A hidden Markov model (HMM) scheme for tracking continuous-wave gravitational radiation from neutron stars in low-mass x-ray binaries (LMXBs) with wandering spin is extended by introducing a frequency-domain matched filter, called the J -statistic, which sums the signal power in orbital sidebands coherently. The J -statistic is similar but not identical to the binary-modulated F -statistic computed by demodulation or resampling. By injecting synthetic LMXB signals into Gaussian noise characteristic of the Advanced Laser Interferometer Gravitational-wave Observatory (Advanced LIGO), it is shown that the J -statistic HMM tracker detects signals with characteristic wave strain h0≥2 ×10-26 in 370 d of data from two interferometers, divided into 37 coherent blocks of equal length. When applied to data from Stage I of the Scorpius X-1 Mock Data Challenge organized by the LIGO Scientific Collaboration, the tracker detects all 50 closed injections (h0≥6.84 ×10-26), recovering the frequency with a root-mean-square accuracy of ≤1.95 ×10-5 Hz . Of the 50 injections, 43 (with h0≥1.09 ×10-25) are detected in a single, coherent 10 d block of data. The tracker employs an efficient, recursive HMM solver based on the Viterbi algorithm, which requires ˜105 CPU-hours for a typical broadband (0.5 kHz) LMXB search.

Black holes, hidden symmetries, and complete integrability

NASA Astrophysics Data System (ADS)

Frolov, Valeri P.; Krtouš, Pavel; Kubizňák, David

2017-11-01

The study of higher-dimensional black holes is a subject which has recently attracted vast interest. Perhaps one of the most surprising discoveries is a realization that the properties of higher-dimensional black holes with the spherical horizon topology and described by the Kerr-NUT-(A)dS metrics are very similar to the properties of the well known four-dimensional Kerr metric. This remarkable result stems from the existence of a single object called the principal tensor. In our review we discuss explicit and hidden symmetries of higher-dimensional Kerr-NUT-(A)dS black hole spacetimes. We start with discussion of the Killing and Killing-Yano objects representing explicit and hidden symmetries. We demonstrate that the principal tensor can be used as a "seed object" which generates all these symmetries. It determines the form of the geometry, as well as guarantees its remarkable properties, such as special algebraic type of the spacetime, complete integrability of geodesic motion, and separability of the Hamilton-Jacobi, Klein-Gordon, and Dirac equations. The review also contains a discussion of different applications of the developed formalism and its possible generalizations.

Black holes, hidden symmetries, and complete integrability.

PubMed

Frolov, Valeri P; Krtouš, Pavel; Kubizňák, David

2017-01-01

The study of higher-dimensional black holes is a subject which has recently attracted vast interest. Perhaps one of the most surprising discoveries is a realization that the properties of higher-dimensional black holes with the spherical horizon topology and described by the Kerr-NUT-(A)dS metrics are very similar to the properties of the well known four-dimensional Kerr metric. This remarkable result stems from the existence of a single object called the principal tensor. In our review we discuss explicit and hidden symmetries of higher-dimensional Kerr-NUT-(A)dS black hole spacetimes. We start with discussion of the Killing and Killing-Yano objects representing explicit and hidden symmetries. We demonstrate that the principal tensor can be used as a "seed object" which generates all these symmetries. It determines the form of the geometry, as well as guarantees its remarkable properties, such as special algebraic type of the spacetime, complete integrability of geodesic motion, and separability of the Hamilton-Jacobi, Klein-Gordon, and Dirac equations. The review also contains a discussion of different applications of the developed formalism and its possible generalizations.

Behavioural mapping of a pelagic seabird: combining multiple sensors and a hidden Markov model reveals the distribution of at-sea behaviour

PubMed Central

Dean, Ben; Freeman, Robin; Kirk, Holly; Leonard, Kerry; Phillips, Richard A.; Perrins, Chris M.; Guilford, Tim

2013-01-01

The use of miniature data loggers is rapidly increasing our understanding of the movements and habitat preferences of pelagic seabirds. However, objectively interpreting behavioural information from the large volumes of highly detailed data collected by such devices can be challenging. We combined three biologging technologies—global positioning system (GPS), saltwater immersion and time–depth recorders—to build a detailed picture of the at-sea behaviour of the Manx shearwater (Puffinus puffinus) during the breeding season. We used a hidden Markov model to explore discrete states within the combined GPS and immersion data, and found that behaviour could be organized into three principal activities representing (i) sustained direct flight, (ii) sitting on the sea surface, and (iii) foraging, comprising tortuous flight interspersed with periods of immersion. The additional logger data verified that the foraging activity corresponded well to the occurrence of diving. Applying this approach to a large tracking dataset revealed that birds from two different colonies foraged in local waters that were exclusive, but overlapped in one key area: the Irish Sea Front (ISF). We show that the allocation of time to each activity differed between colonies, with birds breeding furthest from the ISF spending the greatest proportion of time engaged in direct flight and the smallest proportion of time engaged in foraging activity. This type of analysis has considerable potential for application in future biologging studies and in other taxa. PMID:23034356

Factors Affecting Infants’ Manual Search for Occluded Objects and the Genesis of Object Permanence

PubMed Central

Moore, M. Keith; Meltzoff, Andrew N.

2009-01-01

Two experiments systematically examined factors that influence infants’ manual search for hidden objects (N = 96). Experiment 1 used a new procedure to assess infants’ search for partially versus totally occluded objects. Results showed that 8.75-month-old infants solved partial occlusions by removing the occluder and uncovering the object, but these same infants failed to use this skill on total occlusions. Experiment 2 used sound-producing objects to provide a perceptual clue to the objects’ hidden location. Sound clues significantly increased the success rate on total occlusions for 10-month-olds, but not for 8.75-month-olds. An identity development account is offered for why infants succeed on partial occlusions earlier than total occlusions and why sound helps only the older infants. We propose a mechanism for how infants use object identity as a basis for developing a notion of permanence. Implications are drawn for understanding the dissociation between looking-time and search assessments of object permanence. PMID:18036668

Hidden Milky Way star clusters hosting Wolf-Rayet stars

NASA Astrophysics Data System (ADS)

Kurtev, R.; Borissova, J.; Ivanov, V. D.; Georgiev, L.

2009-05-01

A noticeable fraction of the hidden young star clusters contain WR and O stars providing us with unique laboratories to study the evolution of these rare objects and their maternity places. We are reporting the reddening, the distance and age of two new members of the family of massive young Galactic clusters, hosting WR stars - Glimpse 23 and Glimpse 30.

Determinism, independence, and objectivity are incompatible.

PubMed

Ionicioiu, Radu; Mann, Robert B; Terno, Daniel R

2015-02-13

Hidden-variable models aim to reproduce the results of quantum theory and to satisfy our classical intuition. Their refutation is usually based on deriving predictions that are different from those of quantum mechanics. Here instead we study the mutual compatibility of apparently reasonable classical assumptions. We analyze a version of the delayed-choice experiment which ostensibly combines determinism, independence of hidden variables on the conducted experiments, and wave-particle objectivity (the assertion that quantum systems are, at any moment, either particles or waves, but not both). These three ideas are incompatible with any theory, not only with quantum mechanics.

Top-down contextual knowledge guides visual attention in infancy.

PubMed

Tummeltshammer, Kristen; Amso, Dima

2017-10-26

The visual context in which an object or face resides can provide useful top-down information for guiding attention orienting, object recognition, and visual search. Although infants have demonstrated sensitivity to covariation in spatial arrays, it is presently unclear whether they can use rapidly acquired contextual knowledge to guide attention during visual search. In this eye-tracking experiment, 6- and 10-month-old infants searched for a target face hidden among colorful distracter shapes. Targets appeared in Old or New visual contexts, depending on whether the visual search arrays (defined by the spatial configuration, shape and color of component items in the search display) were repeated or newly generated throughout the experiment. Targets in Old contexts appeared in the same location within the same configuration, such that context covaried with target location. Both 6- and 10-month-olds successfully distinguished between Old and New contexts, exhibiting faster search times, fewer looks at distracters, and more anticipation of targets when contexts repeated. This initial demonstration of contextual cueing effects in infants indicates that they can use top-down information to facilitate orienting during memory-guided visual search. © 2017 John Wiley & Sons Ltd.

The Hidden Costs of California's Harsh School Discipline: And the Localized Economic Benefits from Suspending Fewer High School Students

ERIC Educational Resources Information Center

Rumberger, Russell W.; Losen, Daniel J.

2017-01-01

This California study focuses on the economic impact of school suspensions at the district level. Every 10th grade student in California was tracked for three years to determine the degree to which suspensions predicted lower graduation rates at the state and district level. This estimated impact on graduation was then used to calculate the…

State Actor Threats in 2025

DTIC Science & Technology

2007-04-01

not target tracking (Richardson, Stealth Warplanes, 175.). 51 David A. Fulghum, "New Radars Peel Veil from Hidden Targets," Aviation Week & Space...without meeting any resistance. The world banana population is currently facing such a crisis; bananas are essentially genetic copies of one another...and currently a virus is spreading worldwide, threatening to make the banana , as we know it, extinct.10 In a similar manner, forcing all the

Chronic Elementary Absenteeism: A Problem Hidden in Plain Sight. A Research Brief from Attendance Works and Child & Family Policy Center

ERIC Educational Resources Information Center

Bruner, Charles; Discher, Anne; Chang, Hedy

2011-01-01

Chronic absenteeism--or missing 10 percent or more of school days for any reason--is a proven early warning sign of academic risk and school dropout. Too often, though, this problem is overlooked, especially among elementary students, because of the way attendance data are tracked. This study confirms the premise that districts and schools may…

Object Boundaries Influence Toddlers' Performance in a Search Task

ERIC Educational Resources Information Center

Shutts, Kristin; Keen, Rachel; Spelke, Elizabeth S.

2006-01-01

Previous research has shown that young children have difficulty searching for a hidden object whose location depends on the position of a partly visible physical barrier. Across four experiments, we tested whether children's search errors are affected by two variables that influence adults' object-directed attention: object boundaries and…

Depth-resolved ballistic imaging in a low-depth-of-field optical Kerr gated imaging system

NASA Astrophysics Data System (ADS)

Zheng, Yipeng; Tan, Wenjiang; Si, Jinhai; Ren, YuHu; Xu, Shichao; Tong, Junyi; Hou, Xun

2016-09-01

We demonstrate depth-resolved imaging in a ballistic imaging system, in which a heterodyned femtosecond optical Kerr gate is introduced to extract useful imaging photons for detecting an object hidden in turbid media and a compound lens is proposed to ensure both the depth-resolved imaging capability and the long working distance. Two objects of about 15-μm widths hidden in a polystyrene-sphere suspension have been successfully imaged with approximately 600-μm depth resolution. Modulation-transfer-function curves with the object in and away from the object plane have also been measured to confirm the depth-resolved imaging capability of the low-depth-of-field (low-DOF) ballistic imaging system. This imaging approach shows potential for application in research of the internal structure of highly scattering fuel spray.

Depth-resolved ballistic imaging in a low-depth-of-field optical Kerr gated imaging system

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

Zheng, Yipeng; Tan, Wenjiang, E-mail: tanwenjiang@mail.xjtu.edu.cn; Si, Jinhai

2016-09-07

We demonstrate depth-resolved imaging in a ballistic imaging system, in which a heterodyned femtosecond optical Kerr gate is introduced to extract useful imaging photons for detecting an object hidden in turbid media and a compound lens is proposed to ensure both the depth-resolved imaging capability and the long working distance. Two objects of about 15-μm widths hidden in a polystyrene-sphere suspension have been successfully imaged with approximately 600-μm depth resolution. Modulation-transfer-function curves with the object in and away from the object plane have also been measured to confirm the depth-resolved imaging capability of the low-depth-of-field (low-DOF) ballistic imaging system. Thismore » imaging approach shows potential for application in research of the internal structure of highly scattering fuel spray.« less

Not All Locations Are Created Equal: Exploring How Adults Hide and Search for Objects

PubMed Central

Legge, Eric L. G.; Spetch, Marcia L.; Cenkner, Andrew; Bulitko, Vadim; Anderson, Craig; Brown, Matthew; Heth, Donald

2012-01-01

Little is known about the strategies people use to effectively hide objects from others, or to search for objects others have hidden. The present research extends a recent investigation of people’s hiding and searching strategies in a simple room with 9 cache location. In the present studies, people hid and searched for three objects under more than 70 floor tiles in complex real and virtual rooms. Experiment 1 replicated several finding of Talbot et al within the more complex real and virtual environments. Specifically, people traveled further from origin and selected more dispersed locations when hiding than when searching. Experiments 2 and 3 showed that: 1) people were attracted to an area of darkness when searching and avoided locations close to a window when hiding, 2) when search attempts were limited to three choices, people searched farther from origin and dispersed their locations more when hiding than when searching, and 3) informing people that they would need to recover their hidden objects altered their hiding behavior and increased recovery accuracy. Across all experiments, consistencies in location preferences emerged, with more preference for the middle of the room during hiding and more preference for corners of the room during searching. Even though the same people participated in both the hiding and searching tasks, it appears that people use different strategies to select hiding places than to search for objects hidden by others. PMID:22606324

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.

Detection of Objects Hidden in Highly Scattering Media Using Time-Gated Imaging Methods

NASA Technical Reports Server (NTRS)

Galland, Pierre A.; Wang, L.; Liang, X.; Ho, P. P.; Alfano, R. R.

2000-01-01

Non-intrusive and non-invasive optical imaging techniques has generated great interest among researchers for their potential applications to biological study, device characterization, surface defect detection, and jet fuel dynamics. Non-linear optical parametric amplification gate (NLOPG) has been used to detect back-scattered images of objects hidden in diluted Intralipid solutions. To directly detect objects hidden in highly scattering media, the diffusive component of light needs to be sorted out from early arrived ballistic and snake photons. In an optical imaging system, images are collected in transmission or back-scattered geometry. The early arrival photons in the transmission approach, always carry the direct information of the hidden object embedded in the turbid medium. In the back-scattered approach, the result is not so forth coming. In the presence of a scattering host, the first arrival photons in back-scattered approach will be directly photons from the host material. In the presentation, NLOPG was applied to acquire time resolved back-scattered images under the phase matching condition. A time-gated amplified signal was obtained through this NLOPG process. The system's gain was approximately 100 times. The time-gate was achieved through phase matching condition where only coherent photons retain their phase. As a result, the diffusive photons, which were the primary contributor to the background, were removed. With a large dynamic range and high resolution, time-gated early light imaging has the potential for improving rocket/aircraft design by determining jets shape and particle sizes. Refinements to these techniques may enable drop size measurements in the highly scattering, optically dense region of multi-element rocket injectors. These types of measurements should greatly enhance the design of stable, and higher performing rocket engines.

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).

Rethinking infant knowledge: toward an adaptive process account of successes and failures in object permanence tasks.

PubMed

Munakata, Y; McClelland, J L; Johnson, M H; Siegler, R S

1997-10-01

Infants seem sensitive to hidden objects in habituation tasks at 3.5 months but fail to retrieve hidden objects until 8 months. The authors first consider principle-based accounts of these successes and failures, in which early successes imply knowledge of principles and failures are attributed to ancillary deficits. One account is that infants younger than 8 months have the object permanence principle but lack means-ends abilities. To test this, 7-month-olds were trained on means-ends behaviors and were tested on retrieval of visible and occluded toys. Means-ends demands were the same, yet infants made more toy-guided retrievals in the visible case. The authors offer an adaptive process account in which knowledge is graded and embedded in specific behavioral processes. Simulation models that learn gradually to represent occluded objects show how this approach can account for success and failure in object permanence tasks without assuming principles and ancillary deficits.

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.

Magneto-Radar Hidden Metal Detector

DOEpatents

McEwan, Thomas E.

2005-07-05

A varying magnetic field excites slight vibrations in an object and a radar sensor detects the vibrations at a harmonic of the excitation frequency. The synergy of the magnetic excitation and radar detection provides increased detection range compared to conventional magnetic metal detectors. The radar rejects background clutter by responding only to reflecting objects that are vibrating at a harmonic excitation field, thereby significantly improving detection reliability. As an exemplary arrangement, an ultra-wideband micropower impulse radar (MIR) is capable of being employed to provide superior materials penetration while providing range information. The magneto-radar may be applied to pre-screening magnetic resonance imaging (MRI) patients, landmine detection and finding hidden treasures.

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.

Search for gravitational waves from Scorpius X-1 in the first Advanced LIGO observing run with a hidden Markov model

NASA Astrophysics Data System (ADS)

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A.; Giardina, K. D.; Giazotto, A.; Gill, K.; Glover, L.; Goetz, E.; Goetz, R.; Gomes, S.; González, G.; Gonzalez Castro, J. M.; Gopakumar, A.; Gorodetsky, M. L.; Gossan, S. E.; Gosselin, M.; Gouaty, R.; Grado, A.; Graef, C.; Granata, M.; Grant, A.; Gras, S.; Gray, C.; Greco, G.; Green, A. C.; Groot, P.; Grote, H.; Grunewald, S.; Gruning, P.; Guidi, G. M.; Guo, X.; Gupta, A.; Gupta, M. K.; Gushwa, K. E.; Gustafson, E. K.; Gustafson, R.; Hall, B. R.; Hall, E. D.; Hammond, G.; Haney, M.; Hanke, M. M.; Hanks, J.; Hanna, C.; Hannuksela, O. A.; Hanson, J.; Hardwick, T.; Harms, J.; Harry, G. M.; Harry, I. W.; Hart, M. J.; Haster, C.-J.; Haughian, K.; Healy, J.; Heidmann, A.; Heintze, M. C.; Heitmann, H.; Hello, P.; Hemming, G.; Hendry, M.; Heng, I. S.; Hennig, J.; Henry, J.; Heptonstall, A. W.; Heurs, M.; Hild, S.; Hoak, D.; Hofman, D.; Holt, K.; Holz, D. E.; Hopkins, P.; Horst, C.; Hough, J.; Houston, E. A.; Howell, E. J.; Hu, Y. M.; Huerta, E. A.; Huet, D.; Hughey, B.; Husa, S.; Huttner, S. H.; Huynh-Dinh, T.; Indik, N.; Ingram, D. R.; Inta, R.; Intini, G.; Isa, H. N.; Isac, J.-M.; Isi, M.; Iyer, B. R.; Izumi, K.; Jacqmin, T.; Jani, K.; Jaranowski, P.; Jawahar, S.; Jiménez-Forteza, F.; Johnson, W. W.; Jones, D. I.; Jones, R.; Jonker, R. J. G.; Ju, L.; Junker, J.; Kalaghatgi, C. V.; Kalogera, V.; Kandhasamy, S.; Kang, G.; Kanner, J. B.; Karki, S.; Karvinen, K. S.; Kasprzack, M.; Katolik, M.; Katsavounidis, E.; Katzman, W.; Kaufer, S.; Kawabe, K.; Kéfélian, F.; Keitel, D.; Kemball, A. J.; Kennedy, R.; Kent, C.; Key, J. S.; Khalili, F. Y.; Khan, I.; Khan, S.; Khan, Z.; Khazanov, E. A.; Kijbunchoo, N.; Kim, Chunglee; Kim, J. C.; Kim, W.; Kim, W. S.; Kim, Y.-M.; Kimbrell, S. J.; King, E. J.; King, P. J.; Kirchhoff, R.; Kissel, J. S.; Kleybolte, L.; Klimenko, S.; Koch, P.; Koehlenbeck, S. M.; Koley, S.; Kondrashov, V.; Kontos, A.; Korobko, M.; Korth, W. Z.; Kowalska, I.; Kozak, D. B.; Krämer, C.; Kringel, V.; Krishnan, B.; Królak, A.; Kuehn, G.; Kumar, P.; Kumar, R.; Kumar, S.; Kuo, L.; Kutynia, A.; Kwang, S.; Lackey, B. D.; Lai, K. H.; Landry, M.; Lang, R. N.; Lange, J.; Lantz, B.; Lanza, R. K.; Lartaux-Vollard, A.; Lasky, P. D.; Laxen, M.; Lazzarini, A.; Lazzaro, C.; Leaci, P.; Leavey, S.; Lee, C. H.; Lee, H. K.; Lee, H. M.; Lee, H. W.; Lee, K.; Lehmann, J.; Lenon, A.; Leonardi, M.; Leroy, N.; Letendre, N.; Levin, Y.; Li, T. G. F.; Libson, A.; Littenberg, T. B.; Liu, J.; Lockerbie, N. A.; London, L. T.; Lord, J. E.; Lorenzini, M.; Loriette, V.; Lormand, M.; Losurdo, G.; Lough, J. D.; Lovelace, G.; Lück, H.; Lumaca, D.; Lundgren, A. P.; Lynch, R.; Ma, Y.; Macfoy, S.; Machenschalk, B.; MacInnis, M.; Macleod, D. M.; Magaña Hernandez, I.; Magaña-Sandoval, F.; Magaña Zertuche, L.; Magee, R. M.; Majorana, E.; Maksimovic, I.; Man, N.; Mandic, V.; Mangano, V.; Mansell, G. L.; Manske, M.; Mantovani, M.; Marchesoni, F.; Marion, F.; Márka, S.; Márka, Z.; Markakis, C.; Markosyan, A. S.; Maros, E.; Martelli, F.; Martellini, L.; Martin, I. W.; Martynov, D. V.; Marx, J. N.; Mason, K.; Masserot, A.; Massinger, T. J.; Masso-Reid, M.; Mastrogiovanni, S.; Matas, A.; Matichard, F.; Matone, L.; Mavalvala, N.; Mayani, R.; Mazumder, N.; McCarthy, R.; McClelland, D. E.; McCormick, S.; McCuller, L.; McGuire, S. C.; McIntyre, G.; McIver, J.; McManus, D. J.; McRae, T.; McWilliams, S. T.; Meacher, D.; Meadors, G. D.; Meidam, J.; Mejuto-Villa, E.; Melatos, A.; Mendell, G.; Mercer, R. A.; Merilh, E. L.; Merzougui, M.; Meshkov, S.; Messenger, C.; Messick, C.; Metzdorff, R.; Meyers, P. M.; Mezzani, F.; Miao, H.; Michel, C.; Middleton, H.; Mikhailov, E. E.; Milano, L.; Miller, A. L.; Miller, A.; Miller, B. B.; Miller, J.; Millhouse, M.; Minazzoli, O.; Minenkov, Y.; Ming, J.; Mishra, C.; Mitra, S.; Mitrofanov, V. P.; Mitselmakher, G.; Mittleman, R.; Moggi, A.; Mohan, M.; Mohapatra, S. R. P.; Montani, M.; Moore, B. C.; Moore, C. J.; Moraru, D.; Moreno, G.; Morriss, S. R.; Mours, B.; Mow-Lowry, C. M.; Mueller, G.; Muir, A. W.; Mukherjee, Arunava; Mukherjee, D.; Mukherjee, S.; Mukund, N.; Mullavey, A.; Munch, J.; Muniz, E. A. M.; Murray, P. G.; Napier, K.; Nardecchia, I.; Naticchioni, L.; Nayak, R. K.; Nelemans, G.; Nelson, T. J. N.; Neri, M.; Nery, M.; Neunzert, A.; Newport, J. M.; Newton, G.; Ng, K. K. Y.; Nguyen, T. T.; Nichols, D.; Nielsen, A. B.; Nissanke, S.; Nitz, A.; Noack, A.; Nocera, F.; Nolting, D.; Normandin, M. E. N.; Nuttall, L. K.; Oberling, J.; Ochsner, E.; Oelker, E.; Ogin, G. H.; Oh, J. J.; Oh, S. H.; Ohme, F.; Oliver, M.; Oppermann, P.; Oram, Richard J.; O'Reilly, B.; Ormiston, R.; Ortega, L. F.; O'Shaughnessy, R.; Ottaway, D. J.; Overmier, H.; Owen, B. J.; Pace, A. E.; Page, J.; Page, M. A.; Pai, A.; Pai, S. A.; Palamos, J. R.; Palashov, O.; Palomba, C.; Pal-Singh, A.; Pan, H.; Pang, B.; Pang, P. T. H.; Pankow, C.; Pannarale, F.; Pant, B. C.; Paoletti, F.; Paoli, A.; Papa, M. A.; Paris, H. R.; Parker, W.; Pascucci, D.; Pasqualetti, A.; Passaquieti, R.; Passuello, D.; Patricelli, B.; Pearlstone, B. L.; Pedraza, M.; Pedurand, R.; Pekowsky, L.; Pele, A.; Penn, S.; Perez, C. J.; Perreca, A.; Perri, L. M.; Pfeiffer, H. P.; Phelps, M.; Piccinni, O. J.; Pichot, M.; Piergiovanni, F.; Pierro, V.; Pillant, G.; Pinard, L.; Pinto, I. M.; Pitkin, M.; Poggiani, R.; Popolizio, P.; Porter, E. K.; Post, A.; Powell, J.; Prasad, J.; Pratt, J. W. W.; Predoi, V.; Prestegard, T.; Prijatelj, M.; Principe, M.; Privitera, S.; Prix, R.; Prodi, G. A.; Prokhorov, L. G.; Puncken, O.; Punturo, M.; Puppo, P.; Pürrer, M.; Qi, H.; Qin, J.; Qiu, S.; Quetschke, V.; Quintero, E. A.; Quitzow-James, R.; Raab, F. J.; Rabeling, D. S.; Radkins, H.; Raffai, P.; Raja, S.; Rajan, C.; Rakhmanov, M.; Ramirez, K. E.; Rapagnani, P.; Raymond, V.; Razzano, M.; Read, J.; Regimbau, T.; Rei, L.; Reid, S.; Reitze, D. H.; Rew, H.; Reyes, S. D.; Ricci, F.; Ricker, P. M.; Rieger, S.; Riles, K.; Rizzo, M.; Robertson, N. A.; Robie, R.; Robinet, F.; Rocchi, A.; Rolland, L.; Rollins, J. G.; Roma, V. J.; Romano, R.; Romel, C. L.; Romie, J. H.; Rosińska, D.; Ross, M. P.; Rowan, S.; Rüdiger, A.; Ruggi, P.; Ryan, K.; Rynge, M.; Sachdev, S.; Sadecki, T.; Sadeghian, L.; Sakellariadou, M.; Salconi, L.; Saleem, M.; Salemi, F.; Samajdar, A.; Sammut, L.; Sampson, L. M.; Sanchez, E. J.; Sandberg, V.; Sandeen, B.; Sanders, J. R.; Sassolas, B.; Sathyaprakash, B. S.; Saulson, P. R.; Sauter, O.; Savage, R. L.; Sawadsky, A.; Schale, P.; Scheuer, J.; Schmidt, E.; Schmidt, J.; Schmidt, P.; Schnabel, R.; Schofield, R. M. S.; Schönbeck, A.; Schreiber, E.; Schuette, D.; Schulte, B. W.; Schutz, B. F.; Schwalbe, S. G.; Scott, J.; Scott, S. M.; Seidel, E.; Sellers, D.; Sengupta, A. S.; Sentenac, D.; Sequino, V.; Sergeev, A.; Shaddock, D. A.; Shaffer, T. J.; Shah, A. A.; Shahriar, M. S.; Shao, L.; Shapiro, B.; Shawhan, P.; Sheperd, A.; Shoemaker, D. H.; Shoemaker, D. M.; Siellez, K.; Siemens, X.; Sieniawska, M.; Sigg, D.; Silva, A. D.; Singer, A.; Singer, L. P.; Singh, A.; Singh, R.; Singhal, A.; Sintes, A. M.; Slagmolen, B. J. J.; Smith, B.; Smith, J. R.; Smith, R. J. E.; Son, E. J.; Sonnenberg, J. A.; Sorazu, B.; Sorrentino, F.; Souradeep, T.; Spencer, A. P.; Srivastava, A. K.; Staley, A.; Steinke, M.; Steinlechner, J.; Steinlechner, S.; Steinmeyer, D.; Stephens, B. C.; Stone, R.; Strain, K. A.; Stratta, G.; Strigin, S. E.; Sturani, R.; Stuver, A. L.; Summerscales, T. Z.; Sun, L.; Sunil, S.; Sutton, P. J.; Swinkels, B. L.; Szczepańczyk, M. J.; Tacca, M.; Talukder, D.; Tanner, D. B.; Tápai, M.; Taracchini, A.; Taylor, J. A.; Taylor, R.; Theeg, T.; Thomas, E. G.; Thomas, M.; Thomas, P.; Thorne, K. A.; Thorne, K. S.; Thrane, E.; Tiwari, S.; Tiwari, V.; Tokmakov, K. V.; Toland, K.; Tonelli, M.; Tornasi, Z.; Torrie, C. I.; Töyrä, D.; Travasso, F.; Traylor, G.; Trifirò, D.; Trinastic, J.; Tringali, M. C.; Trozzo, L.; Tsang, K. W.; Tse, M.; Tso, R.; Tuyenbayev, D.; Ueno, K.; Ugolini, D.; Unnikrishnan, C. S.; Urban, A. L.; Usman, S. A.; Vahi, K.; Vahlbruch, H.; Vajente, G.; Valdes, G.; van Bakel, N.; van Beuzekom, M.; van den Brand, J. F. J.; Van Den Broeck, C.; Vander-Hyde, D. C.; van der Schaaf, L.; van Heijningen, J. V.; van Veggel, A. A.; Vardaro, M.; Varma, V.; Vass, S.; Vasúth, M.; Vecchio, A.; Vedovato, G.; Veitch, J.; Veitch, P. J.; Venkateswara, K.; Venugopalan, G.; Verkindt, D.; Vetrano, F.; Viceré, A.; Viets, A. D.; Vinciguerra, S.; Vine, D. J.; Vinet, J.-Y.; Vitale, S.; Vo, T.; Vocca, H.; Vorvick, C.; Voss, D. V.; Vousden, W. D.; Vyatchanin, S. P.; Wade, A. R.; Wade, L. E.; Wade, M.; Walet, R.; Walker, M.; Wallace, L.; Walsh, S.; Wang, G.; Wang, H.; Wang, J. Z.; Wang, M.; Wang, Y.-F.; Wang, Y.; Ward, R. L.; Warner, J.; Was, M.; Watchi, J.; Weaver, B.; Wei, L.-W.; Weinert, M.; Weinstein, A. J.; Weiss, R.; Wen, L.; Wessel, E. K.; Weßels, P.; Westphal, T.; Wette, K.; Whelan, J. T.; Whiting, B. F.; Whittle, C.; Williams, D.; Williams, R. D.; Williamson, A. R.; Willis, J. L.; Willke, B.; Wimmer, M. H.; Winkler, W.; Wipf, C. C.; Wittel, H.; Woan, G.; Woehler, J.; Wofford, J.; Wong, K. W. K.; Worden, J.; Wright, J. L.; Wu, D. S.; Wu, G.; Yam, W.; Yamamoto, H.; Yancey, C. C.; Yap, M. J.; Yu, Hang; Yu, Haocun; Yvert, M.; ZadroŻny, A.; Zanolin, M.; Zelenova, T.; Zendri, J.-P.; Zevin, M.; Zhang, L.; Zhang, M.; Zhang, T.; Zhang, Y.-H.; Zhao, C.; Zhou, M.; Zhou, Z.; Zhu, X. J.; Zucker, M. E.; Zweizig, J.; Suvorova, S.; Moran, W.; Evans, R. J.; LIGO Scientific Collaboration; Virgo Collaboration

