Human Motion Change Detection by Hierarchical Gaussian Process Dynamical Model with Particle Filter

Yin, Yafeng; Man, Hong; Wang, Jing; Yang, Guang

doi:10.1109/avss.2010.55

Cited by 7 publications

(3 citation statements)

References 34 publications

(28 reference statements)

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“…Using the video analysis for target tracking [60], event detection [61], activity recognition [62,63], and scene analysis [64] requires a common schema policy. The ontology content should use a common message passing schema, with fields such as at <time> <place> <{pers, veh, obj}, qty> <activity> that are available through video extraction.…”

Section: Activity Schema For Alertingmentioning

confidence: 99%

Enhanced air operations for ground situational awareness

Blasch

Wang

Shen

et al. 2014

2014 IEEE/AIAA 33rd Digital Avionics Systems Conference (DASC)

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Future digital avionics systems will work in complex and cluttered environments which require systems engineering solutions for such applications as airport ground surface management. In this paper, we highlight the use of a L1 video tracker for monitoring activities at an airport. We present methods of information fusion, entity detection, and activity analysis using airport videos for runway detection and terminal events. For coordinated airport security, automated ground surveillance enhances efficient and safe maneuvers for unmanned air vehicles (UAVs) and unmanned ground vehicles (UGVs) operation at airport environments.

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Section: Activity Schema For Alertingmentioning

confidence: 99%

Enhanced air operations for ground situational awareness

Blasch

Wang

Shen

et al. 2014

2014 IEEE/AIAA 33rd Digital Avionics Systems Conference (DASC)

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“…We are interested in image extraction of content, cues and context through ontology text generation. Using the WAMI data, we are interested in behavioral analysis [80], activity recognition [81], and object motion [82]. A. Schemas A schema for image processing is shown in Fig.…”

Section: Example -Wamimentioning

confidence: 99%

Wide-area motion imagery (WAMI) exploitation tools for enhanced situation awareness

Blasch¹,

Seetharaman²,

Palaniappan

et al. 2012

2012 IEEE Applied Imagery Pattern Recognition Workshop (AIPR)

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“…Targets also need signature analysis [51] for detecting move-stop-move patterns [52], distributed tracking techniques [53], and advanced WAMI analysis [54]. Tracking multiple dismounts [55,56] requires real-time solutions [57] for small group activity recognition [58]. Environment: Recent developments in information fusion technology can aid in the analysis of warnings.…”

Section: Layered Sensing Dismount Tracking Directionsmentioning

confidence: 99%

Dismount tracking and identification from electro-optical imagery

Blasch

Ling

et al. 2012

Evolutionary and Bio-Inspired Computation: Theory and Applications VI

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With the advent of new technology in wide-area motion imagery (WAMI) and full-motion video (FMV), there is a capability to exploit the imagery in conjunction with other information sources for improving confidence in detection, tracking, and identification (DTI) of dismounts. Image exploitation, along with other radar and intelligence information can aid decision support and situation awareness. Many advantages and limitations exist in dismount tracking analysis using WAMI/FMV; however, through layered management of sensing resources, there are future capabilities to explore that would increase dismount DTI accuracy, confidence, and timeliness. A layered sensing approach enables commandlevel strategic, operational, and tactical analysis of dismounts to combine multiple sensors and databases, to validate DTI information, as well as to enhance reporting results. In this paper, we discuss WAMI/FMV, compile a list of issues and challenges of exploiting the data for WAMI, and provide examples from recently reported results. Our aim is to provide a discussion to ensure that nominated combatants are detected, the sensed information is validated across multiple perspectives, the reported confidence values achieve positive combatant versus non-combatant detection, and the related situational awareness attributes including behavior analysis, spatial-temporal relations, and cueing are provided in a timely and reliable manner to stakeholders.

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Human Motion Change Detection by Hierarchical Gaussian Process Dynamical Model with Particle Filter

Abstract: Abstract

Cited by 7 publications

References 34 publications

Enhanced air operations for ground situational awareness

Enhanced air operations for ground situational awareness

Wide-area motion imagery (WAMI) exploitation tools for enhanced situation awareness

Dismount tracking and identification from electro-optical imagery

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