Natural movement generation using hidden Markov models and principal components

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics

Volumn 38, Issue 5, 2008, Pages 1184-1194

  Kwon, Junghyun ^a   Park, Frank C ^a  

^a Seoul National University   (South Korea)

Author keywords

Hidden Markov model (HMM); Movement primitive; Natural movement; Principal component

Indexed keywords

COMPUTATIONAL GRAMMARS; GESTURE RECOGNITION; LEARNING SYSTEMS; MARKOV PROCESSES; OBJECT RECOGNITION; PRINCIPAL COMPONENT ANALYSIS;

CASE STUDIES; HIDDEN MARKOV MODEL (HMM); HIDDEN MARKOV MODELING; HUMAN MOTION DATA; HUMANOID ROBOT; JOINT TRAJECTORIES; LINEAR COMBINATION; MOTION DATA; MOTION GENERATION; MOVEMENT PRIMITIVE; NATURAL MOVEMENT; NATURAL MOVEMENTS; PRINCIPAL COMPONENT; PRINCIPAL COMPONENTS; TASK SPACE;

HIDDEN MARKOV MODELS;

ARTICLE; BIOLOGICAL MODEL; COMPUTER SIMULATION; GESTURE; HUMAN; JOINT; MOVEMENT (PHYSIOLOGY); PHYSIOLOGY; PRINCIPAL COMPONENT ANALYSIS; PROBABILITY; STATISTICAL MODEL;

COMPUTER SIMULATION; GESTURES; HUMANS; JOINTS; MARKOV CHAINS; MODELS, BIOLOGICAL; MODELS, STATISTICAL; MOVEMENT; PRINCIPAL COMPONENT ANALYSIS;

EID: 52349094947     PISSN: 10834419     EISSN: None     Source Type: Journal    
DOI: 10.1109/TSMCB.2008.926324     Document Type: Article

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