Online learning of correspondences between images

IEEE Transactions on Pattern Analysis and Machine Intelligence

Volumn 35, Issue 1, 2013, Pages 118-129

  Felsberg, Michael ^a   Larsson, Fredrik ^a   Wiklund, Johan ^a   Wadstr̈mer, Niclas ^b   Ahlberg, J̈rgen ^c  

^a LINKÖPING UNIVERSITY   (Sweden)

^b SWEDISH DEFENCE RESEARCH AGENCY   (Sweden)

^c Termisk Systemteknik AB   (Sweden)

Author keywords

channel representation; computer vision; correspondence problem; Online learning; surveillance

Indexed keywords

3-D SPACE; 3D SCENES; BASIS FUNCTION APPROACH; CHANNEL REPRESENTATION; CHANNEL VECTORS; CORRESPONDENCE PROBLEMS; FAST CONVERGENCE; FUNDAMENTAL MATRIX; IMAGE SEQUENCE; IMAGING GEOMETRY; ITERATIVE LEARNING; ITERATIVE SOLUTIONS; ONLINE LEARNING; POINT CORRESPONDENCE; POINT SET; REAL TIME; STATE-OF-THE-ART METHODS;

COMPUTER VISION; E-LEARNING; GLOBAL OPTIMIZATION; ITERATIVE METHODS; MAPPING; SPACE SURVEILLANCE; THREE DIMENSIONAL COMPUTER GRAPHICS; UNCERTAINTY ANALYSIS;

THREE DIMENSIONAL;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; COMPUTER ASSISTED DIAGNOSIS; IMAGE SUBTRACTION; METHODOLOGY; ONLINE SYSTEM; THREE DIMENSIONAL IMAGING;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; IMAGE INTERPRETATION, COMPUTER-ASSISTED; IMAGING, THREE-DIMENSIONAL; ONLINE SYSTEMS; PATTERN RECOGNITION, AUTOMATED; SUBTRACTION TECHNIQUE;

MLCS; MLOWN;

EID: 84870219247     PISSN: 01628828     EISSN: None     Source Type: Journal    
DOI: 10.1109/TPAMI.2012.65     Document Type: Article

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