Model driven segmentation of articulating humans in Laplacian Eigenspace

IEEE Transactions on Pattern Analysis and Machine Intelligence

Volumn 30, Issue 10, 2008, Pages 1771-1785

  Sundaresan, Aravind ^a   Chellappa, Rama ^b  

^a SRI INTERNATIONAL   (United States)

^b UNIVERSITY OF MARYLAND   (United States)

Author keywords

Computer vision; Graph theoretic methods; Image processing; Object recognition; Partitioning; Pattern recognition; Region growing; Segmentation

Indexed keywords

CHLORINE COMPOUNDS; FACE RECOGNITION; FEATURE EXTRACTION; GRAPH THEORY; GRAPHIC METHODS; LAPLACE TRANSFORMS; SPLINES;

3D VOXEL DATA; ARTICULATED OBJECTS; BOTTOM-UP; COMPUTER VISION; EIGEN SPACE; GENERAL APPROACH; GRAPH-THEORETIC METHODS; GRAPHICAL MODELLING; HIGH-DIMENSIONAL; HUMAN BODIES; HUMAN BODY MODELING; HUMAN SUBJECTS; IMAGE PROCESSING; LAPLACIAN; LAPLACIAN EIGENMAPS; LONG CHAINS; MODEL-DRIVEN SEGMENTATION; NEIGHBORHOOD GRAPHS; OBJECT RECOGNITION; PARTITIONING; PATTERN RECOGNITION; PROBABILISTIC APPROACHES; REGION GROWING; SEGMENTATION; SEGMENTATION RESULTS; SPLINE FITTING; SYNTHETIC DATA; TOP-DOWN;

THREE DIMENSIONAL;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUDIOVISUAL EQUIPMENT; AUTOMATED PATTERN RECOGNITION; COMPUTER ASSISTED DIAGNOSIS; COMPUTER SIMULATION; HISTOLOGY; HUMAN; IMAGE ENHANCEMENT; JOINT; METHODOLOGY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; THREE DIMENSIONAL IMAGING; WHOLE BODY IMAGING;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; COMPUTER SIMULATION; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; IMAGING, THREE-DIMENSIONAL; JOINTS; MODELS, ANATOMIC; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; WHOLE BODY IMAGING;

EID: 50249135567     PISSN: 01628828     EISSN: None     Source Type: Journal    
DOI: 10.1109/TPAMI.2007.70823     Document Type: Article

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