Extraction of Discriminative Patterns from Skeleton Sequences for Accurate Action Recognition

• Autorzy: Thanh T. T. , Chen F , Kotani K. , Le B.

Identyfikatory

DOI

10.3233/FI-2014-991

• Języki publikacji: EN

Abstrakty

EN

Emergence of novel techniques devices e.g., MS Kinect, enables reliable extraction of human skeletons from action videos. Taking skeleton data as inputs, we propose an approach to extract the discriminative patterns for efficient human action recognition. Each action is considered to consist of a sequence of unit actions, each of which is represented by a pattern. Given a skeleton sequence, we first automatically extract the key-frames, and then categorize them into different patterns. We further use a statistical metric to evaluate the discriminative capability of patterns, and define them as local features for action recognition. Experimental results show that the extracted local descriptors could provide very high accuracy in the action recognition, which demonstrate the efficiency of our method in extracting discriminative unit actions.

Słowa kluczowe

EN

discriminative patterns; 3D skeletons; local descriptor; improved TF-IDF; action recognition

• Wydawca: IOS Press
• Czasopismo: Fundamenta Informaticae
• Rocznik: 2014
• Tom: Vol. 130, nr 2
• Strony: 247--261
• Opis fizyczny: Bibliogr. 20 poz., rys.

Twórcy

autor

Thanh T. T.

• School of Information Science, Japan Advanced Institute of Science and Technology, Japan

autor

Chen F

• School of Information Science, Japan Advanced Institute of Science and Technology, Japan

autor

Kotani K.

• School of Information Science, Japan Advanced Institute of Science and Technology, Japan

autor

Le B.

• Faculty of Information Technology, University of Science, VNU - Ho Chi Minh City, Vietnam

Bibliografia

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