Recovering the basic structure of human activities from noisy video-based symbol strings

International Journal of Pattern Recognition and Artificial Intelligence

Volumn 22, Issue 8, 2008, Pages 1621-1646

  Kitani, Kris M ^a   Sato, Yoichi ^a   Sugimoto, Akihiro ^b  

^a INSTITUTE OF INDUSTRIAL SCIENCE   (Japan)

^b NATIONAL INSTITUTE OF INFORMATICS   (Japan)

Author keywords

Activity learning; Grammatical inference; Minimum description length principle; Model selection; Noise; Stochastic context free grammars

Indexed keywords

COMPUTATIONAL GRAMMARS; EDUCATION; FORESTRY; RANDOM PROCESSES; STOCHASTIC MODELS; VIDEO RECORDING;

ACTIVITY LEARNING; GRAMMATICAL INFERENCE; MINIMUM DESCRIPTION LENGTH PRINCIPLE; MODEL SELECTION; NOISE; STOCHASTIC CONTEXT-FREE GRAMMARS;

CONTEXT FREE GRAMMARS;

EID: 58449098738     PISSN: 02180014     EISSN: None     Source Type: Journal    
DOI: 10.1142/S0218001408006776     Document Type: Article

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