Action classification using deep embedded clustering

Action classification using deep embedded clustering

Described is a system for action recognition through application of deep embedded clustering. For each image frame of an input video, the system computes skeletal joint-based pose features representing an action of a human in the image frame. Non-linear mapping of the pose features into an embedded...

Ausführliche Beschreibung

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Bibliographische Detailangaben
Hauptverfasser: Rahimi, Amir M, Hoffmann, Heiko, Kwon, Hyukseong
Format: Patent
Sprache:eng
Schlagworte:
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
CONTROLLING
COUNTING
HANDLING RECORD CARRIERS
PHYSICS
PRESENTATION OF DATA
RECOGNITION OF DATA
RECORD CARRIERS
REGULATING
SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
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Beschreibung
Zusammenfassung:Described is a system for action recognition through application of deep embedded clustering. For each image frame of an input video, the system computes skeletal joint-based pose features representing an action of a human in the image frame. Non-linear mapping of the pose features into an embedded action space is performed. Temporal classification of the action is performed and a set of categorical gesture-based labels is obtained. The set of categorical gesture-based labels is used to control movement of a machine.