Incremental learning, clustering and hierarchy formation of whole body motion patterns using adaptive Hidden Markov Chains

International Journal of Robotics Research

Volumn 27, Issue 7, 2008, Pages 761-784

  Kulić, Dana ^a   Takano, Wataru ^a   Nakamura, Yoshihiko ^a  

^a UNIVERSITY OF TOKYO   (Japan)

Author keywords

Cognitive robotics; Computer vision; Gesture; Human centred and life like robotics; Humanoid robots; Learning and adaptive systems; Posture; Recognition; Sensing and perception; Social spaces and facial expressions

Indexed keywords

BOOLEAN FUNCTIONS; CHAINS; CLUSTER ANALYSIS; CLUSTERING ALGORITHMS; DYNAMIC MODELS; FLOW OF SOLIDS; HIDDEN MARKOV MODELS; KNOWLEDGE BASED SYSTEMS; LEARNING SYSTEMS; MAMMALS; MARKOV PROCESSES; MATHEMATICAL MODELS; STOCHASTIC MODELS;

COMPUTATION COSTS; DYNAMIC STOCHASTIC MODEL; HIDDEN MARKOV CHAINS; HIERARCHICAL AGGLOMERATIVE CLUSTERING; HUMAN MOTIONS; INCREMENTAL LEARNING; KNOWLEDGE BASE (KB); MARKOV CHAINS (MC); MODEL ADAPTATION; MODEL SIZE; MODEL SPACES; MOTION CAPTURE DATA; MOTION PATTERNS; MOTION PRIMITIVES; MOTION RECOGNITION; NEW ALGORITHM; NOVE L APPROACH; OBSERVATION OF HUMAN MOTION; RELATIVE DISTANCES; SAGE PUBLICATIONS (CO); TRAINING DATA; TREE LEAVES; TREE STRUCTURES; WHOLE-BODY MOTION;

TREES (MATHEMATICS);

EID: 45849101711     PISSN: 02783649     EISSN: 17413176     Source Type: Journal    
DOI: 10.1177/0278364908091153     Document Type: Article

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