2017-06-01

Results are presented from a semicoherent search for continuous gravitational waves from the brightest low-mass X-ray binary, Scorpius X-1, using data collected during the first Advanced LIGO observing run. The search combines a frequency domain matched filter (Bessel-weighted F -statistic) with a hidden Markov model to track wandering of the neutron star spin frequency. No evidence of gravitational waves is found in the frequency range 60-650 Hz. Frequentist 95% confidence strain upper limits, h095 %=4.0 ×1 0-25, 8.3 ×1 0-25, and 3.0 ×1 0-25 for electromagnetically restricted source orientation, unknown polarization, and circular polarization, respectively, are reported at 106 Hz. They are ≤10 times higher than the theoretical torque-balance limit at 106 Hz.

Young Infants' Expectations about Hidden Objects

ERIC Educational Resources Information Center

Ruffman, Ted; Slade, Lance; Redman, Jessica

2005-01-01

Infants aged 3-5 months (mean of approximately 4 months) were given a novel anticipatory looking task to test object permanence understanding. They were trained to expect an experimenter to retrieve an object from behind a transparent screen upon hearing a cue (''Doors up, here comes the hand''). The experimenter then hid the object behind one of…

Design Graphics

NASA Technical Reports Server (NTRS)

1990-01-01

A mathematician, David R. Hedgley, Jr. developed a computer program that considers whether a line in a graphic model of a three-dimensional object should or should not be visible. Known as the Hidden Line Computer Code, the program automatically removes superfluous lines and displays an object from a specific viewpoint, just as the human eye would see it. An example of how one company uses the program is the experience of Birdair which specializes in production of fabric skylights and stadium covers. The fabric called SHEERFILL is a Teflon coated fiberglass material developed in cooperation with DuPont Company. SHEERFILL glazed structures are either tension structures or air-supported tension structures. Both are formed by patterned fabric sheets supported by a steel or aluminum frame or cable network. Birdair uses the Hidden Line Computer Code, to illustrate a prospective structure to an architect or owner. The program generates a three- dimensional perspective with the hidden lines removed. This program is still used by Birdair and continues to be commercially available to the public.

Three Dimensional Object Recognition Using a Complex Autoregressive Model

DTIC Science & Technology

1993-12-01

3.4.2 Template Matching Algorithm ...................... 3-16 3.4.3 K-Nearest-Neighbor ( KNN ) Techniques ................. 3-25 3.4.4 Hidden Markov Model...Neighbor ( KNN ) Test Results ...................... 4-13 4.2.1 Single-Look 1-NN Testing .......................... 4-14 4.2.2 Multiple-Look 1-NN Testing...4-15 4.2.3 Discussion of KNN Test Results ...................... 4-15 4.3 Hidden Markov Model (HMM) Test Results

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.

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

How should we question young children's understanding of aspectuality?

PubMed

Waters, Gillian M; Beck, Sarah R

2012-09-01

In two experiments, we investigated whether 4- to 5-year-old children's ability to demonstrate their understanding of aspectuality was influenced by how the test question was phrased. In Experiment 1, 60 children chose whether to look or feel to gain information about a hidden object (identifiable by sight or touch). Test questions referred either to the perceptual aspect of the hidden object (e.g., whether it was red or blue), the modality dimension (e.g., what colour it was), or the object's identity (e.g., which one it was). Children who heard the identity question performed worse than those who heard the aspect or dimension question. Further investigation in Experiment 2 (N= 23) established that children's difficulty with the identity question was not due to a problem recalling the objects. We discuss how the results of these methodological investigations impact on researchers' assessment of the development of aspectuality understanding. ©2011 The British Psychological Society.

Learning-based saliency model with depth information.

PubMed

Ma, Chih-Yao; Hang, Hsueh-Ming

2015-01-01

Most previous studies on visual saliency focused on two-dimensional (2D) scenes. Due to the rapidly growing three-dimensional (3D) video applications, it is very desirable to know how depth information affects human visual attention. In this study, we first conducted eye-fixation experiments on 3D images. Our fixation data set comprises 475 3D images and 16 subjects. We used a Tobii TX300 eye tracker (Tobii, Stockholm, Sweden) to track the eye movement of each subject. In addition, this database contains 475 computed depth maps. Due to the scarcity of public-domain 3D fixation data, this data set should be useful to the 3D visual attention research community. Then, a learning-based visual attention model was designed to predict human attention. In addition to the popular 2D features, we included the depth map and its derived features. The results indicate that the extra depth information can enhance the saliency estimation accuracy specifically for close-up objects hidden in a complex-texture background. In addition, we examined the effectiveness of various low-, mid-, and high-level features on saliency prediction. Compared with both 2D and 3D state-of-the-art saliency estimation models, our methods show better performance on the 3D test images. The eye-tracking database and the MATLAB source codes for the proposed saliency model and evaluation methods are available on our website.

On the Multi-Modal Object Tracking and Image Fusion Using Unsupervised Deep Learning Methodologies

NASA Astrophysics Data System (ADS)

LaHaye, N.; Ott, J.; Garay, M. J.; El-Askary, H. M.; Linstead, E.

2017-12-01

The number of different modalities of remote-sensors has been on the rise, resulting in large datasets with different complexity levels. Such complex datasets can provide valuable information separately, yet there is a bigger value in having a comprehensive view of them combined. As such, hidden information can be deduced through applying data mining techniques on the fused data. The curse of dimensionality of such fused data, due to the potentially vast dimension space, hinders our ability to have deep understanding of them. This is because each dataset requires a user to have instrument-specific and dataset-specific knowledge for optimum and meaningful usage. Once a user decides to use multiple datasets together, deeper understanding of translating and combining these datasets in a correct and effective manner is needed. Although there exists data centric techniques, generic automated methodologies that can potentially solve this problem completely don't exist. Here we are developing a system that aims to gain a detailed understanding of different data modalities. Such system will provide an analysis environment that gives the user useful feedback and can aid in research tasks. In our current work, we show the initial outputs our system implementation that leverages unsupervised deep learning techniques so not to burden the user with the task of labeling input data, while still allowing for a detailed machine understanding of the data. Our goal is to be able to track objects, like cloud systems or aerosols, across different image-like data-modalities. The proposed system is flexible, scalable and robust to understand complex likenesses within multi-modal data in a similar spatio-temporal range, and also to be able to co-register and fuse these images when needed.

Results from the Solar Hidden Photon Search (SHIPS)

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

Schwarz, Matthias; Schneide, Magnus; Susol, Jaroslaw

We present the results of a search for transversely polarised hidden photons (HPs) with ∼ 3 eV energies emitted from the Sun. These hypothetical particles, known also as paraphotons or dark sector photons, are theoretically well motivated for example by string theory inspired extensions of the Standard Model. Solar HPs of sub-eV mass can convert into photons of the same energy (photon ↔ HP oscillations are similar to neutrino flavour oscillations). At SHIPS this would take place inside a long light-tight high-vacuum tube, which tracks the Sun. The generated photons would then be focused into a low-noise photomultiplier at the far end ofmore » the tube. Our analysis of 330 h of data (and 330 h of background characterisation) reveals no signal of photons from solar hidden photon conversion. We estimate the rate of newly generated photons due to this conversion to be smaller than 25 mHz/m{sup 2} at the 95% C.L . Using this and a recent model of solar HP emission, we set stringent constraints on χ, the coupling constant between HPs and photons, as a function of the HP mass.« less

Results from the Solar Hidden Photon Search (SHIPS)

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

Schwarz, Matthias; Knabbe, Ernst-Axel; Lindner, Axel

We present the results of a search for transversely polarised hidden photons (HPs) with ∼3 eV energies emitted from the Sun. These hypothetical particles, known also as paraphotons or dark sector photons, are theoretically well motivated for example by string theory inspired extensions of the Standard Model. Solar HPs of sub-eV mass can convert into photons of the same energy (photon ↔ HP oscillations are similar to neutrino flavour oscillations). At SHIPS this would take place inside a long light-tight high-vacuum tube, which tracks the Sun. The generated photons would then be focused into a low-noise photomultiplier at the farmore » end of the tube. Our analysis of 330 h of data (and 330 h of background characterisation) reveals no signal of photons from solar hidden photon conversion. We estimate the rate of newly generated photons due to this conversion to be smaller than 25 mHz/m{sup 2} at the 95% C.L. Using this and a recent model of solar HP emission, we set stringent constraints on χ, the coupling constant between HPs and photons, as a function of the HP mass.« less

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.

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.

A Bell-type theorem without hidden variables

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

Stapp, Henry P.

2003-09-12

It is shown that no theory that satisfies certain premises can exclude faster-than-light influences. The premises include neither the existence of hidden variables nor counterfactual definiteness, nor any premise that effectively entails the general existence of outcomes of unperformed local measurements. All the premises are compatible with Copenhagen philosophy and the principles and predictions of relativistic quantum field theory. The present proof is contrasted with an earlier one with the same objective.

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).

Autonomous detection of crowd anomalies in multiple-camera surveillance feeds

NASA Astrophysics Data System (ADS)

Nordlöf, Jonas; Andersson, Maria

2016-10-01

A novel approach for autonomous detection of anomalies in crowded environments is presented in this paper. The proposed models uses a Gaussian mixture probability hypothesis density (GM-PHD) filter as feature extractor in conjunction with different Gaussian mixture hidden Markov models (GM-HMMs). Results, based on both simulated and recorded data, indicate that this method can track and detect anomalies on-line in individual crowds through multiple camera feeds in a crowded environment.

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.

Usage of cornea and sclera back reflected images captured in security cameras for forensic and card games applications

NASA Astrophysics Data System (ADS)

Zalevsky, Zeev; Ilovitsh, Asaf; Beiderman, Yevgeny

2013-10-01

We present an approach allowing seeing objects that are hidden and that are not positioned in direct line of sight with security inspection cameras. The approach is based on inspecting the back reflections obtained from the cornea and the sclera of the eyes of people attending the inspected scene and which are positioned in front of the hidden objects we aim to image after performing proper calibration with point light source (e.g. a LED). The scene can be a forensic scene or for instance a casino in which the application is to see the cards of poker players seating in front of you.

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…

Spread spectrum image steganography.

PubMed

Marvel, L M; Boncelet, C R; Retter, C T

1999-01-01

In this paper, we present a new method of digital steganography, entitled spread spectrum image steganography (SSIS). Steganography, which means "covered writing" in Greek, is the science of communicating in a hidden manner. Following a discussion of steganographic communication theory and review of existing techniques, the new method, SSIS, is introduced. This system hides and recovers a message of substantial length within digital imagery while maintaining the original image size and dynamic range. The hidden message can be recovered using appropriate keys without any knowledge of the original image. Image restoration, error-control coding, and techniques similar to spread spectrum are described, and the performance of the system is illustrated. A message embedded by this method can be in the form of text, imagery, or any other digital signal. Applications for such a data-hiding scheme include in-band captioning, covert communication, image tamperproofing, authentication, embedded control, and revision tracking.

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.

Early Knowledge of Object Motion: Continuity and Inertia.

ERIC Educational Resources Information Center

Spelke, Elizabeth; And Others

1994-01-01

Investigated whether infants infer that a hidden, freely moving object will move continuously and smoothly. Six- to 10- month olds inferred that the object's path would be connected and unobstructed, in accord with continuity. Younger infants did not infer this, in accord with inertia. At 8 and 10 months, knowledge of inertia emerged but remained…

The Influence of Object Conceptions on the Mechanical Intuitions of Children and Adults.

ERIC Educational Resources Information Center

Rosser, Rosemary A.; Chandler, Kacey

1995-01-01

Examined how children's and adults' initial conceptions of objects and space influence predictions about the physical world, but lead the naive person to misconstrue a dynamic event. Found that participants proficiently anticipated where an oscillating screen would contact a hidden object, but underestimated the distance until contact.…

Phase object retrieval through scattering medium

NASA Astrophysics Data System (ADS)

Zhao, Ming; Zhao, Meijing; Wu, Houde; Xu, Wenhai

2018-05-01

Optical imaging through a scattering medium has been an interesting and important research topic, especially in the field of biomedical imaging. However, it is still a challenging task due to strong scattering. This paper proposes to recover the phase object behind the scattering medium from one single-shot speckle intensity image using calibrated transmission matrices (TMs). We construct the forward model as a non-linear mapping, since the intensity image loses the phase information, and then a generalized phase retrieval algorithm is employed to recover the hidden object. Moreover, we show that a phase object can be reconstructed with a small portion of the speckle image captured by the camera. The simulation is performed to demonstrate our scheme and test its performance. Finally, a real experiment is set up, we measure the TMs from the scattering medium, and then use it to reconstruct the hidden object. We show that a phase object of size 32 × 32 is retrieved from 150 × 150 speckle grains, which is only 1/50 of the speckles area. We believe our proposed method can benefit the community of imaging through the scattering medium.

A neurocomputational model of figure-ground discrimination and target tracking.

PubMed

Sun, H; Liu, L; Guo, A

1999-01-01

A neurocomputational model is presented for figureground discrimination and target tracking. In the model, the elementary motion detectors of the correlation type, the computational modules of saccadic and smooth pursuit eye movement, an oscillatory neural-network motion perception module and a selective attention module are involved. It is shown that through the oscillatory amplitude and frequency encoding, and selective synchronization of phase oscillators, the figure and the ground can be successfully discriminated from each other. The receptive fields developed by hidden units of the networks were surprisingly similar to the actual receptive fields and columnar organization found in the primate visual cortex. It is suggested that equivalent mechanisms may exist in the primate visual cortex to discriminate figure-ground in both temporal and spatial domains.

Quasi-steady state reduction of molecular motor-based models of directed intermittent search.

PubMed

Newby, Jay M; Bressloff, Paul C

2010-10-01

We present a quasi-steady state reduction of a linear reaction-hyperbolic master equation describing the directed intermittent search for a hidden target by a motor-driven particle moving on a one-dimensional filament track. The particle is injected at one end of the track and randomly switches between stationary search phases and mobile nonsearch phases that are biased in the anterograde direction. There is a finite possibility that the particle fails to find the target due to an absorbing boundary at the other end of the track. Such a scenario is exemplified by the motor-driven transport of vesicular cargo to synaptic targets located on the axon or dendrites of a neuron. The reduced model is described by a scalar Fokker-Planck (FP) equation, which has an additional inhomogeneous decay term that takes into account absorption by the target. The FP equation is used to compute the probability of finding the hidden target (hitting probability) and the corresponding conditional mean first passage time (MFPT) in terms of the effective drift velocity V, diffusivity D, and target absorption rate λ of the random search. The quasi-steady state reduction determines V, D, and λ in terms of the various biophysical parameters of the underlying motor transport model. We first apply our analysis to a simple 3-state model and show that our quasi-steady state reduction yields results that are in excellent agreement with Monte Carlo simulations of the full system under physiologically reasonable conditions. We then consider a more complex multiple motor model of bidirectional transport, in which opposing motors compete in a "tug-of-war", and use this to explore how ATP concentration might regulate the delivery of cargo to synaptic targets.

Structure and Randomness of Continuous-Time, Discrete-Event Processes

NASA Astrophysics Data System (ADS)

Marzen, Sarah E.; Crutchfield, James P.

2017-10-01

Loosely speaking, the Shannon entropy rate is used to gauge a stochastic process' intrinsic randomness; the statistical complexity gives the cost of predicting the process. We calculate, for the first time, the entropy rate and statistical complexity of stochastic processes generated by finite unifilar hidden semi-Markov models—memoryful, state-dependent versions of renewal processes. Calculating these quantities requires introducing novel mathematical objects (ɛ -machines of hidden semi-Markov processes) and new information-theoretic methods to stochastic processes.

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

Adaptive early detection ML/PDA estimator for LO targets with EO sensors

NASA Astrophysics Data System (ADS)

Chummun, Muhammad R.; Kirubarajan, Thiagalingam; Bar-Shalom, Yaakov

2000-07-01

The batch Maximum Likelihood Estimator, combined with Probabilistic Data (ML-PDA), has been shown to be effective in acquiring low observable (LO) - low SNR - non-maneuvering targets in the presence of heavy clutter. The use of signal strength or amplitude information (AI) in the ML-PDA estimator with AI in a sliding-window fashion, to detect high- speed targets in heavy clutter using electro-optical (EO) sensors. The initial time and the length of the sliding-window are adjusted adaptively according to the information content of the received measurements. A track validation scheme via hypothesis testing is developed to confirm the estimated track, that is, the presence of a target, in each window. The sliding-window ML-PDA approach, together with track validation, enables early detection by rejecting noninformative scans, target reacquisition in case of temporary target disappearance and the handling of targets with speeds evolving over time. The proposed algorithm is shown to detect the target, which is hidden in as many as 600 false alarms per scan, 10 frames earlier than the Multiple Hypothesis Tracking (MHT) algorithm.

Religion, Spirituality, and the Hidden Curriculum: Medical Student and Faculty Reflections

PubMed Central

Balboni, Michael J.; Bandini, Julia; Mitchell, Christine; Epstein-Peterson, Zachary D.; Amobi, Ada; Cahill, Jonathan; Enzinger, Andrea C.; Peteet, John; Balboni, Tracy

2017-01-01

Context Religion and spirituality play an important role in physicians’ medical practice, but little research has examined their influence within the socialization of medical trainees and the hidden curriculum. Objectives The objective is to explore the role of religion and spirituality as they intersect with aspects of medicine’s hidden curriculum. Methods Semiscripted, one-on-one interviews and focus groups (n = 33 respondents) were conducted to assess Harvard Medical School student and faculty experiences of religion/spirituality and the professionalization process during medical training. Using grounded theory, theme extraction was performed with interdisciplinary input (medicine, sociology, and theology), yielding a high inter-rater reliability score (kappa = 0.75). Results Three domains emerged where religion and spirituality appear as a factor in medical training. First, religion/spirituality may present unique challenges and benefits in relation to the hidden curriculum. Religious/spiritual respondents more often reported to struggle with issues of personal identity, increased self-doubt, and perceived medical knowledge inadequacy. However, religious/spiritual participants less often described relationship conflicts within the medical team, work-life imbalance, and emotional stress arising from patient suffering. Second, religion/spirituality may influence coping strategies during encounters with patient suffering. Religious/spiritual trainees described using prayer, faith, and compassion as means for coping whereas nonreligious/nonspiritual trainees discussed compartmentalization and emotional repression. Third, levels of religion/spirituality appear to fluctuate in relation to medical training, with many trainees experiencing an increase in religiousness/spirituality during training. Conclusion Religion/spirituality has a largely unstudied but possibly influential role in medical student socialization. Future study is needed to characterize its function within the hidden curriculum. PMID:26025271

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.

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.

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.

The hidden ion population - Revisited. [in outer plasmasphere

NASA Technical Reports Server (NTRS)

Olsen, R. C.; Chappell, C. R.; Gallagher, D. L.; Green, J. L.; Gurnett, D. A.

1985-01-01

In an investigation conducted by Olsen (1982) on the basis of particle data taken with an electrostatic analyzer, it was found that a cold plasma population with a density between 10 and 100 per cu cm appeared suddenly when the satellite was eclipsed, but was hidden in sunlight. The present paper has the objective to show further measurements of ordinarily 'hidden' ion populations, in order to resolve some of the questions raised in connection with the Scatha satellite data reported by Olsen. It is found that the retarding ion mass spectrometer (RIMS) detector is capable of measuring the core of the plasma distribution in sunlight and eclipse, though the task is more easily done in eclipse. There are, however, limitations concerning the ability of the detector to measure all the plasma, all the time. It is, therefore, pointed out that continuous effective measurements of the 'hidden' ion population of the magnetosphere still awaits satellites with effective means of potential control.

On Levels of Awareness of Objects in Infants and Students Thereof.

ERIC Educational Resources Information Center

Gratch, Gerald

This paper describes a series of longitudinal experiments which dealt with the development of object awareness in infants, ages 6-18 months. The experiments were designed to document and evaluate Piaget's account of this development. The studies focused on two types of phenomena: (1) when infants first find an object hidden in one place, they will…

Steganography on multiple MP3 files using spread spectrum and Shamir's secret sharing

NASA Astrophysics Data System (ADS)

Yoeseph, N. M.; Purnomo, F. A.; Riasti, B. K.; Safiie, M. A.; Hidayat, T. N.

