Semantic representation module of a machine-learning engine in a video analysis system

Semantic representation module of a machine-learning engine in a video analysis system

A machine-learning engine is disclosed that is configured to recognize and learn behaviors, as well as to identify and distinguish between normal and abnormal behavior within a scene, by analyzing movements and/or activities (or absence of such) over time. The machine-learning engine may be configur...

Ausführliche Beschreibung

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Bibliographische Detailangaben
Hauptverfasser: Yang Tao, Gottumukkal Rajkiran K, Urech Dennis G, Cobb Wesley Kenneth, Seow Ming-Jung, Saitwal Kishor Adinath, Friedlander David S, Xu Gang, Solum David M, Eaton John Eric, Risinger Lon W
Format: Patent
Sprache:eng
Schlagworte:
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
HANDLING RECORD CARRIERS
PHYSICS
PRESENTATION OF DATA
RECOGNITION OF DATA
RECORD CARRIERS
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Beschreibung
Zusammenfassung:A machine-learning engine is disclosed that is configured to recognize and learn behaviors, as well as to identify and distinguish between normal and abnormal behavior within a scene, by analyzing movements and/or activities (or absence of such) over time. The machine-learning engine may be configured to evaluate a sequence of primitive events and associated kinematic data generated for an object depicted in a sequence of video frames and a related vector representation. The vector representation is generated from a primitive event symbol stream and a phase space symbol stream, and the streams describe actions of the objects depicted in the sequence of video frames.