Recognizing human actions using a new descriptor based on spatial-temporal interest points and weighted-output classifier

Neurocomputing

Volumn 87, Issue , 2012, Pages 51-61

  Yan, Xunshi ^a,b   Luo, Yupin ^a,b  

^a TSINGHUA NATIONAL LABORATORY FOR INFORMATION SCIENCE AND TECHNOLOGY   (China)

^b TSINGHUA UNIVERSITY   (China)

Author keywords

Action recognition; AdaBoost; Classifier combination; Sparse representation; Spatial temporal interest points

Indexed keywords

ACTION RECOGNITION; CLASSIFIER COMBINATION; DATA SETS; DESCRIPTORS; FEATURE VECTORS; HUMAN ACTIONS; HUMAN-ACTION RECOGNITION; MULTIPLE FEATURES; OVERFITTING; POINT LOCATION; SPARSE REPRESENTATION; SPATIAL LOCATION; SPATIAL TEMPORALS;

ADAPTIVE BOOSTING; GESTURE RECOGNITION; IMAGE RECOGNITION;

MOTION ESTIMATION;

ALGORITHM; ANALYTIC METHOD; ARTICLE; BOXING; DIVING; HAND MOVEMENT; HISTOGRAM; HUMAN; HUMAN ACTIVITIES; IMAGE ANALYSIS; JOGGING; MATHEMATICAL ANALYSIS; MATHEMATICAL COMPUTING; PHYSICAL ACTIVITY; PRIORITY JOURNAL; RUNNING; SKATEBOARDING; SPATIAL TEMPORAL INTEREST POINT; WALKING;

EID: 84861947531     PISSN: 09252312     EISSN: 18728286     Source Type: Journal    
DOI: 10.1016/j.neucom.2012.02.002     Document Type: Article

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