2016-11-01

The purpose of steganography is how to hide data into another media. In order to increase security of data, steganography technique is often combined with cryptography. The weakness of this combination technique is the data was centralized. Therefore, a steganography technique is develop by using combination of spread spectrum and secret sharing technique. In steganography with secret sharing, shares of data is created and hidden in several medium. Medium used to concealed shares were MP3 files. Hiding technique used was Spread Spectrum. Secret sharing scheme used was Shamir's Secret Sharing. The result showed that steganography with spread spectrum combined with Shamir's Secret Share using MP3 files as medium produce a technique that could hid data into several cover. To extract and reconstruct the data hidden in stego object, it is needed the amount of stego object which more or equal to its threshold. Furthermore, stego objects were imperceptible and robust.

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.

Ferromagnetic Objects Magnetovision Detection System.

PubMed

Nowicki, Michał; Szewczyk, Roman

2013-12-02

This paper presents the application of a weak magnetic fields magnetovision scanning system for detection of dangerous ferromagnetic objects. A measurement system was developed and built to study the magnetic field vector distributions. The measurements of the Earth's field distortions caused by various ferromagnetic objects were carried out. The ability for passive detection of hidden or buried dangerous objects and the determination of their location was demonstrated.

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

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.

Invisible waves and hidden realms: augmented reality and experimental art

NASA Astrophysics Data System (ADS)

Ruzanka, Silvia

2012-03-01

Augmented reality is way of both altering the visible and revealing the invisible. It offers new opportunities for artistic exploration through virtual interventions in real space. In this paper, the author describes the implementation of two art installations using different AR technologies, one using optical marker tracking on mobile devices and one integrating stereoscopic projections into the physical environment. The first artwork, De Ondas y Abejas (The Waves and the Bees), is based on the widely publicized (but unproven) hypothesis of a link between cellphone radiation and the phenomenon of bee colony collapse disorder. Using an Android tablet, viewers search out small fiducial markers in the shape of electromagnetic waves hidden throughout the gallery, which reveal swarms of bees scattered on the floor. The piece also creates a generative soundscape based on electromagnetic fields. The second artwork, Urban Fauna, is a series of animations in which features of the urban landscape become plants and animals. Surveillance cameras become flocks of birds while miniature cellphone towers, lampposts, and telephone poles grow like small seedlings in time-lapse animation. The animations are presented as small stereoscopic projections, integrated into the physical space of the gallery. These two pieces explore the relationship between nature and technology through the visualization of invisible forces and hidden alternate realities.

Accurate step-hold tracking of smoothly varying periodic and aperiodic probability.

PubMed

Ricci, Matthew; Gallistel, Randy

2017-07-01

Subjects observing many samples from a Bernoulli distribution are able to perceive an estimate of the generating parameter. A question of fundamental importance is how the current percept-what we think the probability now is-depends on the sequence of observed samples. Answers to this question are strongly constrained by the manner in which the current percept changes in response to changes in the hidden parameter. Subjects do not update their percept trial-by-trial when the hidden probability undergoes unpredictable and unsignaled step changes; instead, they update it only intermittently in a step-hold pattern. It could be that the step-hold pattern is not essential to the perception of probability and is only an artifact of step changes in the hidden parameter. However, we now report that the step-hold pattern obtains even when the parameter varies slowly and smoothly. It obtains even when the smooth variation is periodic (sinusoidal) and perceived as such. We elaborate on a previously published theory that accounts for: (i) the quantitative properties of the step-hold update pattern; (ii) subjects' quick and accurate reporting of changes; (iii) subjects' second thoughts about previously reported changes; (iv) subjects' detection of higher-order structure in patterns of change. We also call attention to the challenges these results pose for trial-by-trial updating theories.

A ball is not a Kong: Odor representation and search behavior in domestic dogs (Canis familiaris) of different education.

PubMed

Bräuer, Juliane; Belger, Julia

2018-05-01

There has been a growing interest in the cognitive skills of domestic dogs, but most current knowledge about dogs' understanding of their environment is limited to the visual or auditory modality. Although it is well known that dogs have an excellent olfactory sense and that they rely on olfaction heavily when exploring the environment or recognizing individuals, it remains unclear whether dogs perceive odors as representing specific objects. In the current study, we examined this aspect of dogs' perception of the world. Dogs were presented with a violation-of-expectation paradigm in which they could track the odor trail of one target (Target A), but at the end of the trail, they found another target (Target B). We explored (a) what dogs expect when they smell the trail of an object, (b) how they search for an object, and (c) how their educational background influences their ability to find a hidden object, by comparing family dogs and working dogs that had passed exams for police or rescue dogs. We found that all subjects showed a flexible searching behavior, with the working dogs being more effective but the family dogs learning to be effective over trials. In the first trial, dogs showed measurable signs of "surprise" (i.e., further searching for Target A) when they found Target B, which did not correspond to the odor of Target A from the trail. We conclude that dogs represent what they smell and search flexibly, which is independent from their educational background. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

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

Multiplicative processes in visual cognition

NASA Astrophysics Data System (ADS)

Credidio, H. F.; Teixeira, E. N.; Reis, S. D. S.; Moreira, A. A.; Andrade, J. S.

2014-03-01

The Central Limit Theorem (CLT) is certainly one of the most important results in the field of statistics. The simple fact that the addition of many random variables can generate the same probability curve, elucidated the underlying process for a broad spectrum of natural systems, ranging from the statistical distribution of human heights to the distribution of measurement errors, to mention a few. An extension of the CLT can be applied to multiplicative processes, where a given measure is the result of the product of many random variables. The statistical signature of these processes is rather ubiquitous, appearing in a diverse range of natural phenomena, including the distributions of incomes, body weights, rainfall, and fragment sizes in a rock crushing process. Here we corroborate results from previous studies which indicate the presence of multiplicative processes in a particular type of visual cognition task, namely, the visual search for hidden objects. Precisely, our results from eye-tracking experiments show that the distribution of fixation times during visual search obeys a log-normal pattern, while the fixational radii of gyration follow a power-law behavior.

Recognizing visual focus of attention from head pose in natural meetings.

PubMed

Ba, Sileye O; Odobez, Jean-Marc

2009-02-01

We address the problem of recognizing the visual focus of attention (VFOA) of meeting participants based on their head pose. To this end, the head pose observations are modeled using a Gaussian mixture model (GMM) or a hidden Markov model (HMM) whose hidden states correspond to the VFOA. The novelties of this paper are threefold. First, contrary to previous studies on the topic, in our setup, the potential VFOA of a person is not restricted to other participants only. It includes environmental targets as well (a table and a projection screen), which increases the complexity of the task, with more VFOA targets spread in the pan as well as tilt gaze space. Second, we propose a geometric model to set the GMM or HMM parameters by exploiting results from cognitive science on saccadic eye motion, which allows the prediction of the head pose given a gaze target. Third, an unsupervised parameter adaptation step not using any labeled data is proposed, which accounts for the specific gazing behavior of each participant. Using a publicly available corpus of eight meetings featuring four persons, we analyze the above methods by evaluating, through objective performance measures, the recognition of the VFOA from head pose information obtained either using a magnetic sensor device or a vision-based tracking system. The results clearly show that in such complex but realistic situations, the VFOA recognition performance is highly dependent on how well the visual targets are separated for a given meeting participant. In addition, the results show that the use of a geometric model with unsupervised adaptation achieves better results than the use of training data to set the HMM parameters.

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.

Marine Ship Automatic Identification System (AIS) for Enhanced Coastal Security Capabilities: An Oil Spill Tracking Application

DTIC Science & Technology

2007-09-01

in port, harbor or waterway incidents; and, oil or oily wastes illegally dumped at sea, including illegal discharge of oily bilge or ballast waters ...quantities of oily waste and oily bilge water and sludge at sea using specially installed pipes, which they were careful to have removed and hidden...detailing specifics for oil and bilge water handling equipment, oil hold washing protocols, and a 15 part per million discharge limit of oil content in

HCE Research Coordination Directorate (ReCoorD Database)

DTIC Science & Technology

2016-04-27

portfolio management is often hidden within broader mission scopes and visibility into those portfolio is often limited at best. Current specialty...specific tracking databases do not exist. Current broad-sweeping portfolio management tools do not exist (not true--define terms?). The HCE receives...requests from a variety of oversight bodies for reports on the current state of project-through- portfolio efforts. Tools such as NIH’s Reporter, while still in development, do not yet appear to meet HCE element requirements.

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…

Coding Location: The View from Toddler Studies

ERIC Educational Resources Information Center

Huttenlocher, Janellen

2008-01-01

The ability to locate objects in the environment is adaptively important for mobile organisms. Research on location coding reveals that even toddlers have considerable spatial skill. Important information has been obtained using a disorientation task in which children watch a target object being hidden and are then blindfolded and rotated so they…

Discovering the Science Hidden behind Real Objects

ERIC Educational Resources Information Center

Desforges, Ruth

2018-01-01

The Zoological Society of London (ZSL) has a huge collection of unique and curious objects from the natural world that have been loaned to us by HM Revenue and Customs after being seized at the UK border. Among the turtle shells and snake skins, the strangest of these is perhaps the freestanding rhino-foot ash tray. This single object can open up…

Selective Information Use and Perseveration in the Search Behavior of Infants and Young Children.

ERIC Educational Resources Information Center

Sophian, Catherine; Wellman, Henry M.

1983-01-01

Experiment one tested 9- and 16-month-old children on a modification of Piaget's Stage IV object permanence task, examining infants' use of information from previous experiences with an object and from a recent hiding to locate a hidden object. In experiment two, two-, two-and-a-half-, and four-year-old children additionally received verbal…

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.

Intuitive optics: what great apes infer from mirrors and shadows.

PubMed

Völter, Christoph J; Call, Josep

2018-05-02

There is ongoing debate about the extent to which nonhuman animals, like humans, can go beyond first-order perceptual information to abstract structural information from their environment. To provide more empirical evidence regarding this question, we examined what type of information great apes (chimpanzees, bonobos, and orangutans) gain from optical effects such as shadows and mirror images. In an initial experiment, we investigated whether apes would use mirror images and shadows to locate hidden food. We found that all examined ape species used these cues to find the food. Follow-up experiments showed that apes neither confused these optical effects with the food rewards nor did they merely associate cues with food. First, naïve chimpanzees used the shadow of the hidden food to locate it but they did not learn within the same number of trials to use a perceptually similar rubber patch as indicator of the hidden food reward. Second, apes made use of the mirror images to estimate the distance of the hidden food from their own body. Depending on the distance, apes either pointed into the direction of the food or tried to access the hidden food directly. Third, apes showed some sensitivity to the geometrical relation between mirror orientation and mirrored objects when searching hidden food. Fourth, apes tended to interpret mirror images and pictures of these mirror images differently depending on their prior knowledge. Together, these findings suggest that apes are sensitive to the optical relation between mirror images and shadows and their physical referents.

An interactive visualization tool for mobile objects

NASA Astrophysics Data System (ADS)

Kobayashi, Tetsuo

Recent advancements in mobile devices---such as Global Positioning System (GPS), cellular phones, car navigation system, and radio-frequency identification (RFID)---have greatly influenced the nature and volume of data about individual-based movement in space and time. Due to the prevalence of mobile devices, vast amounts of mobile objects data are being produced and stored in databases, overwhelming the capacity of traditional spatial analytical methods. There is a growing need for discovering unexpected patterns, trends, and relationships that are hidden in the massive mobile objects data. Geographic visualization (GVis) and knowledge discovery in databases (KDD) are two major research fields that are associated with knowledge discovery and construction. Their major research challenges are the integration of GVis and KDD, enhancing the ability to handle large volume mobile objects data, and high interactivity between the computer and users of GVis and KDD tools. This dissertation proposes a visualization toolkit to enable highly interactive visual data exploration for mobile objects datasets. Vector algebraic representation and online analytical processing (OLAP) are utilized for managing and querying the mobile object data to accomplish high interactivity of the visualization tool. In addition, reconstructing trajectories at user-defined levels of temporal granularity with time aggregation methods allows exploration of the individual objects at different levels of movement generality. At a given level of generality, individual paths can be combined into synthetic summary paths based on three similarity measures, namely, locational similarity, directional similarity, and geometric similarity functions. A visualization toolkit based on the space-time cube concept exploits these functionalities to create a user-interactive environment for exploring mobile objects data. Furthermore, the characteristics of visualized trajectories are exported to be utilized for data mining, which leads to the integration of GVis and KDD. Case studies using three movement datasets (personal travel data survey in Lexington, Kentucky, wild chicken movement data in Thailand, and self-tracking data in Utah) demonstrate the potential of the system to extract meaningful patterns from the otherwise difficult to comprehend collections of space-time trajectories.

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…

Hidden Surface Removal through Object Space Decomposition.

DTIC Science & Technology

1982-01-01

12 2.1 Methods of Subdividing the Object Space ..................................................... 14 2.2 Accessing...AC.AIIA TO5ASK FORCE MNT OF TECH WRIONT-PATTERSON AFB 0O4 P/O 1a/I 64100(6 SURFACE REMOVAL THROWN4 OBJECT SPACE 0(COMPOSIT109d.(U UiCLASIFIEC AFZITNl...Surface Removal Through Object Space THESlS/ J AJ;I Decomposition 6. PERFORMING ORG. REPORT NUMBER 7. AUTHOR() a. CONTRACT OR GRANT NUMBER(s) Robert

Children's Perception of Black and White Boxes and Bobo Dolls as a Reflection of How They Regard Their Own and Other's Racial Membership.

ERIC Educational Resources Information Center

Stabler, John R.; Johnson, Edward E.

Investigation of how children's responses to black and white objects reflect racial concepts is reported. One series of experiments asking Headstart children to guess which objects they liked or disliked were hidden in black or white boxes. Although white children guessed more often that positively evaluated objects were in white boxes, black…

Hidden symmetries for ellipsoid-solitonic deformations of Kerr-Sen black holes and quantum anomalies

NASA Astrophysics Data System (ADS)

Vacaru, Sergiu I.

2013-02-01

We prove the existence of hidden symmetries in the general relativity theory defined by exact solutions with generic off-diagonal metrics, nonholonomic (non-integrable) constraints, and deformations of the frame and linear connection structure. A special role in characterization of such spacetimes is played by the corresponding nonholonomic generalizations of Stackel-Killing and Killing-Yano tensors. There are constructed new classes of black hole solutions and we study hidden symmetries for ellipsoidal and/or solitonic deformations of "prime" Kerr-Sen black holes into "target" off-diagonal metrics. In general, the classical conserved quantities (integrable and not-integrable) do not transfer to the quantized systems and produce quantum gravitational anomalies. We prove that such anomalies can be eliminated via corresponding nonholonomic deformations of fundamental geometric objects (connections and corresponding Riemannian and Ricci tensors) and by frame transforms.

What do Two-Year-Olds Understand about Hidden-Object Events?

ERIC Educational Resources Information Center

Mash, Clay; Novak, Elizabeth; Berthier, Neil E.; Keen, Rachel

2006-01-01

Preferential-looking studies suggest that by 2 months of age, infants may have knowledge about some object properties, such as solidity. Manual search studies of toddlers examining these same concepts, however, have failed to provide evidence for the same understanding. Investigators have recently attempted to reconcile this disparity but failed…

Preschool Children's Understanding of Semantic Relations.

ERIC Educational Resources Information Center

Fu, Panfang

Two experiments investigated 4- to 5-year olds' understanding of semantic relations and methods for incorporating new words into their lexicon. In one experiment, 24 children were shown a picture of a container and told that an object called "X" was hidden inside it. Children were asked questions about the object X and about…

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

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.

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.

Three-dimensional reconstruction with x-ray shape-from-silhouette

NASA Astrophysics Data System (ADS)

Simioni, E.; Ratti, F.; Calliari, I.; Poletto, L.

2010-09-01

In the field of restoration of ancient handworks, X-ray tomography is a powerful method to reconstruct the internal structure of the object in non-invasive way. In some cases, such as small objects fully realized with hard metals and completely hidden by clay or products of oxidation, the tomography, although necessary to obtain the 3D appearance of the object, does not give any additional information on its internal monolithic structure. We present here the application of the shape-from-silhouette technique on X-ray images to reconstruct the 3D profile of handworks. The acquisition technique is similar to tomography, since several X-ray images are taken while the object is rotated. Some reference points are placed on a structure co-rotating with the object and are acquired on the images for calibration and registration. The shape-from-silhouette algorithm gives finally the 3D appearance of the handwork. We present the analysis of a tin pendant of VI-VIII century b.C. (Venetian area) completely hidden by solid ground. The 3D reconstruction shows surprisingly that the pendant is a very elaborated piece, with two embraced figures that were completely invisible before restoration.

3D abnormal behavior recognition in power generation

NASA Astrophysics Data System (ADS)

Wei, Zhenhua; Li, Xuesen; Su, Jie; Lin, Jie

2011-06-01

So far most research of human behavior recognition focus on simple individual behavior, such as wave, crouch, jump and bend. This paper will focus on abnormal behavior with objects carrying in power generation. Such as using mobile communication device in main control room, taking helmet off during working and lying down in high place. Taking account of the color and shape are fixed, we adopted edge detecting by color tracking to recognize object in worker. This paper introduces a method, which using geometric character of skeleton and its angle to express sequence of three-dimensional human behavior data. Then adopting Semi-join critical step Hidden Markov Model, weighing probability of critical steps' output to reduce the computational complexity. Training model for every behavior, mean while select some skeleton frames from 3D behavior sample to form a critical step set. This set is a bridge linking 2D observation behavior with 3D human joints feature. The 3D reconstruction is not required during the 2D behavior recognition phase. In the beginning of recognition progress, finding the best match for every frame of 2D observed sample in 3D skeleton set. After that, 2D observed skeleton frames sample will be identified as a specifically 3D behavior by behavior-classifier. The effectiveness of the proposed algorithm is demonstrated with experiments in similar power generation environment.

Industrial radiography with cosmic-ray muons: A progress report

NASA Astrophysics Data System (ADS)

Gilboy, W. B.; Jenneson, P. M.; Simons, S. J. R.; Stanley, S. J.; Rhodes, D.

2007-09-01

Cosmic-ray produced muons arrive at the surface of the earth with enormous energies ranging up to 1012 GeV. There have been sporadic attempts to exploit their extreme penetration through matter to probe the internal structures of very large objects, including an Egyptian pyramid and a volcano but their very low intensity per unit area ( ≈1 cm-2 per min) generally restricts the practicably attainable spatial resolution to large dimensions. Nevertheless the more intense low energy region of the muon spectrum has recently been shown to be capable of detecting high-Z objects with dimensions of the order of 10 cm hidden inside large transport containers in measurement times of minutes. These various developments have encouraged further studies of potential industrial uses of cosmic-ray muons in industrial applications. In order to gain maximum benefit from the low muon flux large area detectors are required and plastic scintillators offer useful advantages in size, cost and simplicity. Scintillator slabs up to 1 m2 square and 76.2 mm thick are undergoing testing for applications in the nuclear industry. The most direct approach employs photomultiplier tubes at each corner to measure the relative sizes of muon induced pulses to determine the location of each muon track passing through the scintillator. The performance of this technique is reported and its imaging potential is assessed.

Smart Sensor-Based Motion Detection System for Hand Movement Training in Open Surgery.

PubMed

Sun, Xinyao; Byrns, Simon; Cheng, Irene; Zheng, Bin; Basu, Anup

2017-02-01

We introduce a smart sensor-based motion detection technique for objective measurement and assessment of surgical dexterity among users at different experience levels. The goal is to allow trainees to evaluate their performance based on a reference model shared through communication technology, e.g., the Internet, without the physical presence of an evaluating surgeon. While in the current implementation we used a Leap Motion Controller to obtain motion data for analysis, our technique can be applied to motion data captured by other smart sensors, e.g., OptiTrack. To differentiate motions captured from different participants, measurement and assessment in our approach are achieved using two strategies: (1) low level descriptive statistical analysis, and (2) Hidden Markov Model (HMM) classification. Based on our surgical knot tying task experiment, we can conclude that finger motions generated from users with different surgical dexterity, e.g., expert and novice performers, display differences in path length, number of movements and task completion time. In order to validate the discriminatory ability of HMM for classifying different movement patterns, a non-surgical task was included in our analysis. Experimental results demonstrate that our approach had 100 % accuracy in discriminating between expert and novice performances. Our proposed motion analysis technique applied to open surgical procedures is a promising step towards the development of objective computer-assisted assessment and training systems.

Dense Plasma Focus: physics and applications (radiation material science, single-shot disclosure of hidden illegal objects, radiation biology and medicine, etc.)

NASA Astrophysics Data System (ADS)

Gribkov, V. A.; Miklaszewski, R.; Paduch, M.; Zielinska, E.; Chernyshova, M.; Pisarczyk, T.; Pimenov, V. N.; Demina, E. V.; Niemela, J.; Crespo, M.-L.; Cicuttin, A.; Tomaszewski, K.; Sadowski, M. J.; Skladnik-Sadowska, E.; Pytel, K.; Zawadka, A.; Giannini, G.; Longo, F.; Talab, A.; Ul'yanenko, S. E.

2015-03-01

The paper presents some outcomes obtained during the year of 2013 of the activity in the frame of the International Atomic Energy Agency Co-ordinated research project "Investigations of Materials under High Repetition and Intense Fusion-Relevant Pulses". The main results are related to the effects created at the interaction of powerful pulses of different types of radiation (soft and hard X-rays, hot plasma and fast ion streams, neutrons, etc. generated in Dense Plasma Focus (DPF) facilities) with various materials including those that are counted as perspective ones for their use in future thermonuclear reactors. Besides we discuss phenomena observed at the irradiation of biological test objects. We examine possible applications of nanosecond powerful pulses of neutrons to the aims of nuclear medicine and for disclosure of hidden illegal objects. Special attention is devoted to discussions of a possibility to create extremely large and enormously diminutive DPF devices and probabilities of their use in energetics, medicine and modern electronics.

Stress-induced cortisol secretion impairs detection performance in x-ray baggage screening for hidden weapons by screening novices.

PubMed

Thomas, Livia; Schwaninger, Adrian; Heimgartner, Nadja; Hedinger, Patrik; Hofer, Franziska; Ehlert, Ulrike; Wirtz, Petra H

2014-09-01

Aviation security strongly depends on screeners' performance in the detection of threat objects in x-ray images of passenger bags. We examined for the first time the effects of stress and stress-induced cortisol increases on detection performance of hidden weapons in an x-ray baggage screening task. We randomly assigned 48 participants either to a stress or a nonstress group. The stress group was exposed to a standardized psychosocial stress test (TSST). Before and after stress/nonstress, participants had to detect threat objects in a computer-based object recognition test (X-ray ORT). We repeatedly measured salivary cortisol and X-ray ORT performance before and after stress/nonstress. Cortisol increases in reaction to psychosocial stress induction but not to nonstress independently impaired x-ray detection performance. Our results suggest that stress-induced cortisol increases at peak reactivity impair x-ray screening performance. Copyright © 2014 Society for Psychophysiological Research.

Results and experiences from the NATO Common Shield DAT#7 experiment for the Defence Against Terrorism program

NASA Astrophysics Data System (ADS)

Peichl, Markus; Dill, Stephan; Jirousek, Matthias; Süß, Helmut

2009-05-01

Passive microwave imaging allows a daytime independent observation and examination of objects and persons without artificial exposure under nearly all weather conditions. The penetration capability of microwaves allows the detection of hidden objects like weapons and explosive devices under the clothing. In August/September 2008 a comprehensive military experiment was conducted by the German armed forces at the naval base Eckernfoerde, Germany. One activity in the Eckernfoerde trial was the simulation of a military entrance portal by a tent including various imaging and a chemical sensor suite. Besides commercial optical and infrared cameras various passive millimeter-wave imagers have been used from different German research institutions. The DLR Microwaves and Radar Institute, Department for Reconnaissance and Security (HR-AS), provided an imaging radiometer scanner operating at W band. A multitude of situations have been simulated and many persons carrying hidden objects under their clothing have been scanned. Some exemplary results from the trial are shown and discussed in the paper.

Analyzing Hidden Semantics in Social Bookmarking of Open Educational Resources

NASA Astrophysics Data System (ADS)

Minguillón, Julià

Web 2.0 services such as social bookmarking allow users to manage and share the links they find interesting, adding their own tags for describing them. This is especially interesting in the field of open educational resources, as delicious is a simple way to bridge the institutional point of view (i.e. learning object repositories) with the individual one (i.e. personal collections), thus promoting the discovering and sharing of such resources by other users. In this paper we propose a methodology for analyzing such tags in order to discover hidden semantics (i.e. taxonomies and vocabularies) that can be used to improve descriptions of learning objects and make learning object repositories more visible and discoverable. We propose the use of a simple statistical analysis tool such as principal component analysis to discover which tags create clusters that can be semantically interpreted. We will compare the obtained results with a collection of resources related to open educational resources, in order to better understand the real needs of people searching for open educational resources.

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.

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

A Hidden Surface Algorithm for Computer Generated Halftone Pictures

DTIC Science & Technology

converting data describing three-dimensional objects into data that can be used to generate two-dimensional halftone images. It deals with some problems that arise in black and white, and color shading.

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…

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.

Apes Know that Hidden Objects Can Affect the Orientation of Other Objects

ERIC Educational Resources Information Center

Call, Josep

2007-01-01

Four bonobos, seven gorillas, and six orangutans were presented with two small rectangular boards on a platform. One of the boards had a piece of food under it so that it acquired an inclined orientation whereas the other remained flat on the platform. Subjects preferentially selected the inclined board. In another experiment, subjects were…

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.

Real-time computer treatment of THz passive device images with the high image quality

NASA Astrophysics Data System (ADS)

Trofimov, Vyacheslav A.; Trofimov, Vladislav V.

