Human action recognition in videos using kinematic features and multiple instance learning

IEEE Transactions on Pattern Analysis and Machine Intelligence

Volumn 32, Issue 2, 2010, Pages 288-303

  Ali, Saad ^a   Shah, Mubarak ^b  

^a CARNEGIE MELLON UNIVERSITY   (United States)

^b UNIVERSITY OF CENTRAL FLORIDA   (United States)

Author keywords

Action recognition; Kinematic features.; Motion; Principal component analysis; Video analysis

Indexed keywords

ACTION RECOGNITION; ANTI-SYMMETRIC; BENCHMARK DATA; CLASSIFICATION ,; FEATURE SPACE; FLOW GRADIENTS; HUMAN-ACTION RECOGNITION; MODE-BASED; MULTIPLE-INSTANCE LEARNING; NEAREST NEIGHBOR ALGORITHM; PRINCIPAL INVARIANTS; QUANTITATIVE RESULT; RATE-OF-STRAIN TENSORS; SEQUENCE OF IMAGES; SPATIOTEMPORAL PATTERNS; SPATIOTEMPORAL VOLUME; VIDEO ANALYSIS;

GESTURE RECOGNITION; KINEMATICS; OPTICAL FLOWS; STRAIN RATE; TENSORS;

PRINCIPAL COMPONENT ANALYSIS;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; BIOMECHANICS; HUMAN; METHODOLOGY; MOVEMENT (PHYSIOLOGY); PHYSIOLOGY; PRINCIPAL COMPONENT ANALYSIS; VIDEORECORDING;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; BIOMECHANICS; HUMANS; MOVEMENT; PATTERN RECOGNITION, AUTOMATED; PRINCIPAL COMPONENT ANALYSIS; VIDEO RECORDING;

EID: 73849126715     PISSN: 01628828     EISSN: None     Source Type: Journal    
DOI: 10.1109/TPAMI.2008.284     Document Type: Article

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