A Bio-Inspired, Motion-Based Analysis of Crowd Behavior Attributes Relevance to Motion Transparency, Velocity Gradients, and Motion Patterns

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Veröffentlicht in:PLoS One vol. 7, no. 12 (Dec 2012), p. e53456
1. Verfasser: Raudies, Florian
Weitere Verfasser: Neumann, Heiko
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Public Library of Science
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100 1 |a Raudies, Florian 
245 1 |a A Bio-Inspired, Motion-Based Analysis of Crowd Behavior Attributes Relevance to Motion Transparency, Velocity Gradients, and Motion Patterns 
260 |b Public Library of Science  |c Dec 2012 
513 |a Journal Article 
520 3 |a The analysis of motion crowds is concerned with the detection of potential hazards for individuals of the crowd. Existing methods analyze the statistics of pixel motion to classify non-dangerous or dangerous behavior, to detect outlier motions, or to estimate the mean throughput of people for an image region. We suggest a biologically inspired model for the analysis of motion crowds that extracts motion features indicative for potential dangers in crowd behavior. Our model consists of stages for motion detection, integration, and pattern detection that model functions of the primate primary visual cortex area (V1), the middle temporal area (MT), and the medial superior temporal area (MST), respectively. This model allows for the processing of motion transparency, the appearance of multiple motions in the same visual region, in addition to processing opaque motion. We suggest that motion transparency helps to identify “danger zones” in motion crowds. For instance, motion transparency occurs in small exit passages during evacuation. However, motion transparency occurs also for non-dangerous crowd behavior when people move in opposite directions organized into separate lanes. Our analysis suggests: The combination of motion transparency and a slow motion speed can be used for labeling of candidate regions that contain dangerous behavior. In addition, locally detected decelerations or negative speed gradients of motions are a precursor of danger in crowd behavior as are globally detected motion patterns that show a contraction toward a single point. In sum, motion transparency, image speeds, motion patterns, and speed gradients extracted from visual motion in videos are important features to describe the behavioral state of a motion crowd. 
610 4 |a Boston University 
651 4 |a United States--US 
651 4 |a Massachusetts 
653 |a International conferences 
653 |a Feature extraction 
653 |a Contraction 
653 |a Hazards 
653 |a Science 
653 |a Video recordings 
653 |a Neurosciences 
653 |a Statistical analysis 
653 |a Optics 
653 |a Paths 
653 |a Pattern recognition 
653 |a Velocity 
653 |a Public spaces 
653 |a Segregation 
653 |a Motion perception 
653 |a Economic 
653 |a Velocity gradient 
653 |a Statistical methods 
653 |a Transparency 
653 |a Motion detection 
653 |a Surveillance 
653 |a Deceleration 
653 |a Human behavior 
653 |a Visual cortex 
653 |a Automation 
653 |a Temporal lobe 
700 1 |a Neumann, Heiko 
773 0 |t PLoS One  |g vol. 7, no. 12 (Dec 2012), p. e53456 
786 0 |d ProQuest  |t Health & Medical Collection 
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