2012-06-01

We demonstrate real-time computer code improving significantly the quality of images captured by the passive THz imaging system. The code is not only designed for a THz passive device: it can be applied to any kind of such devices and active THz imaging systems as well. We applied our code for computer processing of images captured by four passive THz imaging devices manufactured by different companies. It should be stressed that computer processing of images produced by different companies requires using the different spatial filters usually. The performance of current version of the computer code is greater than one image per second for a THz image having more than 5000 pixels and 24 bit number representation. Processing of THz single image produces about 20 images simultaneously corresponding to various spatial filters. The computer code allows increasing the number of pixels for processed images without noticeable reduction of image quality. The performance of the computer code can be increased many times using parallel algorithms for processing the image. We develop original spatial filters which allow one to see objects with sizes less than 2 cm. The imagery is produced by passive THz imaging devices which captured the images of objects hidden under opaque clothes. For images with high noise we develop an approach which results in suppression of the noise after using the computer processing and we obtain the good quality image. With the aim of illustrating the efficiency of the developed approach we demonstrate the detection of the liquid explosive, ordinary explosive, knife, pistol, metal plate, CD, ceramics, chocolate and other objects hidden under opaque clothes. The results demonstrate the high efficiency of our approach for the detection of hidden objects and they are a very promising solution for the security problem.

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.

Recovering a hidden polarization by ghost polarimetry.

PubMed

Janassek, Patrick; Blumenstein, Sébastien; Elsäßer, Wolfgang

2018-02-15

By exploiting polarization correlations of light from a broadband fiber-based amplified spontaneous emission source we succeed in reconstructing a hidden polarization in a ghost polarimetry experiment in close analogy to ghost imaging and ghost spectroscopy. Thereby, an original linear polarization state in the object arm of a Mach-Zehnder interferometer configuration which has been camouflaged by a subsequent depolarizer is recovered by correlating it with light from a reference beam. The variation of a linear polarizer placed inside the reference beam results in a Malus law type second-order intensity correlation with high contrast, thus measuring a ghost polarigram.

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

Stanley Corrsin Award Lecture: Lagrangian Measurements in Turbulence: From Fundamentals to Applications

NASA Astrophysics Data System (ADS)

Bodenschatz, Eberhard

2014-11-01

In my talk I shall present results from particle tracking experiments in turbulence. After a short review of the history of the field, I shall summarize the most recent technological advances that range form low and high-density particle tracking to direct measurements of the Lagrangian evolution of vorticity. I shall embark on a journey that describes the discoveries made possible by this new technology in the last 15 years. I present results that challenge our understanding of turbulence and show how Lagrangian particle tracking can help us ask questions on turbulent flows that so far were hidden. I shall show how Lagrangian particle tracking may provide important insights into the reversibility of turbulent flows, on vorticity generation, the energy cascade and turbulent mixing. I shall describe the consequences of inertial particle transport on rain formation and end with an outlook on how Lagrangian particle tracking experiments on non-stationary flows in real-world situations may provide high quality data that can support real world engineering problems. I am very thankful for the support by Cornell University, the National Science Foundation, the Research Corporation, the Alfred P. Sloan Foundation, the Kavli Institute for Theoretical Physics, the German Research Foundation, the European Union and the Max Planck Society. I very gratefully acknowledge the excellent partnership with many colleagues in the field of fluid mechanics and turbulence.

Tracking children's mental states while solving algebra equations.

PubMed

Anderson, John R; Betts, Shawn; Ferris, Jennifer L; Fincham, Jon M

2012-11-01

Behavioral and function magnetic resonance imagery (fMRI) data were combined to infer the mental states of students as they interacted with an intelligent tutoring system. Sixteen children interacted with a computer tutor for solving linear equations over a six-day period (days 0-5), with days 1 and 5 occurring in an fMRI scanner. Hidden Markov model algorithms combined a model of student behavior with multi-voxel imaging pattern data to predict the mental states of students. We separately assessed the algorithms' ability to predict which step in a problem-solving sequence was performed and whether the step was performed correctly. For day 1, the data patterns of other students were used to predict the mental states of a target student. These predictions were improved on day 5 by adding information about the target student's behavioral and imaging data from day 1. Successful tracking of mental states depended on using the combination of a behavioral model and multi-voxel pattern analysis, illustrating the effectiveness of an integrated approach to tracking the cognition of individuals in real time as they perform complex tasks. Copyright © 2011 Wiley Periodicals, Inc.

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.

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.

Reconstruction of shapes of near symmetric and asymmetric objects

DOEpatents

Pizlo, Zygmunt; Sawada, Tadamasa; Li, Yunfeng

2013-03-26

A system processes 2D images of 2D or 3D objects, creating a model of the object that is consistent with the image and as veridical as the perception of the 2D image by humans. Vertices of the object that are hidden in the image are recovered by using planarity and symmetry constraints. The 3D shape is recovered by maximizing 3D compactness of the recovered object and minimizing its surface area. In some embodiments, these two criteria are weighted by using the geometric mean.

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.

Short range, ultra-wideband radar with high resolution swept range gate

DOEpatents

McEwan, T.E.

1998-05-26

A radar range finder and hidden object locator is based on ultra-wide band radar with a high resolution swept range gate. The device generates an equivalent time amplitude scan with a typical range of 4 inches to 20 feet, and an analog range resolution as limited by a jitter of on the order of 0.01 inches. A differential sampling receiver is employed to effectively eliminate ringing and other aberrations induced in the receiver by the near proximity of the transmit antenna, so a background subtraction is not needed, simplifying the circuitry while improving performance. Uses of the invention include a replacement of ultrasound devices for fluid level sensing, automotive radar, such as cruise control and parking assistance, hidden object location, such as stud and rebar finding. Also, this technology can be used when positioned over a highway lane to collect vehicle count and speed data for traffic control. 14 figs.

Short range, ultra-wideband radar with high resolution swept range gate

DOEpatents

McEwan, Thomas E.

1998-05-26

A radar range finder and hidden object locator is based on ultra-wide band radar with a high resolution swept range gate. The device generates an equivalent time amplitude scan with a typical range of 4 inches to 20 feet, and an analog range resolution as limited by a jitter of on the order of 0.01 inches. A differential sampling receiver is employed to effectively eliminate ringing and other aberrations induced in the receiver by the near proximity of the transmit antenna, so a background subtraction is not needed, simplifying the circuitry while improving performance. Uses of the invention include a replacement of ultrasound devices for fluid level sensing, automotive radar, such as cruise control and parking assistance, hidden object location, such as stud and rebar finding. Also, this technology can be used when positioned over a highway lane to collect vehicle count and speed data for traffic control.

Is wave-particle objectivity compatible with determinism and locality?

PubMed

Ionicioiu, Radu; Jennewein, Thomas; Mann, Robert B; Terno, Daniel R

2014-09-26

Wave-particle duality, superposition and entanglement are among the most counterintuitive features of quantum theory. Their clash with our classical expectations motivated hidden-variable (HV) theories. With the emergence of quantum technologies, we can test experimentally the predictions of quantum theory versus HV theories and put strong restrictions on their key assumptions. Here, we study an entanglement-assisted version of the quantum delayed-choice experiment and show that the extension of HV to the controlling devices only exacerbates the contradiction. We compare HV theories that satisfy the conditions of objectivity (a property of photons being either particles or waves, but not both), determinism and local independence of hidden variables with quantum mechanics. Any two of the above conditions are compatible with it. The conflict becomes manifest when all three conditions are imposed and persists for any non-zero value of entanglement. We propose an experiment to test our conclusions.

Is wave–particle objectivity compatible with determinism and locality?

PubMed Central

Ionicioiu, Radu; Jennewein, Thomas; Mann, Robert B.; Terno, Daniel R.

2014-01-01

Wave–particle duality, superposition and entanglement are among the most counterintuitive features of quantum theory. Their clash with our classical expectations motivated hidden-variable (HV) theories. With the emergence of quantum technologies, we can test experimentally the predictions of quantum theory versus HV theories and put strong restrictions on their key assumptions. Here, we study an entanglement-assisted version of the quantum delayed-choice experiment and show that the extension of HV to the controlling devices only exacerbates the contradiction. We compare HV theories that satisfy the conditions of objectivity (a property of photons being either particles or waves, but not both), determinism and local independence of hidden variables with quantum mechanics. Any two of the above conditions are compatible with it. The conflict becomes manifest when all three conditions are imposed and persists for any non-zero value of entanglement. We propose an experiment to test our conclusions. PMID:25256419

Linguistic Mediation of Children's Performance in a New Symbolic Understanding Task

ERIC Educational Resources Information Center

Homer, Bruce D.; Petroff, Natalya; Hayward, Elizabeth O.

2013-01-01

The effects of language on symbolic functioning were examined using the "boxes task," a new symbolic understanding task based on DeLoache's model task. Children ("N" = 32; ages 2;4--3;8) observed an object being hidden in a stack of four boxes and were then asked to retrieve a similar object in the same location from a set of…

Attentional Predictors of 5-Month-Olds' Performance on a Looking A-Not-B Task

ERIC Educational Resources Information Center

Marcovitch, Stuart; Clearfield, Melissa W.; Swingler, Margaret; Calkins, Susan D.; Bell, Martha Ann

2016-01-01

In the first year of life, the ability to search for hidden objects is an indicator of object permanence and, when multiple locations are involved, executive function (i.e. inhibition, cognitive flexibility and working memory). The current study was designed to examine attentional predictors of search in 5-month-old infants (as measured by the…

Time-lapse microscopy and image processing for stem cell research: modeling cell migration

NASA Astrophysics Data System (ADS)

Gustavsson, Tomas; Althoff, Karin; Degerman, Johan; Olsson, Torsten; Thoreson, Ann-Catrin; Thorlin, Thorleif; Eriksson, Peter

2003-05-01

This paper presents hardware and software procedures for automated cell tracking and migration modeling. A time-lapse microscopy system equipped with a computer controllable motorized stage was developed. The performance of this stage was improved by incorporating software algorithms for stage motion displacement compensation and auto focus. The microscope is suitable for in-vitro stem cell studies and allows for multiple cell culture image sequence acquisition. This enables comparative studies concerning rate of cell splits, average cell motion velocity, cell motion as a function of cell sample density and many more. Several cell segmentation procedures are described as well as a cell tracking algorithm. Statistical methods for describing cell migration patterns are presented. In particular, the Hidden Markov Model (HMM) was investigated. Results indicate that if the cell motion can be described as a non-stationary stochastic process, then the HMM can adequately model aspects of its dynamic behavior.

Adaptive output feedback control of uncertain nonlinear systems using single-hidden-layer neural networks.

PubMed

Hovakimyan, N; Nardi, F; Calise, A; Kim, Nakwan

2002-01-01

We consider adaptive output feedback control of uncertain nonlinear systems, in which both the dynamics and the dimension of the regulated system may be unknown. However, the relative degree of the regulated output is assumed to be known. Given a smooth reference trajectory, the problem is to design a controller that forces the system measurement to track it with bounded errors. The classical approach requires a state observer. Finding a good observer for an uncertain nonlinear system is not an obvious task. We argue that it is sufficient to build an observer for the output tracking error. Ultimate boundedness of the error signals is shown through Lyapunov's direct method. The theoretical results are illustrated in the design of a controller for a fourth-order nonlinear system of relative degree two and a high-bandwidth attitude command system for a model R-50 helicopter.

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.

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.

Adult-acquired hidden penis in obese patients: a critical survey of the literature.

PubMed

Cavayero, Chase T; Cooper, Meghan A; Harlin, Stephen L

2015-03-01

Hidden penis is anatomically defined by a lack of firm attachments of the skin and dartos fascia to the underlying Buck fascia. To critically appraise the research evidence that could support the most effective surgical techniques for adult-acquired hidden penis in obese patients. Studies investigating patients with a diagnosis of hidden penis were identified. Of these studies, only those with adult patients classified as overweight or obese (body mass index >25) were included in the review. Three reviewers examined the abstracts of the studies identified in the initial Medline search, and abstracts considered potentially relevant underwent full-text review. Studies that included patients with congenital, iatrogenic (eg, circumcision issues or aesthetic genital surgery), or traumatic causes of hidden penis were excluded. Studies that did not define the diagnostic criteria for hidden penis were excluded to minimize the risk of definition bias. The quality of evidence for each study was determined after considering the following sources of bias: method of allocation to study groups, data analysis, presence of baseline differences between groups, objectivity of outcome, and completeness of follow-up. Using these criteria, studies were then graded as high, moderate, or low in quality. Seven studies with a total of 119 patients met the inclusion criteria. All but 1 of the studies were nonrandomized. One study provided a clear presentation of results and appropriate statistical analysis. Six studies accounted for individual-based differences, and 1 study failed to account for baseline differences altogether. Four studies addressed follow-up. One study was of high quality, 2 were of moderate quality, and 4 were of low quality. Building a clinical practice guideline for the surgical management of hidden penis has proven difficult because of a lack of high-quality, statistically significant data in the research synthesis. The authors elucidate the challenges and epitomize the collective wisdom of surgeons who have investigated this problem and emphasize the need for rigorous evaluative studies. © 2015 The American Osteopathic Association.

Ultrasonic tracking of shear waves using a particle filter.

PubMed

Ingle, Atul N; Ma, Chi; Varghese, Tomy

2015-11-01

This paper discusses an application of particle filtering for estimating shear wave velocity in tissue using ultrasound elastography data. Shear wave velocity estimates are of significant clinical value as they help differentiate stiffer areas from softer areas which is an indicator of potential pathology. Radio-frequency ultrasound echo signals are used for tracking axial displacements and obtaining the time-to-peak displacement at different lateral locations. These time-to-peak data are usually very noisy and cannot be used directly for computing velocity. In this paper, the denoising problem is tackled using a hidden Markov model with the hidden states being the unknown (noiseless) time-to-peak values. A particle filter is then used for smoothing out the time-to-peak curve to obtain a fit that is optimal in a minimum mean squared error sense. Simulation results from synthetic data and finite element modeling suggest that the particle filter provides lower mean squared reconstruction error with smaller variance as compared to standard filtering methods, while preserving sharp boundary detail. Results from phantom experiments show that the shear wave velocity estimates in the stiff regions of the phantoms were within 20% of those obtained from a commercial ultrasound scanner and agree with estimates obtained using a standard method using least-squares fit. Estimates of area obtained from the particle filtered shear wave velocity maps were within 10% of those obtained from B-mode ultrasound images. The particle filtering approach can be used for producing visually appealing SWV reconstructions by effectively delineating various areas of the phantom with good image quality properties comparable to existing techniques.

A simple but powerful test of perseverative search in dogs and toddlers.

PubMed

Péter, András; Gergely, Anna; Topál, József; Miklósi, Ádám; Pongrácz, Péter

2015-01-01

Perseverative (A-not-B) errors during the search of a hidden object were recently described in both dogs and 10-month-old infants. It was found that ostensive cues indicating a communicative intent of the person who hides the object played a major role in eliciting perseverative errors in both species. However, the employed experimental set-up gave rise to several alternative explanations regarding the source of these errors. Here we present a simplified protocol that eliminates the ambiguities present in the original design. Using five consecutive object hiding events to one of two locations in a fixed order ("AABBA"), we tested adult companion dogs and human children (24 months old). The experimenter performed the hiding actions while giving ostensive cues in each trial and moved the target object to the given location in a straight line. Our results show that in the B trials, both 24-month-old children and dogs could not reliably find the hidden object, and their performance in the first B trials was significantly below that of any of the A trials. These results are the first to show that the tendency for perseverative errors in an ostensive-communicative context is a robust phenomenon among 2-year-old children and dogs, and not the by-product of a topographically elaborate hiding event.

Optical imaging of objects in turbid medium with ultrashort pulses

NASA Astrophysics Data System (ADS)

Wang, Chih-Yu; Sun, Chia-Wei; Yang, Chih Chung; Kiang, Yean-Woei; Lin, Chii-Wann

2000-07-01

Photons are seriously scattered when entering turbid medium; this the images of objects hidden in turbid medium can not be obtained by just collecting the transmitted photons. Early-arriving photons, which are also called ballistic or snake protons, are much less scattered when passing through turbid medium, and contains more image information than the late-arriving ones. Therefore, objects embedded in turbid medium can be imaged by gathering the ballistic and snake photons. In the present research we try to recover images of objects in turbid medium by simultaneously time-gate and polarization-gate to obtain the snake photons. An Argon-pumped Ti-Sapphire laser with 100fs pulses was employed as a light source. A streak camera with a 2ps temporal resolution was used to extract the ballistic and snake photons. Two pieces of lean swine meat, measured 4mmX3mm and 5xxX4mm, respectively, were placed in a 10cmX10cmX3cm acrylic tank, which was full of diluted milk. A pair of polarizer and an analyzer was used to extract the light that keeps polarization unchanged. The combination of time gating and polarization gating resulted in good images of objects hidden in turbid medium.

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

Hand, belt, pocket or bag: Practical activity tracking with mobile phones

PubMed Central

Antos, Stephen A.; Albert, Mark V.; Kording, Konrad P.

2013-01-01

For rehabilitation and diagnoses, an understanding of patient activities and movements is important. Modern smartphones have built in accelerometers which promise to enable quantifying minute-by-minute what patients do (e.g. walk or sit). Such a capability could inform recommendations of physical activities and improve medical diagnostics. However, a major problem is that during everyday life, we carry our phone in different ways, e.g. on our belt, in our pocket, in our hand, or in a bag. The recorded accelerations are not only affected by our activities but also by the phone’s location. Here we develop a method to solve this kind of problem, based on the intuition that activities change rarely, and phone locations change even less often. A Hidden Markov Model (HMM) tracks changes across both activities and locations, enabled by a static Support Vector Machine (SVM) classifier that probabilistically identifies activity-location pairs. We find that this approach improves tracking accuracy on healthy subjects as compared to a static classifier alone. The obtained method can be readily applied to patient populations. Our research enables the use of phones as activity tracking devices, without the need of previous approaches to instruct subjects to always carry the phone in the same location. PMID:24091138

Hand, belt, pocket or bag: Practical activity tracking with mobile phones.

PubMed

Antos, Stephen A; Albert, Mark V; Kording, Konrad P

2014-07-15

For rehabilitation and diagnoses, an understanding of patient activities and movements is important. Modern smartphones have built in accelerometers which promise to enable quantifying minute-by-minute what patients do (e.g. walk or sit). Such a capability could inform recommendations of physical activities and improve medical diagnostics. However, a major problem is that during everyday life, we carry our phone in different ways, e.g. on our belt, in our pocket, in our hand, or in a bag. The recorded accelerations are not only affected by our activities but also by the phone's location. Here we develop a method to solve this kind of problem, based on the intuition that activities change rarely, and phone locations change even less often. A hidden Markov model (HMM) tracks changes across both activities and locations, enabled by a static support vector machine (SVM) classifier that probabilistically identifies activity-location pairs. We find that this approach improves tracking accuracy on healthy subjects as compared to a static classifier alone. The obtained method can be readily applied to patient populations. Our research enables the use of phones as activity tracking devices, without the need of previous approaches to instruct subjects to always carry the phone in the same location. Copyright © 2013 Elsevier B.V. All rights reserved.

Intelligent complementary sliding-mode control for LUSMS-based X-Y-theta motion control stage.

PubMed

Lin, Faa-Jeng; Chen, Syuan-Yi; Shyu, Kuo-Kai; Liu, Yen-Hung

2010-07-01

An intelligent complementary sliding-mode control (ICSMC) system using a recurrent wavelet-based Elman neural network (RWENN) estimator is proposed in this study to control the mover position of a linear ultrasonic motors (LUSMs)-based X-Y-theta motion control stage for the tracking of various contours. By the addition of a complementary generalized error transformation, the complementary sliding-mode control (CSMC) can efficiently reduce the guaranteed ultimate bound of the tracking error by half compared with the slidingmode control (SMC) while using the saturation function. To estimate a lumped uncertainty on-line and replace the hitting control of the CSMC directly, the RWENN estimator is adopted in the proposed ICSMC system. In the RWENN, each hidden neuron employs a different wavelet function as an activation function to improve both the convergent precision and the convergent time compared with the conventional Elman neural network (ENN). The estimation laws of the RWENN are derived using the Lyapunov stability theorem to train the network parameters on-line. A robust compensator is also proposed to confront the uncertainties including approximation error, optimal parameter vectors, and higher-order terms in Taylor series. Finally, some experimental results of various contours tracking show that the tracking performance of the ICSMC system is significantly improved compared with the SMC and CSMC systems.

Von Neumann's impossibility proof: Mathematics in the service of rhetorics

NASA Astrophysics Data System (ADS)

Dieks, Dennis

2017-11-01

According to what has become a standard history of quantum mechanics, in 1932 von Neumann persuaded the physics community that hidden variables are impossible as a matter of principle, after which leading proponents of the Copenhagen interpretation put the situation to good use by arguing that the completeness of quantum mechanics was undeniable. This state of affairs lasted, so the story continues, until Bell in 1966 exposed von Neumann's proof as obviously wrong. The realization that von Neumann's proof was fallacious then rehabilitated hidden variables and made serious foundational research possible again. It is often added in recent accounts that von Neumann's error had been spotted almost immediately by Grete Hermann, but that her discovery was of no effect due to the dominant Copenhagen Zeitgeist. We shall attempt to tell a story that is more historically accurate and less ideologically charged. Most importantly, von Neumann never claimed to have shown the impossibility of hidden variables tout court, but argued that hidden-variable theories must possess a structure that deviates fundamentally from that of quantum mechanics. Both Hermann and Bell appear to have missed this point; moreover, both raised unjustified technical objections to the proof. Von Neumann's argument was basically that hidden-variables schemes must violate the ;quantum principle; that physical quantities are to be represented by operators in a Hilbert space. As a consequence, hidden-variables schemes, though possible in principle, necessarily exhibit a certain kind of contextuality. As we shall illustrate, early reactions to Bohm's theory are in agreement with this account. Leading physicists pointed out that Bohm's theory has the strange feature that pre-existing particle properties do not generally reveal themselves in measurements, in accordance with von Neumann's result. They did not conclude that the ;impossible was done; and that von Neumann had been shown wrong.

Deep neural network with weight sparsity control and pre-training extracts hierarchical features and enhances classification performance: Evidence from whole-brain resting-state functional connectivity patterns of schizophrenia

PubMed Central

Kim, Junghoe; Calhoun, Vince D.; Shim, Eunsoo; Lee, Jong-Hwan

2015-01-01

Functional connectivity (FC) patterns obtained from resting-state functional magnetic resonance imaging data are commonly employed to study neuropsychiatric conditions by using pattern classifiers such as the support vector machine (SVM). Meanwhile, a deep neural network (DNN) with multiple hidden layers has shown its ability to systematically extract lower-to-higher level information of image and speech data from lower-to-higher hidden layers, markedly enhancing classification accuracy. The objective of this study was to adopt the DNN for whole-brain resting-state FC pattern classification of schizophrenia (SZ) patients vs. healthy controls (HCs) and identification of aberrant FC patterns associated with SZ. We hypothesized that the lower-to-higher level features learned via the DNN would significantly enhance the classification accuracy, and proposed an adaptive learning algorithm to explicitly control the weight sparsity in each hidden layer via L1-norm regularization. Furthermore, the weights were initialized via stacked autoencoder based pre-training to further improve the classification performance. Classification accuracy was systematically evaluated as a function of (1) the number of hidden layers/nodes, (2) the use of L1-norm regularization, (3) the use of the pre-training, (4) the use of framewise displacement (FD) removal, and (5) the use of anatomical/functional parcellation. Using FC patterns from anatomically parcellated regions without FD removal, an error rate of 14.2% was achieved by employing three hidden layers and 50 hidden nodes with both L1-norm regularization and pre-training, which was substantially lower than the error rate from the SVM (22.3%). Moreover, the trained DNN weights (i.e., the learned features) were found to represent the hierarchical organization of aberrant FC patterns in SZ compared with HC. Specifically, pairs of nodes extracted from the lower hidden layer represented sparse FC patterns implicated in SZ, which was quantified by using kurtosis/modularity measures and features from the higher hidden layer showed holistic/global FC patterns differentiating SZ from HC. Our proposed schemes and reported findings attained by using the DNN classifier and whole-brain FC data suggest that such approaches show improved ability to learn hidden patterns in brain imaging data, which may be useful for developing diagnostic tools for SZ and other neuropsychiatric disorders and identifying associated aberrant FC patterns. PMID:25987366

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.

Embodied memory allows accurate and stable perception of hidden objects despite orientation change.

PubMed

Pan, Jing Samantha; Bingham, Ned; Bingham, Geoffrey P

2017-07-01

Rotating a scene in a frontoparallel plane (rolling) yields a change in orientation of constituent images. When using only information provided by static images to perceive a scene after orientation change, identification performance typically decreases (Rock & Heimer, 1957). However, rolling generates optic flow information that relates the discrete, static images (before and after the change) and forms an embodied memory that aids recognition. The embodied memory hypothesis predicts that upon detecting a continuous spatial transformation of image structure, or in other words, seeing the continuous rolling process and objects undergoing rolling observers should accurately perceive objects during and after motion. Thus, in this case, orientation change should not affect performance. We tested this hypothesis in three experiments and found that (a) using combined optic flow and image structure, participants identified locations of previously perceived but currently occluded targets with great accuracy and stability (Experiment 1); (b) using combined optic flow and image structure information, participants identified hidden targets equally well with or without 30° orientation changes (Experiment 2); and (c) when the rolling was unseen, identification of hidden targets after orientation change became worse (Experiment 3). Furthermore, when rolling was unseen, although target identification was better when participants were told about the orientation change than when they were not told, performance was still worse than when there was no orientation change. Therefore, combined optic flow and image structure information, not mere knowledge about the rolling, enables accurate and stable perception despite orientation change. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

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.

