Detecting anomalous trajectories in a video surveillance system
AssigneeBehavioral Recognition Systems, Inc.
InventorsWesley Kenneth Cobb, Ming-Jung Seow, Gang Xu
Life of this patent
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Abstract
Techniques are disclosed for determining anomalous trajectories of objects tracked over a sequence of video frames. In one embodiment, a symbol trajectory may be derived from observing an object moving through a scene. The symbol trajectory represents semantic concepts extracted from the trajectory of the object. Whether the symbol trajectory is anomalous may be determined, based on previously observed symbol trajectories. A user may be alerted upon determining that the symbol trajectory is anomalous.
Claims21
A computer-implemented method for analyzing a sequence of video frames depicting a scene captured by a video camera, the method comprising:
- passing each of a plurality of kinematic data vectors derived from analyzing a foreground object detected in the sequence of video frames to a plurality of adaptive resonance theory (ART) networks, each ART network modeling a subset of kinematic data parsed from the kinematic data vectors;
- identifying, in each ART network, a cluster to which each respective subset of kinematic data parsed from the plurality of kinematic data vectors is mapped;
- generating a primitive trajectory based on the clusters identified in each of the ART networks;
- and
- generating a symbol trajectory from the primitive trajectory.
A computer-readable storage medium containing a program which, when executed by a processor, performs an operation for analyzing a sequence of video frames depicting a scene captured by a video camera, the operation comprising:
- passing each of a plurality of kinematic data vectors derived from analyzing a foreground object detected in the sequence of video frames to a plurality of adaptive resonance theory (ART) networks, each ART network modeling a subset of kinematic data parsed from the kinematic data vectors;
- identifying, in each ART network, a cluster to which each respective subset of kinematic data parsed from the plurality of kinematic data vectors is mapped;
- generating a primitive trajectory based on the clusters identified in each of the ART networks;
- and
- generating a symbol trajectory from the primitive trajectory.
A system, comprising:
- a video input source configured to provide a sequence of video frames, each depicting a scene;
- a processor;
- and
- a memory containing a program, which, when executed on the processor is configured to perform an operation for analyzing the scene, as depicted by the sequence of video frames captured by the video input source, the operation comprising:
- passing each of a plurality of kinematic data vectors derived from analyzing a foreground object detected in a sequence of video frames to a plurality of adaptive resonance theory (ART) networks, each ART network modeling a subset of kinematic data parsed from the kinematic data vectors,
- identifying, in each ART network, a cluster to which each respective subset of kinematic data parsed from the plurality of kinematic data vectors is mapped,
- generating a primitive trajectory based on the clusters identified in each of the ART networks, and
- generating a symbol trajectory from the primitive trajectory.
Dependencies are inferred from the claim text.