Seven-month-old infants chunk items in memory

PubMed Central

Moher, Mariko; Tuerk, Arin S.; Feigenson, Lisa

2012-01-01

Although working memory has a highly constrained capacity limit of 3 to 4 items, both adults and toddlers can increase the total amount of stored information by chunking object representations in memory. To examine the developmental origins of chunking, we used a violation-of-expectation procedure to ask whether 7-month-old infants, whose working memory capacity is still maturing, also can chunk items in memory. In Experiment 1 we found that in the absence of chunking cues, infants failed to remember 3 identical hidden objects. In Experiments 2 and 3 we found that infants successfully remembered 3 hidden objects when provided with overlapping spatial and featural chunking cues. In Experiment 4 we found that infants did not chunk when provided with either spatial or featural chunking cues alone. Finally, in Experiment 5 we found that infants also failed to chunk when spatial and featural cues specified different chunks (i.e., were pitted against each other). Taken together, these results suggest that chunking is available before working memory capacity has matured, but still may undergo important development over the first year of life. PMID:22575845

The Development of Knowledge of an External Retrieval Cue Strategy.

ERIC Educational Resources Information Center

Ritter, Kenneth

1978-01-01

Investigated preschool and third grade children's metamnemonic knowledge that in order to serve as an efficient retrieval cue of the location of a hidden object, an external marker sign must differentiate it from other locations. (JMB)

Program Enhances Drawings Of Three-Dimensional Objects

NASA Technical Reports Server (NTRS)

Hedgley, David R., Jr.

1992-01-01

SILHOUETTE is program for line drawings rendering any subset of polygons as silhouette. Program is improvement on, and replacement for, HIDDEN LINE COMPUTER CODE (ARC-11446). Offers combinations of silhouette and nonsilhouette specifications for arbitrary solid. Written in FORTRAN 77.

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.

Analysis of surface EMG baseline for detection of hidden muscle activity

NASA Astrophysics Data System (ADS)

Zhang, Xu; Zhou, Ping

2014-02-01

Objective. This study explored the feasibility of detecting hidden muscle activity in surface electromyogram (EMG) baseline. Approach. Power spectral density (PSD) analysis and multi-scale entropy (MSE) analysis were used. Both analyses were applied to computer simulations of surface EMG baseline with the presence (representing activity data) or absence (representing reference data) of hidden muscle activity, as well as surface electrode array EMG baseline recordings of healthy control and amyotrophic lateral sclerosis (ALS) subjects. Main results. Although the simulated reference data and the activity data yielded no distinguishable difference in the time domain, they demonstrated a significant difference in the frequency and signal complexity domains with the PSD and MSE analyses. For a comparison using pooled data, such a difference was also observed when the PSD and MSE analyses were applied to surface electrode array EMG baseline recordings of healthy control and ALS subjects, which demonstrated no distinguishable difference in the time domain. Compared with the PSD analysis, the MSE analysis appeared to be more sensitive for detecting the difference in surface EMG baselines between the two groups. Significance. The findings implied the presence of a hidden muscle activity in surface EMG baseline recordings from the ALS subjects. To promote the presented analysis as a useful diagnostic or investigatory tool, future studies are necessary to assess the pathophysiological nature or origins of the hidden muscle activity, as well as the baseline difference at the individual subject level.

Analysis of Surface EMG Baseline for Detection of Hidden Muscle Activity

PubMed Central

Zhang, Xu; Zhou, Ping

2014-01-01

Objective This study explored the feasibility of detecting hidden muscle activity in surface electromyogram (EMG) baseline. Approach Power spectral density (PSD) analysis and multi-scale entropy (MSE) analysis were used respectively. Both analyses were applied to computer simulations of surface EMG baseline with presence (representing activity data) or absence (representing reference data) of hidden muscle activity, as well as surface electrode array EMG baseline recordings of healthy control and amyotrophic lateral sclerosis (ALS) subjects. Main results Although the simulated reference data and the activity data yielded no distinguishable difference in the time domain, they demonstrated a significant difference in the frequency and signal complexity domains with the PSD and MSE analyses. For a comparison using pooled data, such a difference was also observed when the PSD and MSE analyses were applied to surface electrode array EMG baseline recordings of healthy control and ALS subjects, which demonstrated no distinguishable difference in the time domain. Compared with the PSD analysis, the MSE analysis appeared to be more sensitive for detecting the difference in surface EMG baselines between the two groups. Significance The findings implied presence of hidden muscle activity in surface EMG baseline recordings from the ALS subjects. To promote the presented analysis as a useful diagnostic or investigatory tool, future studies are necessary to assess the pathophysiological nature or origins of the hidden muscle activity, as well as the baseline difference at the individual subject level. PMID:24445526

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.

Escape from Metaignorance: How Children Develop an Understanding of Their Own Lack of Knowledge

ERIC Educational Resources Information Center

Rohwer, Michael; Kloo, Daniela; Perner, Josef

2012-01-01

Previous research yielded conflicting results about when children can accurately assess their epistemic states in different hiding tasks. In Experiment 1, ninety-two 3- to 7-year-olds were either shown which object was hidden inside a box, were totally ignorant about what it could be, or were presented with two objects one of which was being put…

Development of the Ability to Use Recall to Guide Action, as Indicated by Infants' Performance on AB.

ERIC Educational Resources Information Center

Diamond, Adele

1985-01-01

Twenty-five infants were tested every two weeks on the AB Object Permanence Task, from the time they first reached for a hidden object until they were 12 months old. Results indicate that the AB provides an index of the ability to carry out an intention based on stored information despite a conflicting habitual tendency. (Author/RH)

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.

Oscillatory activity in the infant brain reflects object maintenance.

PubMed

Kaufman, Jordy; Csibra, Gergely; Johnson, Mark H

2005-10-18

The apparent failure of infants to understand "object permanence" by reaching for hidden objects is perhaps the most striking and debated phenomenon in cognitive development. Of particular interest is the extent to which infants perceive and remember objects in a similar way to that of adults. Here we report two findings that clarify infant object processing. The first is that 6-mo-old infants are sensitive to visual cues to occlusion, particularly gradual deletion. The second finding is that oscillatory electroencephalogram activity recorded over right temporal channels is involved in object maintenance. This effect occurs only after disappearance in a manner consistent with occlusion and the object's continued existence.

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.

Miniaturised Gravity Sensors for Remote Gravity Surveys.

NASA Astrophysics Data System (ADS)

Middlemiss, R. P.; Bramsiepe, S. G.; Hough, J.; Paul, D. J.; Rowan, S.; Samarelli, A.; Hammond, G.

2016-12-01

Gravimetry lets us see the world from a completely different perspective. The ability to measure tiny variations in gravitational acceleration (g), allows one to see not just the Earth's gravitational pull, but the influence of smaller objects. The more accurate the gravimeter, the smaller the objects one can see. Gravimetry has applications in many different fields: from tracking magma moving under volcanoes before eruptions; to locating hidden tunnels. The top commercial gravimeters weigh tens of kg and cost at least $100,000, limiting the situations in which they can be used. By contrast, smart phones use a MEMS (microelectromechanical system) accelerometer that can measure the orientation of the device. These are not nearly sensitive or stable enough to be used for the gravimetry but they are cheap, light-weight and mass-producible. At Glasgow University we have developed a MEMS device with both the stability and sensitivity for useful gravimetric measurements. This was demonstrated by a measurement of the Earth tides - the first time this has been achieved with a MEMS sensor. A gravimeter of this size opens up the possiblility for new gravity imaging modalities. Thousands of gravimeters could be networked over a survey site, storing data on an SD card or communicating wirelessly to a remote location. These devices could also be small enough to be carried by a UAVs: airborne gravity surveys could be carried out at low altitude by mulitple UAVs, or UAVs could be used to deliver ground based gravimeters to remote or inaccessible locations.

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.

Critical object recognition in millimeter-wave images with robustness to rotation and scale.

PubMed

Mohammadzade, Hoda; Ghojogh, Benyamin; Faezi, Sina; Shabany, Mahdi

2017-06-01

Locating critical objects is crucial in various security applications and industries. For example, in security applications, such as in airports, these objects might be hidden or covered under shields or secret sheaths. Millimeter-wave images can be utilized to discover and recognize the critical objects out of the hidden cases without any health risk due to their non-ionizing features. However, millimeter-wave images usually have waves in and around the detected objects, making object recognition difficult. Thus, regular image processing and classification methods cannot be used for these images and additional pre-processings and classification methods should be introduced. This paper proposes a novel pre-processing method for canceling rotation and scale using principal component analysis. In addition, a two-layer classification method is introduced and utilized for recognition. Moreover, a large dataset of millimeter-wave images is collected and created for experiments. Experimental results show that a typical classification method such as support vector machines can recognize 45.5% of a type of critical objects at 34.2% false alarm rate (FAR), which is a drastically poor recognition. The same method within the proposed recognition framework achieves 92.9% recognition rate at 0.43% FAR, which indicates a highly significant improvement. The significant contribution of this work is to introduce a new method for analyzing millimeter-wave images based on machine vision and learning approaches, which is not yet widely noted in the field of millimeter-wave image analysis.

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.

Detection of Illicit Drugs with the EURITRACK System

NASA Astrophysics Data System (ADS)

Perot, B.; Carasco, C.; Valkovic, V.; Sudac, D.; Franulovic, A.

2009-03-01

The EURopean Illicit TRAfficking Countermeasures Kit (EURITRACK) inspection system has been developed within the 6th EU Framework Program to complement X-ray scanners in the detection of explosives and other illicit materials hidden in cargo containers. Gamma rays are produced inside the cargo materials by 14 MeV tagged neutron beams, which yields information about the chemical composition of the transported goods. In the beginning of year 2007, the EURITRACK system was implemented in the Seaport of Rijeka, Croatia, primarily to carry out a demonstration using real containers to conduct a series of detection tests. This article reports tests performed with real samples of illicit drugs hidden in a metallic cargo with an average density of 0.2 g/cm3. Heroin and cocaine have been distinguished from benign substances based on their chemical composition. Marijuana, which chemical composition is similar to benign materials, cannot be distinguished from common organic goods. However, the detection of an unexpected organic substance inside the metallic cargo indicates that a suspicious object has been hidden in the container.

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.

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.

Accurate permittivity measurements for microwave imaging via ultra-wideband removal of spurious reflectors.

PubMed

Pelletier, Mathew G; Viera, Joseph A; Wanjura, John; Holt, Greg

2010-01-01

The use of microwave imaging is becoming more prevalent for detection of interior hidden defects in manufactured and packaged materials. In applications for detection of hidden moisture, microwave tomography can be used to image the material and then perform an inverse calculation to derive an estimate of the variability of the hidden material, such internal moisture, thereby alerting personnel to damaging levels of the hidden moisture before material degradation occurs. One impediment to this type of imaging occurs with nearby objects create strong reflections that create destructive and constructive interference, at the receiver, as the material is conveyed past the imaging antenna array. In an effort to remove the influence of the reflectors, such as metal bale ties, research was conducted to develop an algorithm for removal of the influence of the local proximity reflectors from the microwave images. This research effort produced a technique, based upon the use of ultra-wideband signals, for the removal of spurious reflections created by local proximity reflectors. This improvement enables accurate microwave measurements of moisture in such products as cotton bales, as well as other physical properties such as density or material composition. The proposed algorithm was shown to reduce errors by a 4:1 ratio and is an enabling technology for imaging applications in the presence of metal bale ties.

Intelligent classifier for dynamic fault patterns based on hidden Markov model

NASA Astrophysics Data System (ADS)

Xu, Bo; Feng, Yuguang; Yu, Jinsong

2006-11-01

It's difficult to build precise mathematical models for complex engineering systems because of the complexity of the structure and dynamics characteristics. Intelligent fault diagnosis introduces artificial intelligence and works in a different way without building the analytical mathematical model of a diagnostic object, so it's a practical approach to solve diagnostic problems of complex systems. This paper presents an intelligent fault diagnosis method, an integrated fault-pattern classifier based on Hidden Markov Model (HMM). This classifier consists of dynamic time warping (DTW) algorithm, self-organizing feature mapping (SOFM) network and Hidden Markov Model. First, after dynamic observation vector in measuring space is processed by DTW, the error vector including the fault feature of being tested system is obtained. Then a SOFM network is used as a feature extractor and vector quantization processor. Finally, fault diagnosis is realized by fault patterns classifying with the Hidden Markov Model classifier. The importing of dynamic time warping solves the problem of feature extracting from dynamic process vectors of complex system such as aeroengine, and makes it come true to diagnose complex system by utilizing dynamic process information. Simulating experiments show that the diagnosis model is easy to extend, and the fault pattern classifier is efficient and is convenient to the detecting and diagnosing of new faults.

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.

Early Light Imaging for Biomedical Applications

DTIC Science & Technology

2000-07-01

such as prostate cancer, breast cancer, cervical cancer, glaucoma , macular degeneration, macular endema, and atherosclerosis plaques. Understanding of...harmonic- generation cross-correlation time gating", Opt. Lett., 16 1019-1021 (1991) 17. K. Yoo, Z. Zang, S. Ahmed , R. Alfano, "Imaging objects hidden

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.

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.

Homodyne impulse radar hidden object locator

DOEpatents

McEwan, T.E.

1996-04-30

An electromagnetic detector is designed to locate an object hidden behind a separator or a cavity within a solid object. The detector includes a PRF generator for generating 2 MHz pulses, a homodyne oscillator for generating a 2 kHz square wave, and for modulating the pulses from the PRF generator. A transmit antenna transmits the modulated pulses through the separator, and a receive antenna receives the signals reflected off the object. The receiver path of the detector includes a sample and hold circuit, an AC coupled amplifier which filters out DC bias level shifts in the sample and hold circuit, and a rectifier circuit connected to the homodyne oscillator and to the AC coupled amplifier, for synchronously rectifying the modulated pulses transmitted over the transmit antenna. The homodyne oscillator modulates the signal from the PRF generator with a continuous wave (CW) signal, and the AC coupled amplifier operates with a passband centered on that CW signal. The present detector can be used in several applications, including the detection of metallic and non-metallic objects, such as pipes, studs, joists, nails, rebars, conduits and electrical wiring, behind wood wall, ceiling, plywood, particle board, dense hardwood, masonry and cement structure. The detector is portable, light weight, simple to use, inexpensive, and has a low power emission which facilitates the compliance with Part 15 of the FCC rules. 15 figs.

Homodyne impulse radar hidden object locator

DOEpatents

McEwan, Thomas E.

1996-01-01

An electromagnetic detector is designed to locate an object hidden behind a separator or a cavity within a solid object. The detector includes a PRF generator for generating 2 MHz pulses, a homodyne oscillator for generating a 2 kHz square wave, and for modulating the pulses from the PRF generator. A transmit antenna transmits the modulated pulses through the separator, and a receive antenna receives the signals reflected off the object. The receiver path of the detector includes a sample and hold circuit, an AC coupled amplifier which filters out DC bias level shifts in the sample and hold circuit, and a rectifier circuit connected to the homodyne oscillator and to the AC coupled amplifier, for synchronously rectifying the modulated pulses transmitted over the transmit antenna. The homodyne oscillator modulates the signal from the PRF generator with a continuous wave (CW) signal, and the AC coupled amplifier operates with a passband centered on that CW signal. The present detector can be used in several applications, including the detection of metallic and non-metallic objects, such as pipes, studs, joists, nails, rebars, conduits and electrical wiring, behind wood wall, ceiling, plywood, particle board, dense hardwood, masonry and cement structure. The detector is portable, light weight, simple to use, inexpensive, and has a low power emission which facilitates the compliance with Part 15 of the FCC rules.

Consistency between subjectively and objectively measured hazard perception skills among young male drivers.

PubMed

Ābele, Līva; Haustein, Sonja; Møller, Mette; Martinussen, Laila M

2018-03-01

Young male drivers have lower hazard perception skills (HPS) than older and more experienced drivers and a tendency to overestimate their skills in hazardous situations. Both factors contribute to an over-representation in traffic accidents. Based on a sample of 63 drivers aged 18-24, this study compares the consistency of HPS measured by objective and subjective measures and the link between these measures is the key contribution of the study. Both visible and hidden hazards are included. Objective measures of HPS include responsiveness and eye movements while driving in a driving simulator. Subjective measures of HPS include self-reports derived based on the Hazard Perception Questionnaire (HPQ), Driving Skill Questionnaire (DSQ), and Brief Sensation Seeking Scale (BSSS). Results show that drivers who respond to the hazards on time, as compared to drivers who do not respond, have higher scores on subjective measures of HPS and higher driving skills in the visible but not in the hidden condition. Eye movement analysis confirms the difference and shows that response in time to hazards indicate higher HPS and young drivers are poor at detecting hidden hazards. Drivers with a response in time locate the hazard faster, have more fixations, but dwell less on the hazard. At the same time, those who do not respond have a later first fixation and fewer but longer fixations on the hazard. High sensation seeking drivers respond to visible hazards on time, suggesting that sensation seeking does not affect HPS negatively when the hazard is visible. To enhance the HPS among young drivers, the results of this study suggest that specific hazard perception training is relevant, especially for hazards that require more advanced HPS. Copyright © 2018 Elsevier Ltd. All rights reserved.

Real-time human versus animal classification using pyro-electric sensor array and Hidden Markov Model

NASA Astrophysics Data System (ADS)

Hossen, Jakir; Jacobs, Eddie L.; Chari, Srikant

2014-03-01

In this paper, we propose a real-time human versus animal classification technique using a pyro-electric sensor array and Hidden Markov Model. The technique starts with the variational energy functional level set segmentation technique to separate the object from background. After segmentation, we convert the segmented object to a signal by considering column-wise pixel values and then finding the wavelet coefficients of the signal. HMMs are trained to statistically model the wavelet features of individuals through an expectation-maximization learning process. Human versus animal classifications are made by evaluating a set of new wavelet feature data against the trained HMMs using the maximum-likelihood criterion. Human and animal data acquired-using a pyro-electric sensor in different terrains are used for performance evaluation of the algorithms. Failures of the computationally effective SURF feature based approach that we develop in our previous research are because of distorted images produced when the object runs very fast or if the temperature difference between target and background is not sufficient to accurately profile the object. We show that wavelet based HMMs work well for handling some of the distorted profiles in the data set. Further, HMM achieves improved classification rate over the SURF algorithm with almost the same computational time.

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.

Multiple object tracking using the shortest path faster association algorithm.

PubMed

Xi, Zhenghao; Liu, Heping; Liu, Huaping; Yang, Bin

2014-01-01

To solve the persistently multiple object tracking in cluttered environments, this paper presents a novel tracking association approach based on the shortest path faster algorithm. First, the multiple object tracking is formulated as an integer programming problem of the flow network. Then we relax the integer programming to a standard linear programming problem. Therefore, the global optimum can be quickly obtained using the shortest path faster algorithm. The proposed method avoids the difficulties of integer programming, and it has a lower worst-case complexity than competing methods but better robustness and tracking accuracy in complex environments. Simulation results show that the proposed algorithm takes less time than other state-of-the-art methods and can operate in real time.

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.

Multiple Object Tracking Using the Shortest Path Faster Association Algorithm

PubMed Central

Liu, Heping; Liu, Huaping; Yang, Bin

2014-01-01

To solve the persistently multiple object tracking in cluttered environments, this paper presents a novel tracking association approach based on the shortest path faster algorithm. First, the multiple object tracking is formulated as an integer programming problem of the flow network. Then we relax the integer programming to a standard linear programming problem. Therefore, the global optimum can be quickly obtained using the shortest path faster algorithm. The proposed method avoids the difficulties of integer programming, and it has a lower worst-case complexity than competing methods but better robustness and tracking accuracy in complex environments. Simulation results show that the proposed algorithm takes less time than other state-of-the-art methods and can operate in real time. PMID:25215322

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.

Efficient view based 3-D object retrieval using Hidden Markov Model

NASA Astrophysics Data System (ADS)

Jain, Yogendra Kumar; Singh, Roshan Kumar

2013-12-01

Recent research effort has been dedicated to view based 3-D object retrieval, because of highly discriminative property of 3-D object and has multi view representation. The state-of-art method is highly depending on their own camera array setting for capturing views of 3-D object and use complex Zernike descriptor, HAC for representative view selection which limit their practical application and make it inefficient for retrieval. Therefore, an efficient and effective algorithm is required for 3-D Object Retrieval. In order to move toward a general framework for efficient 3-D object retrieval which is independent of camera array setting and avoidance of representative view selection, we propose an Efficient View Based 3-D Object Retrieval (EVBOR) method using Hidden Markov Model (HMM). In this framework, each object is represented by independent set of view, which means views are captured from any direction without any camera array restriction. In this, views are clustered (including query view) to generate the view cluster, which is then used to build the query model with HMM. In our proposed method, HMM is used in twofold: in the training (i.e. HMM estimate) and in the retrieval (i.e. HMM decode). The query model is trained by using these view clusters. The EVBOR query model is worked on the basis of query model combining with HMM. The proposed approach remove statically camera array setting for view capturing and can be apply for any 3-D object database to retrieve 3-D object efficiently and effectively. Experimental results demonstrate that the proposed scheme has shown better performance than existing methods. [Figure not available: see fulltext.

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.

Deep neural network with weight sparsity control and pre-training extracts hierarchical features and enhances classification performance: Evidence from whole-brain resting-state functional connectivity patterns of schizophrenia.

PubMed

Kim, Junghoe; Calhoun, Vince D; Shim, Eunsoo; Lee, Jong-Hwan

2016-01-01

Functional connectivity (FC) patterns obtained from resting-state functional magnetic resonance imaging data are commonly employed to study neuropsychiatric conditions by using pattern classifiers such as the support vector machine (SVM). Meanwhile, a deep neural network (DNN) with multiple hidden layers has shown its ability to systematically extract lower-to-higher level information of image and speech data from lower-to-higher hidden layers, markedly enhancing classification accuracy. The objective of this study was to adopt the DNN for whole-brain resting-state FC pattern classification of schizophrenia (SZ) patients vs. healthy controls (HCs) and identification of aberrant FC patterns associated with SZ. We hypothesized that the lower-to-higher level features learned via the DNN would significantly enhance the classification accuracy, and proposed an adaptive learning algorithm to explicitly control the weight sparsity in each hidden layer via L1-norm regularization. Furthermore, the weights were initialized via stacked autoencoder based pre-training to further improve the classification performance. Classification accuracy was systematically evaluated as a function of (1) the number of hidden layers/nodes, (2) the use of L1-norm regularization, (3) the use of the pre-training, (4) the use of framewise displacement (FD) removal, and (5) the use of anatomical/functional parcellation. Using FC patterns from anatomically parcellated regions without FD removal, an error rate of 14.2% was achieved by employing three hidden layers and 50 hidden nodes with both L1-norm regularization and pre-training, which was substantially lower than the error rate from the SVM (22.3%). Moreover, the trained DNN weights (i.e., the learned features) were found to represent the hierarchical organization of aberrant FC patterns in SZ compared with HC. Specifically, pairs of nodes extracted from the lower hidden layer represented sparse FC patterns implicated in SZ, which was quantified by using kurtosis/modularity measures and features from the higher hidden layer showed holistic/global FC patterns differentiating SZ from HC. Our proposed schemes and reported findings attained by using the DNN classifier and whole-brain FC data suggest that such approaches show improved ability to learn hidden patterns in brain imaging data, which may be useful for developing diagnostic tools for SZ and other neuropsychiatric disorders and identifying associated aberrant FC patterns. Copyright © 2015 Elsevier Inc. All rights reserved.

Ultrasonic tracking of shear waves using a particle filter

PubMed Central

Ingle, Atul N.; Ma, Chi; Varghese, Tomy

2015-01-01

Purpose: This paper discusses an application of particle filtering for estimating shear wave velocity in tissue using ultrasound elastography data. Shear wave velocity estimates are of significant clinical value as they help differentiate stiffer areas from softer areas which is an indicator of potential pathology. Methods: Radio-frequency ultrasound echo signals are used for tracking axial displacements and obtaining the time-to-peak displacement at different lateral locations. These time-to-peak data are usually very noisy and cannot be used directly for computing velocity. In this paper, the denoising problem is tackled using a hidden Markov model with the hidden states being the unknown (noiseless) time-to-peak values. A particle filter is then used for smoothing out the time-to-peak curve to obtain a fit that is optimal in a minimum mean squared error sense. Results: Simulation results from synthetic data and finite element modeling suggest that the particle filter provides lower mean squared reconstruction error with smaller variance as compared to standard filtering methods, while preserving sharp boundary detail. Results from phantom experiments show that the shear wave velocity estimates in the stiff regions of the phantoms were within 20% of those obtained from a commercial ultrasound scanner and agree with estimates obtained using a standard method using least-squares fit. Estimates of area obtained from the particle filtered shear wave velocity maps were within 10% of those obtained from B-mode ultrasound images. Conclusions: The particle filtering approach can be used for producing visually appealing SWV reconstructions by effectively delineating various areas of the phantom with good image quality properties comparable to existing techniques. PMID:26520761

Simulation of intrafraction motion and overall geometric accuracy of a frameless intracranial radiosurgery process

PubMed Central

Walker, Luke; Chinnaiyan, Prakash; Forster, Kenneth

2008-01-01

We conducted a comprehensive evaluation of the clinical accuracy of an image‐guided frameless intracranial radiosurgery system. All links in the process chain were tested. Using healthy volunteers, we evaluated a novel method to prospectively quantify the range of target motion for optimal determination of the planning target volume (PTV) margin. The overall system isocentric accuracy was tested using a rigid anthropomorphic phantom containing a hidden target. Intrafraction motion was simulated in 5 healthy volunteers. Reinforced head‐and‐shoulders thermoplastic masks were used for immobilization. The subjects were placed in a treatment position for 15 minutes (the maximum expected time between repeated isocenter localizations) and the six‐degrees‐of‐freedom target displacements were recorded with high frequency by tracking infrared markers. The markers were placed on a customized piece of thermoplastic secured to the head independently of the immobilization mask. Additional data were collected with the subjects holding their breath, talking, and deliberately moving. As compared with fiducial matching, the automatic registration algorithm did not introduce clinically significant errors (<0.3 mm difference). The hidden target test confirmed overall system isocentric accuracy of ≤1 mm (total three‐dimensional displacement). The subjects exhibited various patterns and ranges of head motion during the mock treatment. The total displacement vector encompassing 95% of the positional points varied from 0.4 mm to 2.9 mm. Pre‐planning motion simulation with optical tracking was tested on volunteers and appears promising for determination of patient‐specific PTV margins. Further patient study is necessary and is planned. In the meantime, system accuracy is sufficient for confident clinical use with 3 mm PTV margins. PACS number: 87.53.Ly

Two-year-olds use adults' but not peers' points.

PubMed

Kachel, Gregor; Moore, Richard; Tomasello, Michael

2018-03-12

In the current study, 24- to 27-month-old children (N = 37) used pointing gestures in a cooperative object choice task with either peer or adult partners. When indicating the location of a hidden toy, children pointed equally accurately for adult and peer partners but more often for adult partners. When choosing from one of three hiding places, children used adults' pointing to find a hidden toy significantly more often than they used peers'. In interaction with peers, children's choice behavior was at chance level. These results suggest that toddlers ascribe informative value to adults' but not peers' pointing gestures, and highlight the role of children's social expectations in their communicative development. © 2018 John Wiley & Sons Ltd.

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.

Review of terahertz technology development at INO

NASA Astrophysics Data System (ADS)

Dufour, Denis; Marchese, Linda; Terroux, Marc; Oulachgar, Hassane; Généreux, Francis; Doucet, Michel; Mercier, Luc; Tremblay, Bruno; Alain, Christine; Beaupré, Patrick; Blanchard, Nathalie; Bolduc, Martin; Chevalier, Claude; D'Amato, Dominic; Desroches, Yan; Duchesne, François; Gagnon, Lucie; Ilias, Samir; Jerominek, Hubert; Lagacé, François; Lambert, Julie; Lamontagne, Frédéric; Le Noc, Loïc; Martel, Anne; Pancrati, Ovidiu; Paultre, Jacques-Edmond; Pope, Tim; Provençal, Francis; Topart, Patrice; Vachon, Carl; Verreault, Sonia; Bergeron, Alain

2015-10-01

Over the past decade, INO has leveraged its expertise in the development of uncooled microbolometer detectors for infrared imaging to produce terahertz (THz) imaging systems. By modifying its microbolometer-based focal plane arrays to enhance absorption in the THz bands and by developing custom THz imaging lenses, INO has developed a leading-edge THz imaging system, the IRXCAM-THz-384 camera, capable of exploring novel applications in the emerging field of terahertz imaging and sensing. Using appropriate THz sources, results show that the IRXCAM-THz-384 camera is able to image a variety of concealed objects of interest for applications such as non-destructive testing and weapons detections. By using a longer wavelength (94 GHz) source, it is also capable of sensing the signatures of various objects hidden behind a drywall panel. This article, written as a review of THz research at INO over the past decade, describes the technical components that form the IRXCAM-THz-384 camera and the experimental setup used for active THz imaging. Image results for concealed weapons detection experiments, an exploration of wavelength choice on image quality, and the detection of hidden objects behind drywall are also presented.

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.

Automated recognition system for power quality disturbances

NASA Astrophysics Data System (ADS)

Abdelgalil, Tarek

The application of deregulation policies in electric power systems has resulted in the necessity to quantify the quality of electric power. This fact highlights the need for a new monitoring strategy which is capable of tracking, detecting, classifying power quality disturbances, and then identifying the source of the disturbance. The objective of this work is to design an efficient and reliable power quality monitoring strategy that uses the advances in signal processing and pattern recognition to overcome the deficiencies that exist in power quality monitoring devices. The purposed monitoring strategy has two stages. The first stage is to detect, track, and classify any power quality violation by the use of on-line measurements. In the second stage, the source of the classified power quality disturbance must be identified. In the first stage, an adaptive linear combiner is used to detect power quality disturbances. Then, the Teager Energy Operator and Hilbert Transform are utilized for power quality event tracking. After the Fourier, Wavelet, and Walsh Transforms are employed for the feature extraction, two approaches are then exploited to classify the different power quality disturbances. The first approach depends on comparing the disturbance to be classified with a stored set of signatures for different power quality disturbances. The comparison is developed by using Hidden Markov Models and Dynamic Time Warping. The second approach depends on employing an inductive inference to generate the classification rules directly from the data. In the second stage of the new monitoring strategy, only the problem of identifying the location of the switched capacitor which initiates the transients is investigated. The Total Least Square-Estimation of Signal Parameters via Rotational Invariance Technique is adopted to estimate the amplitudes and frequencies of the various modes contained in the voltage signal measured at the facility entrance. After extracting the amplitudes and frequencies, an Artificial Neural Network is employed to identify the switched capacitor by using amplitudes and frequencies extracted from the transient signal. The new algorithms for detecting, tracking, and classifying power quality disturbances demonstrate the potential for further development of a fully automated recognition system for the assessment of power quality. This is possible because the implementation of the proposed algorithms for the power quality monitoring device becomes a straight forward process by modifying the device software.

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.

A simulation system to hide dynamic objects selectively at visible wavelengths

NASA Astrophysics Data System (ADS)

Cheng, Qiluan; Zhang, Shu; Ding, Chizhu; Tan, Zuojun; Wang, Guo Ping

2018-04-01

Currently, invisibility devices are increasingly approaching practical application requirements, such as using easily obtained materials for construction and hiding dynamic objects. Here, using phase retrieval and computer-generated holography techniques, we design an invisibility system in simulation to produce a phase-conjugation signal that changes with the dynamic object to hide it. This system is highly selective for the hidden objects, i.e., it only hides the target object and has no effect on the others. Such function may provide our invisibility system with great potential in special fields, such as biology and military applications for living and dynamic target recognition, selective camouflaging, and others.

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.

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

76 FR 11569 - Hazardous Materials: Enhanced Enforcement Authority Procedures

Federal Register 2010, 2011, 2012, 2013, 2014

2011-03-02

... harm Americans would move those materials as hidden shipments. Accordingly, although the presence of... statutory authority is not limited to undeclared shipments. On a broader scale, Section 7118 promotes the... commerce, when those employees have an objectively reasonable and articulable belief that the shipment may...

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…

An extensive air shower trigger station for the Muon Portal detector

NASA Astrophysics Data System (ADS)

Riggi, F.; Blancato, A. A.; La Rocca, P.; Riggi, S.; Santagati, G.

2014-11-01

The Muon Portal project ( [1]; Riggi et al., 2013 [2,5,7]; Lo Presti et al., 2012 [3]; La Rocca et al., 2014 [4]; Bandieramonte et al., 2013 [6]; Pugliatti et al., 2014 [8]) aims at the construction of a large area detector to reconstruct cosmic muon tracks above and below a container, to search for hidden high-Z materials inside its volume by the muon tomography technique. Due to its sensitive area (about 18 m2), with four XY detection planes, and its good tracking capabilities, the prototype under construction, which should be operational around mid-2015, also allows different studies in cosmic ray physics, including the detection of muon bundles. For such purpose, a trigger station based on three scintillation detectors operating in coincidence close to the main muon tracker has been built. This paper describes the design and preliminary results of the trigger station, together with the physics capabilities of the overall setup.

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.

Visual one-shot learning as an 'anti-camouflage device': a novel morphing paradigm.

PubMed

Ishikawa, Tetsuo; Mogi, Ken

2011-09-01

Once people perceive what is in the hidden figure such as Dallenbach's cow and Dalmatian, they seldom seem to come back to the previous state when they were ignorant of the answer. This special type of learning process can be accomplished in a short time, with the effect of learning lasting for a long time (visual one-shot learning). Although it is an intriguing cognitive phenomenon, the lack of the control of difficulty of stimuli presented has been a problem in research. Here we propose a novel paradigm to create new hidden figures systematically by using a morphing technique. Through gradual changes from a blurred and binarized two-tone image to a blurred grayscale image of the original photograph including objects in a natural scene, spontaneous one-shot learning can occur at a certain stage of morphing when a sufficient amount of information is restored to the degraded image. A negative correlation between confidence levels and reaction times is observed, giving support to the fluency theory of one-shot learning. The correlation between confidence ratings and correct recognition rates indicates that participants had an accurate introspective ability (metacognition). The learning effect could be tested later by verifying whether or not the target object was recognized quicker in the second exposure. The present method opens a way for a systematic production of "good" hidden figures, which can be used to demystify the nature of visual one-shot learning.

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.

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

Olfactory ability and object memory in three mouse models of varying body weight, metabolic hormones, and adiposity

PubMed Central

Tucker, Kristal R.; Godbey, Steven J.; Thiebaud, Nicolas; Fadool, Debra Ann

2012-01-01

Physiological and nutritional state can modify sensory ability and perception through hormone signaling. Obesity and related metabolic disorders present a chronic imbalance in hormonal signaling that could impact sensory systems. In the olfactory system, external chemical cues are transduced into electrical signals to encode information. It is becoming evident that this system can also detect internal chemical cues in the form of molecules of energy homeostasis and endocrine hormones, whereby neurons of the olfactory system are modulated to change animal behavior towards olfactory cues. We hypothesized that chronic imbalance in hormonal signaling and energy homeostasis due to obesity would thereby disrupt olfactory behaviors in mice. To test this idea, we utilized three mouse models of varying body weight, metabolic hormones, and visceral adiposity – 1) C57BL6/J mice maintained on a condensed-milk based, moderately high-fat diet (MHF) of 32% fat for 6 months as the diet-induced obesity model, 2) an obesity-resistant, lean line of mice due to a gene-targeted deletion of a voltage-dependent potassium channel (Kv1.3-null), and 3) a genetic model of obesity as a result of a gene-targeted deletion of the melanocortin 4 receptor (MC4R-null). Diet-induced obese (DIO) mice failed to find fatty-scented hidden peanut butter cracker, based solely on olfactory cues, any faster than an unscented hidden marble, initially suggesting general anosmia. However, when these DIO mice were challenged to find a sweet-scented hidden chocolate candy, they had no difficulty. Furthermore, DIO mice were able to discriminate between fatty acids that differ by a single double bond and are components of the MHF diet (linoleic and oleic acid) in a habituation-dishabituation paradigm. Obesity-resistant, Kv1.3-null mice exhibited no change in scented object retrieval when placed on the MHF-diet, nor did they perform differently than wild-type mice in parallel habituation-dishabituation paradigms of fatty food-related odor components. Genetically obese, MC4R-null mice successfully found hidden scented objects, but did so more slowly than lean, wild-type mice, in an object-dependent fashion. In habituation-dishabituation trials of general odorants, MC4R-null mice failed to discriminate a novel odor, but were able to distinguish two fatty acids. Object memory recognition tests for short- and long-term memory retention demonstrated that maintenance on the MHF diet did not modify ability to perform these tasks independent of whether mice became obese or were resistant to weight gain (Kv1.3-null), however, the genetically predisposed obese mice (MC4R-null) failed the long-term object memory recognition performed at 24 hours. These results demonstrate that even though both the DIO mice and genetically predisposed obese mice are obese, they vary in the degree to which they exhibit behavioral deficits in odor detection, odor discrimination, and long-term memory. PMID:22995978

[Prevalence of dental fluorosis and consumption of hidden fluoride in school children in the municipality of Nezahualcóyotl].

PubMed

Chacón, Luis Fernando Galicia; López, María Lilia Adriana Juárez; Frechero, Nelly Molina

2009-01-01

Dental fluorosis is a dental tissue disease, characterized by hypomineralization resulting from excess fluoride reaching the developing tooth. In Mexico in recent years, the prevalence of fluorosis has increased by the exposure to different fluoridated sources such as those found in soft drinks and beverages. Our objective was to determine the prevalence of dental fluorosis among school children living in Nezahualcoyotl, state of Mexico and identify associated risk factors. We conducted a cross-sectional study among 455 children aged 6-13 years who had been assessed by a previously standardized observer following WHO criteria. We administered The Community Fluorosis index (FCI) and a survey that analyzed the exposure to fluorides hidden in carbonated drinks, juices, bottled water, tea and the use of fluoride toothpastes. The prevalence of dental fluorosis was 73.4%. Very mild and mild fluorosis were the more common levels. The Community Fluorosis index (ICF) was 1.18 +/- 0.80. School children living at Nezahualcoyotl that answered they did drink hidden fluorides > 0.71 ppm thought bottled beverages were more of a risk to develop dental fluorosis (RM 1,554, 95% CI 1.016-2.378, p<0.05). Dental fluorosis results from fluoride intake by different sources, however our study, consumption of fluoride hidden in soft and bottled drinks showed a significant correlation with observed fluorosis.

Accurate Permittivity Measurements for Microwave Imaging via Ultra-Wideband Removal of Spurious Reflectors

PubMed Central

Pelletier, Mathew G.; Viera, Joseph A.; Wanjura, John; Holt, Greg

2010-01-01

The use of microwave imaging is becoming more prevalent for detection of interior hidden defects in manufactured and packaged materials. In applications for detection of hidden moisture, microwave tomography can be used to image the material and then perform an inverse calculation to derive an estimate of the variability of the hidden material, such internal moisture, thereby alerting personnel to damaging levels of the hidden moisture before material degradation occurs. One impediment to this type of imaging occurs with nearby objects create strong reflections that create destructive and constructive interference, at the receiver, as the material is conveyed past the imaging antenna array. In an effort to remove the influence of the reflectors, such as metal bale ties, research was conducted to develop an algorithm for removal of the influence of the local proximity reflectors from the microwave images. This research effort produced a technique, based upon the use of ultra-wideband signals, for the removal of spurious reflections created by local proximity reflectors. This improvement enables accurate microwave measurements of moisture in such products as cotton bales, as well as other physical properties such as density or material composition. The proposed algorithm was shown to reduce errors by a 4:1 ratio and is an enabling technology for imaging applications in the presence of metal bale ties. PMID:22163668

Semantic Stability is More Pleasurable in Unstable Episodic Contexts. On the Relevance of Perceptual Challenge in Art Appreciation.

PubMed

Muth, Claudia; Raab, Marius H; Carbon, Claus-Christian

2016-01-01

Research in the field of psychological aesthetics points to the appeal of stimuli which defy easy recognition by being "semantically unstable" but which still allow for creating meaning-in the ongoing process of elaborative perception or as an end product of the entire process. Such effects were reported for hidden images (Muth and Carbon, 2013) as well as Cubist artworks concealing detectable-although fragmented-objects (Muth et al., 2013). To test the stability of the relationship between semantic determinacy and appreciation across different episodic contexts, 30 volunteers evaluated an artistic movie continuously on visual determinacy or liking via the Continuous Evaluation Procedure (CEP, Muth et al., 2015b). The movie consisted of five episodes with emerging Gestalts. In the first between-participants condition, the hidden Gestalts in the movie episodes were of increasing determinacy, in the second condition, the episodes showed decreasing determinacies of hidden Gestalts. In the increasing-determinacy group, visual determinacy was rated higher and showed better predictive quality for liking than in the decreasing-determinacy group. Furthermore, when the movie started with low visual determinacy of hidden Gestalts, unexpectedly strong increases in visual determinacy had a bigger effect on liking than in the condition which allowed for weaker Gestalt recognition after having started with highly determinate Gestalts. The resulting pattern calls for consideration of the episodic context when examining art appreciation.

Force, torque, linear momentum, and angular momentum in classical electr odynamics

NASA Astrophysics Data System (ADS)

Mansuripur, Masud

2017-10-01

The classical theory of electrodynamics is built upon Maxwell's equations and the concepts of electromagnetic (EM) field, force, energy, and momentum, which are intimately tied together by Poynting's theorem and by the Lorentz force law. Whereas Maxwell's equations relate the fields to their material sources, Poynting's theorem governs the flow of EM energy and its exchange between fields and material media, while the Lorentz law regulates the back-and-forth transfer of momentum between the media and the fields. An alternative force law, first proposed by Einstein and Laub, exists that is consistent with Maxwell's equations and complies with the conservation laws as well as with the requirements of special relativity. While the Lorentz law requires the introduction of hidden energy and hidden momentum in situations where an electric field acts on a magnetized medium, the Einstein-Laub (E-L) formulation of EM force and torque does not invoke hidden entities under such circumstances. Moreover, total force/torque exerted by EM fields on any given object turns out to be independent of whether the density of force/torque is evaluated using the law of Lorentz or that of Einstein and Laub. Hidden entities aside, the two formulations differ only in their predicted force and torque distributions inside matter. Such differences in distribution are occasionally measurable, and could serve as a guide in deciding which formulation, if either, corresponds to physical reality.

Signals of New Physics in the Underlying Event

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

Harnik, Roni; /Stanford U., ITP /SLAC; Wizansky, Tommer

2010-06-11

LHC searches for new physics focus on combinations of hard physics objects. In this work we propose a qualitatively different soft signal for new physics at the LHC - the 'anomalous underlying event'. Every hard LHC event will be accompanied by a soft underlying event due to QCD and pile-up effects. Though it is often used for QCD and monte carlo studies, here we propose the incorporation of an underlying event analysis in some searches for new physics. An excess of anomalous underlying events may be a smoking-gun signal for particular new physics scenarios such as 'quirks' or 'hidden valleys'more » in which large amounts of energy may be emitted by a large multiplicity of soft particles. We discuss possible search strategies for such soft diffuse signals in the tracking system and calorimetry of the LHC experiments. We present a detailed study of the calorimetric signal in a concrete example, a simple quirk model motivated by folded supersymmetry. In these models the production and radiative decay of highly excited quirk bound states leads to an 'antenna pattern' of soft unclustered energy. Using a dedicated simulation of a toy detector and a 'CMB-like' multipole analysis we compare the signal to the expected backgrounds.« less

Rotational displacement skills in rhesus macaques (Macaca mulatta).

PubMed

Hughes, Kelly D; Santos, Laurie R

2012-11-01

Rotational displacement tasks, in which participants must track an object at a hiding location within an array while the array rotates, exhibit a puzzling developmental pattern in humans. Human children take an unusually long time to master this task and tend to solve rotational problems through the use of nongeometric features or landmarks as opposed to other kinds of spatial cues. We investigated whether these developmental characteristics are unique to humans by testing rotational displacement skills in a monkey species, the rhesus macaque (Macaca mulatta), using a looking-time method. Monkeys first saw food hidden in two differently colored boxes within an array. The array was then rotated 180° and the boxes reopened to reveal the food in an expected or unexpected location. Our first two experiments explored the developmental time-course of performance on this rotational displacement task. We found that adult macaques looked longer at the unexpected event, but such performance was not mirrored in younger-aged macaques. In a third study, we systematically varied featural information and visible access to the array to investigate which strategies adult macaques used in solving rotational displacements. Our results show that adult macaques need both sets of information to solve the task. Taken together, these results suggest both similarities and differences in mechanisms by which human and nonhuman primates develop this spatial skill.

Infrared near-Earth-object survey modeling for observatories interior to the Earth's orbit

NASA Astrophysics Data System (ADS)

Buie, M.

2014-07-01

The search for and dynamical characterization of the near-Earth population of objects (NEOs) has been a busy topic for surveys for many years. Most of the work thus far has been from ground-based optical surveys such as the Catalina Sky Survey and LINEAR. These surveys have essentially reached a complete inventory of objects down to 1 km diameter and have shown that the known objects do not pose any significant impact threat. Smaller objects are correspondingly smaller threats but there are more of them and fewer of them have so far been discovered. The next generation of surveys is looking to extend their reach down to much smaller sizes. From an impact risk perspective, those objects as small as 30--40 m are still of interest (similar in size to the Tunguska bolide). Smaller objects than this are largely of interest from a space resource or in-situ analysis efforts. A recent mission concept promoted by the B612 Foundation and Ball Aerospace calls for an infrared survey telescope in a Venus-like orbit, known as the Sentinel Mission. This wide-field facility has been designed to complete the inventory down to a 140 m diameter while also providing substantial constraints on the NEO population down to a Tunguska-sized object. I have been working to develop a suite of tools to provide survey modeling for this class of survey telescope. The purpose of the tool is to uncover hidden complexities that govern mission design and operation while also working to quantitatively understand the orbit quality provided on its catalog of objects without additional followup assets. The baseline mission design calls for a 6.5 year survey lifetime. This survey model is a statistically based tool for establishing completeness as a function of object size and survey duration. Effects modeled include the ability to adjust the field-of-regard (includes all pointing restrictions), field-of-view, focal plane array fill factor, and the observatory orbit. Consequences tracked include time-tagged detection times from which orbit quality can be derived and efficiency by dynamical class. The dominant noise term in the simulations comes from the noise in the background flux caused by thermal emission from zodiacal dust. The model used is sufficient for the study of reasonably low-inclination spacecraft orbits such as are being considered. Results to date are based on the 2002 Bottke NEA orbit-distribution model. The system can work with any orbit-distribution model and with any size-frequency distribution. This tool also serves to quantify the amount of data that will also be collected on main-belt objects by simply testing against the known catalog of bodies. The orbit quality work clearly shows the benefit of a self-followup survey such as Sentinel. Most objects discovered will be seen in multiple observing epochs and the resulting orbits will preclude losing track of them for decades to come (or longer). All of the ephemeris calculations, including investigation of orbit determination quality, are done with the OpenOrb software package. The presentation for this meeting will be based on results of modeling the Sentinel Mission and other similar variants. The focus will be on evaluating the survey completion for different dynamical classes as well as for different sized objects. Within the fidelity of such statistically-based models, the planned Sentinel observatory is well capable of a huge step forward in the efforts to build a complete catalog of all objects that could pose future harm to planet Earth.

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.

The Lobster Tale: An Exercise in Critical Thinking

ERIC Educational Resources Information Center

Stepanovich, Paul L.

2009-01-01

Professors in management and business are encouraged to incorporate critical thinking as an objective in their courses. "The Lobster Tale" provides an opportunity to engage students in various levels of critical thinking, ranging from a relatively superficial reading to an examination of the deeper, often hidden issues. Using the foundations of…

Literature in Language Lessons

ERIC Educational Resources Information Center

Zaiser, Richard

2018-01-01

Teaching modern foreign languages is not all about communicative skills. It is also about testing functional abilities. While we still pay lip service to the creed of communicative language teaching, we have adopted test formats and teaching styles that follow a hidden agenda: the production of human capital. The main objective of teaching is…

Impulse radar studfinder

DOEpatents

McEwan, Thomas E.

1995-01-01

An impulse radar studfinder propagates electromagnetic pulses and detects reflected pulses from a fixed range. Unmodulated pulses, about 200 ps wide, are emitted. A large number of reflected pulses are sampled and averaged. Background reflections are subtracted. Reflections from wall studs or other hidden objects are detected and displayed using light emitting diodes.

Innovations in the Teaching of Behavioral Sciences in the Preclinical Curriculum

ERIC Educational Resources Information Center

Mack, Kevin

2005-01-01

Objective: In problem-based learning curricula, cases are usually clustered into identified themes or organ systems. While this method of aggregating cases presents clear advantages in terms of resource alignment and student focus, an alternative "hidden cluster" approach provides rich opportunities for content integration. Method: The author…

Impulse radar studfinder

DOEpatents

McEwan, T.E.

1995-10-10

An impulse radar studfinder propagates electromagnetic pulses and detects reflected pulses from a fixed range. Unmodulated pulses, about 200 ps wide, are emitted. A large number of reflected pulses are sampled and averaged. Background reflections are subtracted. Reflections from wall studs or other hidden objects are detected and displayed using light emitting diodes. 9 figs.

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

Religion, Spirituality, and the Hidden Curriculum: Medical Student and Faculty Reflections.

PubMed

Balboni, Michael J; Bandini, Julia; Mitchell, Christine; Epstein-Peterson, Zachary D; Amobi, Ada; Cahill, Jonathan; Enzinger, Andrea C; Peteet, John; Balboni, Tracy

2015-10-01

Religion and spirituality play an important role in physicians' medical practice, but little research has examined their influence within the socialization of medical trainees and the hidden curriculum. The objective is to explore the role of religion and spirituality as they intersect with aspects of medicine's hidden curriculum. Semiscripted, one-on-one interviews and focus groups (n = 33 respondents) were conducted to assess Harvard Medical School student and faculty experiences of religion/spirituality and the professionalization process during medical training. Using grounded theory, theme extraction was performed with interdisciplinary input (medicine, sociology, and theology), yielding a high inter-rater reliability score (kappa = 0.75). Three domains emerged where religion and spirituality appear as a factor in medical training. First, religion/spirituality may present unique challenges and benefits in relation to the hidden curriculum. Religious/spiritual respondents more often reported to struggle with issues of personal identity, increased self-doubt, and perceived medical knowledge inadequacy. However, religious/spiritual participants less often described relationship conflicts within the medical team, work-life imbalance, and emotional stress arising from patient suffering. Second, religion/spirituality may influence coping strategies during encounters with patient suffering. Religious/spiritual trainees described using prayer, faith, and compassion as means for coping whereas nonreligious/nonspiritual trainees discussed compartmentalization and emotional repression. Third, levels of religion/spirituality appear to fluctuate in relation to medical training, with many trainees experiencing an increase in religiousness/spirituality during training. Religion/spirituality has a largely unstudied but possibly influential role in medical student socialization. Future study is needed to characterize its function within the hidden curriculum. Copyright © 2015 American Academy of Hospice and Palliative Medicine. Published by Elsevier Inc. All rights reserved.

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.

Time-resolved non-sequential ray-tracing modelling of non-line-of-sight picosecond pulse LIDAR

NASA Astrophysics Data System (ADS)

Sroka, Adam; Chan, Susan; Warburton, Ryan; Gariepy, Genevieve; Henderson, Robert; Leach, Jonathan; Faccio, Daniele; Lee, Stephen T.

2016-05-01

The ability to detect motion and to track a moving object that is hidden around a corner or behind a wall provides a crucial advantage when physically going around the obstacle is impossible or dangerous. One recently demonstrated approach to achieving this goal makes use of non-line-of-sight picosecond pulse laser ranging. This approach has recently become interesting due to the availability of single-photon avalanche diode (SPAD) receivers with picosecond time resolution. We present a time-resolved non-sequential ray-tracing model and its application to indirect line-of-sight detection of moving targets. The model makes use of the Zemax optical design programme's capabilities in stray light analysis where it traces large numbers of rays through multiple random scattering events in a 3D non-sequential environment. Our model then reconstructs the generated multi-segment ray paths and adds temporal analysis. Validation of this model against experimental results is shown. We then exercise the model to explore the limits placed on system design by available laser sources and detectors. In particular we detail the requirements on the laser's pulse energy, duration and repetition rate, and on the receiver's temporal response and sensitivity. These are discussed in terms of the resulting implications for achievable range, resolution and measurement time while retaining eye-safety with this technique. Finally, the model is used to examine potential extensions to the experimental system that may allow for increased localisation of the position of the detected moving object, such as the inclusion of multiple detectors and/or multiple emitters.

Artificial emotion triggered stochastic behavior transitions with motivational gain effects for multi-objective robot tasks

NASA Astrophysics Data System (ADS)

Dağlarli, Evren; Temeltaş, Hakan

2007-04-01

This paper presents artificial emotional system based autonomous robot control architecture. Hidden Markov model developed as mathematical background for stochastic emotional and behavior transitions. Motivation module of architecture considered as behavioral gain effect generator for achieving multi-objective robot tasks. According to emotional and behavioral state transition probabilities, artificial emotions determine sequences of behaviors. Also motivational gain effects of proposed architecture can be observed on the executing behaviors during simulation.

Techniques of noninvasive optical tomographic imaging

NASA Astrophysics Data System (ADS)

Rosen, Joseph; Abookasis, David; Gokhler, Mark

2006-01-01

Recently invented methods of optical tomographic imaging through scattering and absorbing media are presented. In one method, the three-dimensional structure of an object hidden between two biological tissues is recovered from many noisy speckle pictures obtained on the output of a multi-channeled optical imaging system. Objects are recovered from many speckled images observed by a digital camera through two stereoscopic microlens arrays. Each microlens in each array generates a speckle image of the object buried between the layers. In the computer each image is Fourier transformed jointly with an image of the speckled point-like source captured under the same conditions. A set of the squared magnitudes of the Fourier-transformed pictures is accumulated to form a single average picture. This final picture is again Fourier transformed, resulting in the three-dimensional reconstruction of the hidden object. In the other method, the effect of spatial longitudinal coherence is used for imaging through an absorbing layer with different thickness, or different index of refraction, along the layer. The technique is based on synthesis of multiple peak spatial degree of coherence. This degree of coherence enables us to scan simultaneously different sample points on different altitudes, and thus decreases the acquisition time. The same multi peak degree of coherence is also used for imaging through the absorbing layer. Our entire experiments are performed with a quasi-monochromatic light source. Therefore problems of dispersion and inhomogeneous absorption are avoided.

Searching for Extragalactic Sources in the VISTA Variables in the Vía Láctea Survey

NASA Astrophysics Data System (ADS)

Baravalle, Laura D.; Alonso, M. Victoria; Nilo Castellón, José Luis; Beamín, Juan Carlos; Minniti, Dante

2018-01-01

We search for extragalactic sources in the VISTA Variables in the Vía Láctea survey that are hidden by the Galaxy. Herein, we describe our photometric procedure to find and characterize extragalactic objects using a combination of SExtractor and PSFEx. It was applied in two tiles of the survey: d010 and d115, without previous extragalactic IR detections, in order to obtain photometric parameters of the detected sources. The adopted criteria to define extragalactic candidates include CLASSSTAR< 0.3; 1.0 < R1/2< 5.0 arcsec; 2.1 < C < 5 and Φ > 0.002 and the colors: 0.5 < (J–K s ) < 2.0 mag; 0.0 < (J–H) < 1.0 mag; 0.0 < (H–K s ) < 2.0 mag and (J–H) + 0.9 (H–K s ) > 0.44 mag. We detected 345 and 185 extragalactic candidates in the d010 and d115 tiles, respectively. All of them were visually inspected and confirmed to be galaxies. In general, they are small and more circular objects, due to the near-IR sensitivity to select more compact objects with higher surface brightness. The procedure will be used to identify extragalactic objects in other tiles of the VVV disk, which will allow us to study the distribution of galaxies and filaments hidden by the Milky Way.

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

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.

Endoscopic pulsed digital holography for 3D measurements

NASA Astrophysics Data System (ADS)

Saucedo, A. Tonatiuh; Mendoza Santoyo, Fernando; de La Torre-Ibarra, Manuel; Pedrini, Giancarlo; Osten, Wolfgang

2006-02-01

A rigid endoscope and three different object illumination source positions are used in pulsed digital holography to measure the three orthogonal displacement components from hidden areas of a harmonically vibrating metallic cylinder. In order to obtain simultaneous 3D information from the optical set up, it is necessary to match the optical paths of each of the reference object beam pairs, but to incoherently mismatch the three reference object beam pairs, such that three pulsed digital holograms are incoherently recorded within a single frame of the CCD sensor. The phase difference is obtained using the Fourier method and by subtracting two digital holograms captured for two different object positions.

Water Ice in 2060 Chiron and Its Implications for Centaurs and Kuiper Belt Objects.

PubMed

Luu; Jewitt; Trujillo

2000-03-10

We report the detection of water ice in the Centaur 2060 Chiron, based on near-infrared spectra (1.0-2.5 µm) taken with the 3.8 m United Kingdom Infrared Telescope and the 10 m Keck Telescope. The appearance of this ice is correlated with the recent decline in Chiron's cometary activity: the decrease in the coma cross section allows previously hidden solid-state surface features to be seen. We predict that water ice is ubiquitous among Centaurs and Kuiper Belt objects, but its surface coverage varies from object to object and thus determines its detectability and the occurrence of cometary activity.

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.

Detection of hidden objects using a real-time 3-D millimeter-wave imaging system

NASA Astrophysics Data System (ADS)

Rozban, Daniel; Aharon, Avihai; Levanon, Assaf; Abramovich, Amir; Yitzhaky, Yitzhak; Kopeika, N. S.

2014-10-01

Millimeter (mm)and sub-mm wavelengths or terahertz (THz) band have several properties that motivate their use in imaging for security applications such as recognition of hidden objects, dangerous materials, aerosols, imaging through walls as in hostage situations, and also in bad weather conditions. There is no known ionization hazard for biological tissue, and atmospheric degradation of THz radiation is relatively low for practical imaging distances. We recently developed a new technology for the detection of THz radiation. This technology is based on very inexpensive plasma neon indicator lamps, also known as Glow Discharge Detector (GDD), that can be used as very sensitive THz radiation detectors. Using them, we designed and constructed a Focal Plane Array (FPA) and obtained recognizable2-dimensional THz images of both dielectric and metallic objects. Using THz wave it is shown here that even concealed weapons made of dielectric material can be detected. An example is an image of a knife concealed inside a leather bag and also under heavy clothing. Three-dimensional imaging using radar methods can enhance those images since it can allow the isolation of the concealed objects from the body and environmental clutter such as nearby furniture or other people. The GDDs enable direct heterodyning between the electric field of the target signal and the reference signal eliminating the requirement for expensive mixers, sources, and Low Noise Amplifiers (LNAs).We expanded the ability of the FPA so that we are able to obtain recognizable 2-dimensional THz images in real time. We show here that the THz detection of objects in three dimensions, using FMCW principles is also applicable in real time. This imaging system is also shown here to be capable of imaging objects from distances allowing standoff detection of suspicious objects and humans from large distances.

Fixation Biases towards the Index Finger in Almost-Natural Grasping

PubMed Central

Voudouris, Dimitris; Smeets, Jeroen B. J.; Brenner, Eli

2016-01-01

We use visual information to guide our grasping movements. When grasping an object with a precision grip, the two digits need to reach two different positions more or less simultaneously, but the eyes can only be directed to one position at a time. Several studies that have examined eye movements in grasping have found that people tend to direct their gaze near where their index finger will contact the object. Here we aimed at better understanding why people do so by asking participants to lift an object off a horizontal surface. They were to grasp the object with a precision grip while movements of their hand, eye and head were recorded. We confirmed that people tend to look closer to positions that a digit needs to reach more accurately. Moreover, we show that where they look as they reach for the object depends on where they were looking before, presumably because they try to minimize the time during which the eyes are moving so fast that no new visual information is acquired. Most importantly, we confirmed that people have a bias to direct gaze towards the index finger’s contact point rather than towards that of the thumb. In our study, this cannot be explained by the index finger contacting the object before the thumb. Instead, it appears to be because the index finger moves to a position that is hidden behind the object that is grasped, probably making this the place at which one is most likely to encounter unexpected problems that would benefit from visual guidance. However, this cannot explain the bias that was found in previous studies, where neither contact point was hidden, so it cannot be the only explanation for the bias. PMID:26766551

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.

Estimation of effective connectivity via data-driven neural modeling

PubMed Central

Freestone, Dean R.; Karoly, Philippa J.; Nešić, Dragan; Aram, Parham; Cook, Mark J.; Grayden, David B.

2014-01-01

This research introduces a new method for functional brain imaging via a process of model inversion. By estimating parameters of a computational model, we are able to track effective connectivity and mean membrane potential dynamics that cannot be directly measured using electrophysiological measurements alone. The ability to track the hidden aspects of neurophysiology will have a profound impact on the way we understand and treat epilepsy. For example, under the assumption the model captures the key features of the cortical circuits of interest, the framework will provide insights into seizure initiation and termination on a patient-specific basis. It will enable investigation into the effect a particular drug has on specific neural populations and connectivity structures using minimally invasive measurements. The method is based on approximating brain networks using an interconnected neural population model. The neural population model is based on a neural mass model that describes the functional activity of the brain, capturing the mesoscopic biophysics and anatomical structure. The model is made subject-specific by estimating the strength of intra-cortical connections within a region and inter-cortical connections between regions using a novel Kalman filtering method. We demonstrate through simulation how the framework can be used to track the mechanisms involved in seizure initiation and termination. PMID:25506315

Human body contour data based activity recognition.

PubMed

Myagmarbayar, Nergui; Yuki, Yoshida; Imamoglu, Nevrez; Gonzalez, Jose; Otake, Mihoko; Yu, Wenwei

2013-01-01

This research work is aimed to develop autonomous bio-monitoring mobile robots, which are capable of tracking and measuring patients' motions, recognizing the patients' behavior based on observation data, and providing calling for medical personnel in emergency situations in home environment. The robots to be developed will bring about cost-effective, safe and easier at-home rehabilitation to most motor-function impaired patients (MIPs). In our previous research, a full framework was established towards this research goal. In this research, we aimed at improving the human activity recognition by using contour data of the tracked human subject extracted from the depth images as the signal source, instead of the lower limb joint angle data used in the previous research, which are more likely to be affected by the motion of the robot and human subjects. Several geometric parameters, such as, the ratio of height to weight of the tracked human subject, and distance (pixels) between centroid points of upper and lower parts of human body, were calculated from the contour data, and used as the features for the activity recognition. A Hidden Markov Model (HMM) is employed to classify different human activities from the features. Experimental results showed that the human activity recognition could be achieved with a high correct rate.

Tracking the visual focus of attention for a varying number of wandering people.

PubMed

Smith, Kevin; Ba, Sileye O; Odobez, Jean-Marc; Gatica-Perez, Daniel

2008-07-01

We define and address the problem of finding the visual focus of attention for a varying number of wandering people (VFOA-W), determining where the people's movement is unconstrained. VFOA-W estimation is a new and important problem with mplications for behavior understanding and cognitive science, as well as real-world applications. One such application, which we present in this article, monitors the attention passers-by pay to an outdoor advertisement. Our approach to the VFOA-W problem proposes a multi-person tracking solution based on a dynamic Bayesian network that simultaneously infers the (variable) number of people in a scene, their body locations, their head locations, and their head pose. For efficient inference in the resulting large variable-dimensional state-space we propose a Reversible Jump Markov Chain Monte Carlo (RJMCMC) sampling scheme, as well as a novel global observation model which determines the number of people in the scene and localizes them. We propose a Gaussian Mixture Model (GMM) and Hidden Markov Model (HMM)-based VFOA-W model which use head pose and location information to determine people's focus state. Our models are evaluated for tracking performance and ability to recognize people looking at an outdoor advertisement, with results indicating good performance on sequences where a moderate number of people pass in front of an advertisement.

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

Characterization of the guinea pig animal model and subsequent comparison of the behavioral effects of selective dopaminergic drugs and methamphetamine

PubMed Central

Lee, Kiera-Nicole; Pellom, Samuel T.; Oliver, Ericka; Chirwa, Sanika

2014-01-01

Though not commonly used in behavior tests guinea pigs may offer subtle behavior repertoires that better mimic human activity and warrant study. To test this, 31 Hartley guinea pigs (male, 200–250 g) were evaluated in PhenoTyper cages using the video-tracking EthoVision XT 7.0 software. Results showed that guinea pigs spent more time in the hidden zone (small box in corner of cage) than the food/water zone, or arena zone. Guinea pigs exhibited thigmotaxis (a wall following strategy) and were active throughout the light and dark phases. Eating and drinking occurred throughout the light and dark phases. An injection of 0.25 mg/kg SCH23390, the dopamine D1 receptors (D1R) antagonist, produced significant decreases in time spent in the hidden zone. There were insignificant changes in time spent in the hidden zone for guinea pigs treated with 7.5 mg SKF38393 (D1R agonist), 1.0 mg/kg sulpiride (D2R antagonist), and 1.0 or 10.0 mg/kg methamphetamine. Locomotor activity profiles were unchanged after injections of saline, SKF38393, SCH23390 and sulpiride. By contrast, a single injection or repeated administration for 7 days of low-dose methamphetamine induced transient hyperactivity but this declined to baseline levels over the 22-hour observation period. Guinea pigs treated with high-dose methamphetamine displayed sustained hyperactivity and travelled significantly greater distances over the circadian cycle. Subsequent 7-day treatment with high-dose methamphetamine induced motor sensitization and significant increases in total distances moved relative to single drug injections or saline controls. These results highlight the versatility and unique features of the guinea pig for studying brain-behavior interactions. PMID:24436154

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.

The Maimonides Portrait: An Appraisal of One of the World’s Most Famous Pictures

PubMed Central

Schwartz, Yitzhack

2011-01-01

Surprisingly, an utterly imaginative “portrait” has become synonymous with Maimonides forever. How and when did this particular portrait become associated with Maimonides? This and many other intriguing questions regarding this portrait are systematically addressed, and its origins, possible inspiration, and hidden objectives are revealed. PMID:23908810

User's Guide for SKETCH

NASA Technical Reports Server (NTRS)

Hedgley, David R., Jr.

2000-01-01

A user's guide for the computer program SKETCH is presented on this disk. SKETCH solves a popular problem in computer graphics-the removal of hidden lines from images of solid objects. Examples and illustrations are included in the guide. Also included is the SKETCH program, so a user can incorporate the information into a particular software system.

Teaching Evidence-Based Psychiatry: Integrating and Aligning the Formal and Hidden Curricula

ERIC Educational Resources Information Center

Agrawal, Sacha; Szatmari, Peter; Hanson, Mark

2008-01-01

Objective: The authors argue that adopting evidence-based psychiatry will require a paradigm shift in the training of psychiatry residents, and offer some suggestions for how this transformation might be achieved. Methods: The authors review the growing literature that addresses how best to teach evidence-based medicine and highlight several…

29 CFR 1917.43 - Powered industrial trucks.

Code of Federal Regulations, 2011 CFR

2011-07-01

... engagement hidden from the operator, a means shall be provided to enable the operator to determine that the... employees. Employees may be elevated by fork lift trucks only when a platform is secured to the lifting...) if tools or other objects could fall on employees below. (iii) An employee shall be at the truck's...

29 CFR 1917.43 - Powered industrial trucks.

Code of Federal Regulations, 2010 CFR

2010-07-01

... engagement hidden from the operator, a means shall be provided to enable the operator to determine that the... employees. Employees may be elevated by fork lift trucks only when a platform is secured to the lifting...) if tools or other objects could fall on employees below. (iii) An employee shall be at the truck's...

Job Objectives for M60A1A0S Tank Gunnery

DTIC Science & Technology

1976-04-01

aeasuring the costs of an existing, perhaps ineffective prograa — hidden costs, such «• equipment deaage attributable to ■lause, personal Injury, or for...but for review and deliberation by policy aakers : Do the proposed standards reflect what i» known by eneay gunnery capabllitlee-’ And what

In the Minds of OSCE Examiners: Uncovering Hidden Assumptions

ERIC Educational Resources Information Center

Chahine, Saad; Holmes, Bruce; Kowalewski, Zbigniew

2016-01-01

The Objective Structured Clinical Exam (OSCE) is a widely used method of assessment in medical education. Rater cognition has become an important area of inquiry in the medical education assessment literature generally, and in the OSCE literature specifically, because of concerns about potential compromises of validity. In this study, a novel…

Hidden Rules, Secret Agendas: Challenges Facing Contemporary Women Doctoral Students.

ERIC Educational Resources Information Center

Smith, Bobbi

Studies indicate that, although enrollment and degree production by women doctoral students have increased, fewer women than men complete doctorates and women generally take longer than men to finish, in spite of the fact that women demonstrate equal if not superior performance levels on virtually every objective measure. Women who complete the…

Processes Underlying Young Children's Spatial Orientation during Movement.

ERIC Educational Resources Information Center

Bremner, J. Gavin; And Others

1994-01-01

Tested children 18 months to 4 years for their ability to relocate a hidden object after self-produced movement around an array of 4 locations. Children encountered no specific difficulty in coordinating dimensions, or they solved the task without recourse to such a system. They also appeared to change strategy when the problem requires more…

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.

Search protocols for hidden forensic objects beneath floors and within walls.

PubMed

Ruffell, Alastair; Pringle, Jamie K; Forbes, Shari

2014-04-01

The burial of objects (human remains, explosives, weapons) below or behind concrete, brick, plaster or tiling may be associated with serious crime and are difficult locations to search. These are quite common forensic search scenarios but little has been published on them to-date. Most documented discoveries are accidental or from suspect/witness testimony. The problem in locating such hidden objects means a random or chance-based approach is not advisable. A preliminary strategy is presented here, based on previous studies, augmented by primary research where new technology or applications are required. This blend allows a rudimentary search workflow, from remote desktop study, to non-destructive investigation through to recommendations as to how the above may inform excavation, demonstrated here with a case study from a homicide investigation. Published case studies on the search for human remains demonstrate the problems encountered when trying to find and recover sealed-in and sealed-over locations. Established methods include desktop study, photography, geophysics and search dogs: these are integrated with new technology (LiDAR and laser scanning; photographic rectification; close-quarter aerial imagery; ground-penetrating radar on walls and gamma-ray/neutron activation radiography) to propose this possible search strategy. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Noninvasive, near-field terahertz imaging of hidden objects using a single-pixel detector.

PubMed

Stantchev, Rayko Ivanov; Sun, Baoqing; Hornett, Sam M; Hobson, Peter A; Gibson, Graham M; Padgett, Miles J; Hendry, Euan

2016-06-01

Terahertz (THz) imaging can see through otherwise opaque materials. However, because of the long wavelengths of THz radiation (λ = 400 μm at 0.75 THz), far-field THz imaging techniques suffer from low resolution compared to visible wavelengths. We demonstrate noninvasive, near-field THz imaging with subwavelength resolution. We project a time-varying, intense (>100 μJ/cm(2)) optical pattern onto a silicon wafer, which spatially modulates the transmission of synchronous pulse of THz radiation. An unknown object is placed on the hidden side of the silicon, and the far-field THz transmission corresponding to each mask is recorded by a single-element detector. Knowledge of the patterns and of the corresponding detector signal are combined to give an image of the object. Using this technique, we image a printed circuit board on the underside of a 115-μm-thick silicon wafer with ~100-μm (λ/4) resolution. With subwavelength resolution and the inherent sensitivity to local conductivity, it is possible to detect fissures in the circuitry wiring of a few micrometers in size. THz imaging systems of this type will have other uses too, where noninvasive measurement or imaging of concealed structures is necessary, such as in semiconductor manufacturing or in ex vivo bioimaging.

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

Uncovering the wisdom hidden between the lines: the Collaborative Reflexive Deliberative Approach

PubMed Central

Crabtree, Benjamin F; Miller, William L; Gunn, Jane M; Hogg, William E; Scott, Cathie M; Levesque, Jean-Frederic; Harris, Mark F; Chase, Sabrina M; Advocat, Jenny R; Halma, Lisa M; Russell, Grant M

2018-01-01

Abstract Background Meta-analysis and meta-synthesis have been developed to synthesize results across published studies; however, they are still largely grounded in what is already published, missing the tacit ‘between the lines’ knowledge generated during many research projects that are not intrinsic to the main objectives of studies. Objective To develop a novel approach to expand and deepen meta-syntheses using researchers’ experience, tacit knowledge and relevant unpublished materials. Methods We established new collaborations among primary health care researchers from different contexts based on common interests in reforming primary care service delivery and a diversity of perspectives. Over 2 years, the team met face-to-face and via tele- and video-conferences to employ the Collaborative Reflexive Deliberative Approach (CRDA) to discuss and reflect on published and unpublished results from participants’ studies to identify new patterns and insights. Results CRDA focuses on uncovering critical insights, interpretations hidden within multiple research contexts. For the process to work, careful attention must be paid to ensure sufficient diversity among participants while also having people who are able to collaborate effectively. Ensuring there are enough studies for contextual variation also matters. It is necessary to balance rigorous facilitation techniques with the creation of safe space for diverse contributions. Conclusions The CRDA requires large commitments of investigator time, the expense of convening facilitated retreats, considerable coordination, and strong leadership. The process creates an environment where interactions among diverse participants can illuminate hidden information within the contexts of studies, effectively enhancing theory development and generating new research questions and strategies. PMID:29069335

Monsters and babies from the first/IRAS survey

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

Van Bruegel, W J M

Radio continuum emission at cm wavelengths is relatively little affected by extinction. When combined with far-infrared (FIR) surveys this provides for a convenient and unbiased method to select (radio-loud) AGN and starbursts deeply embedded in gas and dust-rich galaxies. Such radio-selected FIR samples are useful for detailed investigations of the complex relationships between (radio) galaxy and starburst activity, and to determine whether ULIRGs are powered by hidden quasars (monsters) or young stars (babies). We present the results of a large program to obtain identifications and spectra of radio-sleected, optically faint IRAS/FSC objects using the FIRST/VLA 20 cm survey (Becker, Whitemore » and Helfand 1995). These objects are all radio-'quiet' in the sense that their radio power/FIR luminosities follow the well-known radio/FIR relationship for star forming galaxies. We compare these results to a previous study by our group of a sample of radio-'loud' IRAS/FSC ULIRGs selected from the Texas 365 MHz survey (Douglas et al. 1996). Many of these objects also show evidence for dominant, A-type stellar populations, as well as high ionization lines usually associated with AGN. These radio-loud ULIRGs have properties intermediate between those of starbursts and quasars, suggesting a possibile evolutionary connection. Deep Keck spectroscopic observations of three ULIRGs from these samples are presented, including high signal-to-noise spectropolarimetry. The polarimetry observations failed to show evidence of a hidden quasar in polarized (scattered) light in the two systems in which the stellar light was dominated by A-type stars. Although observations of a larger sample would be needed to allow a general conclusion, our current data suggest that a large fraction of ULIRGs may be powered by luminous starbursts, not by hidden, luminous AGN (quasars). While we used radio-selected FIR sources to search for evidence of a causal AGN/starburst connection, we conclude our presentation with a dramatic example of an AGN/starburst object from an entirely unrelated quasar survey selected at the opposite, blue end of the spectrum.« less

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.

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.

Differential sensitivity to human communication in dogs, wolves, and human infants.

PubMed

Topál, József; Gergely, György; Erdohegyi, Agnes; Csibra, Gergely; Miklósi, Adám

2009-09-04

Ten-month-old infants persistently search for a hidden object at its initial hiding place even after observing it being hidden at another location. Recent evidence suggests that communicative cues from the experimenter contribute to the emergence of this perseverative search error. We replicated these results with dogs (Canis familiaris), who also commit more search errors in ostensive-communicative (in 75% of the total trials) than in noncommunicative (39%) or nonsocial (17%) hiding contexts. However, comparative investigations suggest that communicative signals serve different functions for dogs and infants, whereas human-reared wolves (Canis lupus) do not show doglike context-dependent differences of search errors. We propose that shared sensitivity to human communicative signals stems from convergent social evolution of the Homo and the Canis genera.

FAST TRACK COMMUNICATION: \\ {P}\\ {T}-symmetry, Cartan decompositions, Lie triple systems and Krein space-related Clifford algebras

NASA Astrophysics Data System (ADS)

Günther, Uwe; Kuzhel, Sergii

2010-10-01

Gauged \\ {P}\\ {T} quantum mechanics (PTQM) and corresponding Krein space setups are studied. For models with constant non-Abelian gauge potentials and extended parity inversions compact and noncompact Lie group components are analyzed via Cartan decompositions. A Lie-triple structure is found and an interpretation as \\ {P}\\ {T}-symmetrically generalized Jaynes-Cummings model is possible with close relation to recently studied cavity QED setups with transmon states in multilevel artificial atoms. For models with Abelian gauge potentials a hidden Clifford algebra structure is found and used to obtain the fundamental symmetry of Krein space-related J-self-adjoint extensions for PTQM setups with ultra-localized potentials.

Density of Mars' south polar layered deposits.

PubMed

Zuber, Maria T; Phillips, Roger J; Andrews-Hanna, Jeffrey C; Asmar, Sami W; Konopliv, Alexander S; Lemoine, Frank G; Plaut, Jeffrey J; Smith, David E; Smrekar, Suzanne E

2007-09-21

Both poles of Mars are hidden beneath caps of layered ice. We calculated the density of the south polar layered deposits by combining the gravity field obtained from initial results of radio tracking of the Mars Reconnaissance Orbiter with existing surface topography from the Mars Orbiter Laser Altimeter on the Mars Global Surveyor spacecraft and basal topography from the Mars Advanced Radar for Subsurface and Ionospheric Sounding on the Mars Express spacecraft. The results indicate a best-fit density of 1220 kilograms per cubic meter, which is consistent with water ice that has approximately 15% admixed dust. The results demonstrate that the deposits are probably composed of relatively clean water ice and also refine the martian surface-water inventory.

The Muon Portal Project: A large-area tracking detector for muon tomography

NASA Astrophysics Data System (ADS)

Riggi, F.

2016-05-01

The Muon Portal Project [1] is a joint initiative between research and industrial partners, aimed at the construction of a real size detector protoype to search for hidden high-Z fissile materials inside containers by the muon scattering technique. The detector is based on a set of 48 detection modules (1 m × 3 m), so as to provide four X-Y detection planes, two placed above and two below the container to be inspected. After a research and development phase, which led to the choice and test of the individual components, the construction of the full size detector has already started and will be completed in a few months.

Sherlock Holmes and the proteome--a detective story.

PubMed

Righetti, Pier Giorgio; Boschetti, Egisto

2007-02-01

The performance of a hexapeptide ligand library in capturing the 'hidden proteome' is illustrated and evaluated. This library, insolubilized on an organic polymer and available under the trade name 'Equalizer Bead Technology', acts by capturing all components of a given proteome, by concentrating rare and very rare proteins, and simultaneously diluting the abundant ones. This results in a proteome of 'normalized' relative abundances, amenable to analysis by MS and any other analytical tool. Examples are given of analysis of human urine and serum, as well as cell and tissue lysates, such as Escherichia coli and Saccharomyces cerevisiae extracts. Another important application is impurity tracking and polishing of recombinant DNA products, especially biopharmaceuticals meant for human consumption.

Nominal ISOMERs (Incorrect Spellings Of Medicines Eluding Researchers)—variants in the spellings of drug names in PubMed: a database review

PubMed Central

Aronson, Jeffrey K

2016-01-01

Objective To examine how misspellings of drug names could impede searches for published literature. Design Database review. Data source PubMed. Review methods The study included 30 drug names that are commonly misspelt on prescription charts in hospitals in Birmingham, UK (test set), and 30 control names randomly chosen from a hospital formulary (control set). The following definitions were used: standard names—the international non-proprietary names, variant names—deviations in spelling from standard names that are not themselves standard names in English language nomenclature, and hidden reference variants—variant spellings that identified publications in textword (tw) searches of PubMed or other databases, and which were not identified by textword searches for the standard names. Variant names were generated from standard names by applying letter substitutions, omissions, additions, transpositions, duplications, deduplications, and combinations of these. Searches were carried out in PubMed (30 June 2016) for “standard name[tw]” and “variant name[tw] NOT standard name[tw].” Results The 30 standard names of drugs in the test set gave 325 979 hits in total, and 160 hidden reference variants gave 3872 hits (1.17%). The standard names of the control set gave 470 064 hits, and 79 hidden reference variants gave 766 hits (0.16%). Letter substitutions (particularly i to y and vice versa) and omissions together accounted for 2924 (74%) of the variants. Amitriptyline (8530 hits) yielded 18 hidden reference variants (179 (2.1%) hits). Names ending in “in,” “ine,” or “micin” were commonly misspelt. Failing to search for hidden reference variants of “gentamicin,” “amitriptyline,” “mirtazapine,” and “trazodone” would miss at least 19 systematic reviews. A hidden reference variant related to Christmas, “No-el”, was rare; variants of “X-miss” were rarer. Conclusion When performing searches, researchers should include misspellings of drug names among their search terms. PMID:27974346

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.

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.

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.

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.

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.

Social pediatrics: weaving horizontal and vertical threads through pediatric residency.

PubMed

van den Heuvel, Meta; Martimianakis, Maria Athina Tina; Levy, Rebecca; Atkinson, Adelle; Ford-Jones, Elizabeth; Shouldice, Michelle

2017-01-13

Social pediatrics teaches pediatric residents how to understand disease within their patients' social, environmental and political contexts. It's an essential component of pediatric residency training; however there is very little literature that addresses how such a broad-ranging topic can be taught effectively. The aim of this study was to determine and characterize social pediatric education in our pediatric residency training in order to identify strengths and gaps. A social pediatrics curriculum map was developed, attending to 3 different dimensions: (1) the intended curriculum as prescribed by the Objectives of Training for Pediatrics of the Royal College of Physicians and Surgeons of Canada (RCPSC), (2) the formal curriculum defined by rotation-specific learning objectives, and (3) the informal/hidden curriculum as reflected in resident and teacher experiences and perceptions. Forty-one social pediatric learning objectives were extracted from the RCPSC Objectives of Training for Pediatrics, most were listed in the Medical Expert (51%) and Health Advocate competencies (24%). Almost all RCPSC social pediatric learning objectives were identified in more than one rotation and/or seminar. Adolescent Medicine (29.2%), Pediatric Ambulatory Medicine (26.2%) and Developmental Pediatrics (25%) listed the highest proportion of social pediatric learning objectives. Four (10%) RCPSC social pediatric objectives were not explicitly named within learning objectives of the formal curriculum. The informal curriculum revealed that both teachers and residents viewed social pediatrics as integral to all clinical encounters. Perceived barriers to teaching and learning of social pediatrics included time constraints, particularly in a tertiary care environment, and the value of social pediatrics relative to medical expert knowledge. Despite the lack of an explicit thematic presentation of social pediatric learning objectives by the Royal College and residency training program, social pediatric topics are integrated, taught and learned throughout the entire curriculum. Special attention needs to be given to the hidden curriculum and system barriers that may impede social pediatric education.

Development of object permanence in food-storing magpies (Pica pica).

PubMed

Pollok, B; Prior, H; Güntürkün, O

2000-06-01

The development of object permanence was investigated in black-billed magpies (Pica pica), a food-storing passerine bird. The authors tested the hypothesis that food-storing development should be correlated with object-permanence development and that specific stages of object permanence should be achieved before magpies become independent. As predicted, Piagetian Stages 4 and 5 were reached before independence was achieved, and the ability to represent a fully hidden object (Piagetian Stage 4) emerged by the age when magpies begin to retrieve food. Contrary to psittacine birds and humans, but as in dogs and cats, no "A-not-B error" occurred. Although magpies also mastered 5 of 6 invisible displacement tasks, evidence of Piagetian Stage 6 competence was ambiguous.

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.

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.

Radiology Jobs: Uncovering Hidden and Not-So-Hidden Opportunities From the ACR Jobs Board.

PubMed

Misono, Alexander S; Saini, Sanjay; Prabhakar, Anand M

2016-04-01

The radiology job market remains daunting. Trainees choosing fellowships benefit from understanding employers' likely future needs. Radiology practices may similarly refine recruiting practices. This study quantitatively analyzes the current radiology job landscape. Job postings on the ACR Career Center online portal between June 2014 and June 2015 were reviewed. As entries are frequently added and removed, posts were manually collected weekly. Postings were recorded in a database and included date, practice, location, specialty/subspecialty, job type, years of experience, salary, and job description. The database was analyzed to characterize employer needs, salary, partnership track availability, and job availability by geography. A total of 1,778 jobs were posted during the study period. Of these, 1,529 (86.0%) were diagnostic; 240 (13.5%) were interventional; and 9 (0.5%) were administrative. Most jobs were in private practice (75.7%), compared with academic (16.3%) and other (7.9%). Although many did not require a specific specialty (46%), the most-frequent needs were breast (17%), neuroradiology (11%), musculoskeletal (8%), and body (7%). Of non-breast-imaging jobs, roughly 30% indicated an interest in breast-imaging skills. A minority (13%) requested prior experience of greater than 1 year, with some seeking 7-10 years of experience. Although most (87%) were full-time positions, part-time, temporary, and contractor roles were described in the remaining 13%. Salary data were rarely reported (7%), with a range of $98,967-$1,000,000. The most jobs were based in California (11%); New York (7%); Pennsylvania (7%); and Illinois (6%). However, when indexed per million population, the highest job rates were in Nevada (14.1); Washington DC (13.7); Hawaii (13.4); Montana (9.8); and Pennsylvania (9.1). Roughly 31% of postings described partnership tracks, with the highest rates in New England (58%), the Pacific Northwest (56%), the Midwest (40%), and Southern (40%) regions; the lowest were in the Mountain (26%), Mid-Atlantic (25%), and Southwest (21%) regions. Most radiology jobs remain in private practice general radiology. Breast, neuroradiology, and musculoskeletal radiology were most frequently desired among areas of subspecialty training. Advertised partnership tracks were less common and varied widely geographically. Copyright © 2016 American College of Radiology. Published by Elsevier Inc. All rights reserved.

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.

The Effect of Visual Signals on Spatial Decision Making

ERIC Educational Resources Information Center

Danziger, Shai; Rafal, Robert

2009-01-01

We examined the effect of an irrelevant visual transient on the decision where to look for a hidden object. Participants also performed a conventional "inhibition of return" localization task. In Experiments 1 and 2 the two tasks were blocked and in Experiments 3 and 4 they were randomly interleaved. In every experiment there was a bias to select…

Spatial Relational Memory in 9-Month-Old Macaque Monkeys

ERIC Educational Resources Information Center

Lavenex, Pierre; Lavenex, Pamela Banta

2006-01-01

This experiment assesses spatial and nonspatial relational memory in freely moving 9-mo-old and adult (11-13-yr-old) macaque monkeys ("Macaca mulatta"). We tested the use of proximal landmarks, two different objects placed at the center of an open-field arena, as conditional cues allowing monkeys to predict the location of food rewards hidden in…

Adults' Social Cues Facilitate Young Children's Use of Signs and Symbols

ERIC Educational Resources Information Center

Leekam, Susan R.; Solomon, Tracy L.; Teoh, Yee-San

2010-01-01

Three experiments investigated the effect of an adult's social cues on 2- and 3-year-old children's ability to use a sign or symbol to locate a hidden object. Results showed that an adult's positive, engaging facial expression facilitated children's ability to identify the correct referent, particularly for 3-year-olds. A neutral facial expression…

How Should We Question Young Children's Understanding of Aspectuality?

ERIC Educational Resources Information Center

Waters, Gillian M.; Beck, Sarah R.

2012-01-01

In two experiments, we investigated whether 4- to 5-year-old children's ability to demonstrate their understanding of aspectuality was influenced by how the test question was phrased. In Experiment 1, 60 children chose whether to look or feel to gain information about a hidden object (identifiable by sight or touch). Test questions referred either…

Finding Hidden Chemistry in Ancient Egyptian Artifacts: Pigment Degradation Taught in a Chemical Engineering Course

ERIC Educational Resources Information Center

Gime´nez, Javier

2015-01-01

The main objective of this work was to show the application of the study of ancient technology and science on teaching (and learning) chemistry in Chemical Engineering Undergraduate studies. Degradation patterns of pigments used in Ancient Egypt were incorporated in the syllabus of the course entitled "Technological and Scientific…

Undesirable Features of the Medical Learning Environment: A Narrative Review of the Literature

ERIC Educational Resources Information Center

Benbassat, Jochanan

2013-01-01

The objective of this narrative review of the literature is to draw attention to four undesirable features of the medical learning environment (MLE). First, students' fears of personal inadequacy and making errors are enhanced rather than alleviated by the hidden curriculum of the clinical teaching setting; second, the MLE projects a denial…

What's Mine Is Mine: Twelve-Month-Olds Use Possessive Pronouns to Identify Referents

ERIC Educational Resources Information Center

Saylor, Megan M.; Ganea, Patricia A.; Vazquez, Maria D.

2011-01-01

This research investigated 12-month-olds' ability to use person-specific language to determine to which of several absent things a person is referring. Infants were introduced to two experimenters who played separately with a different ball. One researcher asked infants to retrieve her object when both balls were hidden. Infants selected the…

Comprehension of Novel Communicative Signs by Apes and Human Children.

ERIC Educational Resources Information Center

Tomasello, Michael; Call, Josep; Gluckman, Andrea

1997-01-01

Compared comprehension of novel communicative signs to assist 2.5- and 3-year-old humans, chimpanzees, and orangutans find hidden objects during a hiding-finding game. Found that children at both ages performed above chance with all signs. No ape performed above chance for any signs not known before the experiment despite three times as many…

A general solution to the hidden-line problem. [to graphically represent aerodynamic stability derivatives

NASA Technical Reports Server (NTRS)

Hedgley, D. R., Jr.

1982-01-01

The requirements for computer-generated perspective projections of three dimensional objects has escalated. A general solution was developed. The theoretical solution to this problem is presented. The method is very efficient as it minimizes the selection of points and comparison of line segments and hence avoids the devastation of square-law growth.

Number Prompts Left-to-Right Spatial Mapping in Toddlerhood

ERIC Educational Resources Information Center

McCrink, Koleen; Perez, Jasmin; Baruch, Erica

2017-01-01

Toddlers performed a spatial mapping task in which they were required to learn the location of a hidden object in a vertical array and then transpose this location information 90° to a horizontal array. During the vertical training, they were given (a) no labels, (b) alphabetical labels, or (c) numerical labels for each potential spatial location.…

Measuring Weld Profiles By Computer Tomography

NASA Technical Reports Server (NTRS)

Pascua, Antonio G.; Roy, Jagatjit

1990-01-01

Noncontacting, nondestructive computer tomography system determines internal and external contours of welded objects. System makes it unnecessary to take metallurgical sections (destructive technique) or to take silicone impressions of hidden surfaces (technique that contaminates) to inspect them. Measurements of contours via tomography performed 10 times as fast as measurements via impression molds, and tomography does not contaminate inspected parts.

The Role of Intentionality and Iconicity in Children's Developing Comprehension and Production of Cartographic Symbols

ERIC Educational Resources Information Center

Myers, Lauren J.; Liben, Lynn S.

2008-01-01

The contribution of intentionality understanding to symbolic development was examined. Actors added colored dots to a map, displaying either symbolic or aesthetic intentions. In Study 1, most children (5-6 years) understood actors' intentions, but when asked which graphic would help find hidden objects, most selected the incorrect (aesthetic) one…

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.

Goal-recognition-based adaptive brain-computer interface for navigating immersive robotic systems

NASA Astrophysics Data System (ADS)

Abu-Alqumsan, Mohammad; Ebert, Felix; Peer, Angelika

2017-06-01

Objective. This work proposes principled strategies for self-adaptations in EEG-based Brain-computer interfaces (BCIs) as a way out of the bandwidth bottleneck resulting from the considerable mismatch between the low-bandwidth interface and the bandwidth-hungry application, and a way to enable fluent and intuitive interaction in embodiment systems. The main focus is laid upon inferring the hidden target goals of users while navigating in a remote environment as a basis for possible adaptations. Approach. To reason about possible user goals, a general user-agnostic Bayesian update rule is devised to be recursively applied upon the arrival of evidences, i.e. user input and user gaze. Experiments were conducted with healthy subjects within robotic embodiment settings to evaluate the proposed method. These experiments varied along three factors: the type of the robot/environment (simulated and physical), the type of the interface (keyboard or BCI), and the way goal recognition (GR) is used to guide a simple shared control (SC) driving scheme. Main results. Our results show that the proposed GR algorithm is able to track and infer the hidden user goals with relatively high precision and recall. Further, the realized SC driving scheme benefits from the output of the GR system and is able to reduce the user effort needed to accomplish the assigned tasks. Despite the fact that the BCI requires higher effort compared to the keyboard conditions, most subjects were able to complete the assigned tasks, and the proposed GR system is additionally shown able to handle the uncertainty in user input during SSVEP-based interaction. The SC application of the belief vector indicates that the benefits of the GR module are more pronounced for BCIs, compared to the keyboard interface. Significance. Being based on intuitive heuristics that model the behavior of the general population during the execution of navigation tasks, the proposed GR method can be used without prior tuning for the individual users. The proposed methods can be easily integrated in devising more advanced SC schemes and/or strategies for automatic BCI self-adaptations.

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.

Subdiffractional tracking of internalized molecules reveals heterogeneous motion states of synaptic vesicles

PubMed Central

Morrow, Isabel C.; Harper, Callista B.

2016-01-01

Our understanding of endocytic pathway dynamics is severely restricted by the diffraction limit of light microscopy. To address this, we implemented a novel technique based on the subdiffractional tracking of internalized molecules (sdTIM). This allowed us to image anti–green fluorescent protein Atto647N-tagged nanobodies trapped in synaptic vesicles (SVs) from live hippocampal nerve terminals expressing vesicle-associated membrane protein 2 (VAMP2)–pHluorin with 36-nm localization precision. Our results showed that, once internalized, VAMP2–pHluorin/Atto647N–tagged nanobodies exhibited a markedly lower mobility than on the plasma membrane, an effect that was reversed upon restimulation in presynapses but not in neighboring axons. Using Bayesian model selection applied to hidden Markov modeling, we found that SVs oscillated between diffusive states or a combination of diffusive and transport states with opposite directionality. Importantly, SVs exhibiting diffusive motion were relatively less likely to switch to the transport motion. These results highlight the potential of the sdTIM technique to provide new insights into the dynamics of endocytic pathways in a wide variety of cellular settings. PMID:27810917

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.

The more often you see an object, the easier it becomes to track it

PubMed Central

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

2010-01-01

Is it easier to track objects that you have seen repeatedly? We compared repeated blocks, where identities were the same from trial to trial, to unrepeated blocks, where identities varied. People were better in tracking objects that they saw repeatedly. We tested four hypotheses to explain this repetition benefit. First, perhaps the repeated condition benefits from consistent mapping of identities to target and distractor roles. However, the repetition benefit persisted even when both the repeated and the unrepeated conditions used consistent mapping. Second, repetition might improve the ability to recover targets that have been lost, or swapped with distractors. However, we observed a larger repetition benefit for color-color conjunctions, which do not benefit from such error recovery processes, than for unique features, which do. Furthermore, a repetition benefit was observed even in the absence of distractors. Third, perhaps repetition frees up resources by reducing memory load. However, increasing memory load by masking identities during the motion phase reduced the repetition benefit. The fourth hypothesis is that repetition facilitates identity tracking, which in turn improves location tracking. This hypothesis is consistent with all our results. Thus, our data suggest that identity and location tracking share a common resource. PMID:20884469

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.

Rotational Displacement Skills in Rhesus Macaques (Macaca mulatta)

PubMed Central

Hughes, Kelly D.; Santos, Laurie R.

2016-01-01

Rotational displacement tasks, in which participants must track an object at a hiding location within an array while the array rotates, exhibit a puzzling developmental pattern in humans. Human children take an unusually long time to master this task and tend to solve rotational problems through the use of nongeometric features or landmarks as opposed to other kinds of spatial cues. We investigated whether these developmental characteristics are unique to humans by testing rotational displacement skills in a monkey species, the rhesus macaque (Macaca mulatta), using a looking-time method. Monkeys first saw food hidden in two differently colored boxes within an array. The array was then rotated 180° and the boxes reopened to reveal the food in an expected or unexpected location. Our first two experiments explored the developmental time-course of performance on this rotational displacement task. We found that adult macaques looked longer at the unexpected event, but such performance was not mirrored in younger-aged macaques. In a third study, we systematically varied featural information and visible access to the array to investigate which strategies adult macaques used in solving rotational displacements. Our results show that adult macaques need both sets of information to solve the task. Taken together, these results suggest both similarities and differences in mechanisms by which human and nonhuman primates develop this spatial skill. PMID:22866770

PADF electromagnetic source localization using extremum seeking control

NASA Astrophysics Data System (ADS)

Al Issa, Huthaifa A.; Ordóñez, Raúl

2014-10-01

Wireless Sensor Networks (WSNs) are a significant technology attracting considerable research interest. Recent advances in wireless communications and electronics have enabled the development of low-cost, low-power and multi-functional sensors that are small in size and communicate over short distances. Most WSN applications require knowing or measuring locations of thousands of sensors accurately. For example, sensing data without knowing the sensor location is often meaningless. Locations of sensor nodes are fundamental to providing location stamps, locating and tracking objects, forming clusters, and facilitating routing. This research focused on the modeling and implementation of distributed, mobile radar sensor networks. In particular, we worked on the problem of Position-Adaptive Direction Finding (PADF), to determine the location of a non- collaborative transmitter, possibly hidden within a structure, by using a team of cooperative intelligent sensor networks. Position-Adaptive radar concepts have been formulated and investigated at the Air Force Research Laboratory (AFRL) within the past few years. In this paper, we present the simulation performance analysis on the application aspect. We apply Extremum Seeking Control (ESC) schemes by using the swarm seeking problem, where the goal is to design a control law for each individual sensor that can minimize the error metric by adapting the sensor positions in real-time, thereby minimizing the unknown estimation error. As a result we achieved source seeking and collision avoidance of the entire group of the sensor positions.

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.

Four-Year-Olds Use a Mixture of Spatial Reference Frames

PubMed Central

Negen, James; Nardini, Marko

2015-01-01

Keeping track of unseen objects is an important spatial skill. In order to do this, people must situate the object in terms of different frames of reference, including body position (egocentric frame of reference), landmarks in the surrounding environment (extrinsic frame reference), or other attached features (intrinsic frame of reference). Nardini et al. hid a toy in one of 12 cups in front of children, turned the array when they were not looking, and then asked them to point to the cup with the toy. This forced children to use the intrinsic frame (information about the array of cups) to locate the hidden toy. Three-year-olds made systematic errors by using the wrong frame of reference, 4-year-olds were at chance, and only 5- and 6-year-olds were successful. Can we better understand the developmental change that takes place at four years? This paper uses a modelling approach to re-examine the data and distinguish three possible strategies that could lead to the previous results at four years: (1) Children were choosing cups randomly, (2) Children were pointing between the egocentric/extrinsic-cued location and the correct target, and (3) Children were pointing near the egocentric/extrinsic-cued location on some trials and near the target on the rest. Results heavily favor the last possibility: 4-year-olds were not just guessing or trying to combine the available frames of reference. They were using the intrinsic frame on some trials, but not doing so consistently. These insights suggest that accounts of improving spatial performance at 4 years need to explain why there is a mixture of responses. Further application of the selected model also suggests that children become both more reliant on the correct frame and more accurate with any chosen frame as they mature. PMID:26133990

Dark matter versus Mach's principle.

NASA Astrophysics Data System (ADS)

von Borzeszkowski, H.-H.; Treder, H.-J.

1998-02-01

Empirical and theoretical evidence show that the astrophysical problem of dark matter might be solved by a theory of Einstein-Mayer type. In this theory up to global Lorentz rotations the reference system is determined by the motion of cosmic matter. Thus one is led to a "Riemannian space with teleparallelism" realizing a geometric version of the Mach-Einstein doctrine. The field equations of this gravitational theory contain hidden matter terms where the existence of hidden matter is inferred safely from its gravitational effects. It is argued that in the nonrelativistic mechanical approximation they provide an inertia-free mechanics where the inertial mass of a body is induced by the gravitational action of the comic masses. Interpreted form the Newtonian point of view this mechanics shows that the effective gravitational mass of astrophysical objects depends on r such that one expects the existence of dark matter.

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

Human analog tests of the sixth stage of object permanence.

PubMed

Heishman, M; Conant, M; Pasnak, R

1995-06-01

Two adult cats were tested on multiple invisible displacement. A dowel was established as a secondary reinforcer and hidden in a manner similar to that used to assess the culmination of sensorimotor intelligence in human infants. Three other cats were tested on single invisible displacement, a simpler version of the task. For human infants, this task is used to assess the beginning of mental representation in the sixth and last stage of sensorimotor intelligence. The cats' searches on these tasks were consistent with representation of an unsensed object and fully developed sensorimotor intelligence.

Information sampling behavior with explicit sampling costs

PubMed Central

Juni, Mordechai Z.; Gureckis, Todd M.; Maloney, Laurence T.

2015-01-01

The decision to gather information should take into account both the value of information and its accrual costs in time, energy and money. Here we explore how people balance the monetary costs and benefits of gathering additional information in a perceptual-motor estimation task. Participants were rewarded for touching a hidden circular target on a touch-screen display. The target’s center coincided with the mean of a circular Gaussian distribution from which participants could sample repeatedly. Each “cue” — sampled one at a time — was plotted as a dot on the display. Participants had to repeatedly decide, after sampling each cue, whether to stop sampling and attempt to touch the hidden target or continue sampling. Each additional cue increased the participants’ probability of successfully touching the hidden target but reduced their potential reward. Two experimental conditions differed in the initial reward associated with touching the hidden target and the fixed cost per cue. For each condition we computed the optimal number of cues that participants should sample, before taking action, to maximize expected gain. Contrary to recent claims that people gather less information than they objectively should before taking action, we found that participants over-sampled in one experimental condition, and did not significantly under- or over-sample in the other. Additionally, while the ideal observer model ignores the current sample dispersion, we found that participants used it to decide whether to stop sampling and take action or continue sampling, a possible consequence of imperfect learning of the underlying population dispersion across trials. PMID:27429991