A fast biologically inspired algorithm for recurrent motion estimation

IEEE Transactions on Pattern Analysis and Machine Intelligence

Volumn 29, Issue 2, 2007, Pages 246-260

  Bayerl, Pierre ^a   Neumann, Heiko ^a  

^a UNIVERSITY OF ULM   (Germany)

Author keywords

Algorithms; Computational models of vision; Motion aperture problem; Motion estimation; Recurrent information processing

Indexed keywords

ALGORITHMS; COMPUTER SIMULATION; COMPUTER VISION; DATA PROCESSING; IMAGE ANALYSIS; MATHEMATICAL MODELS; MEDICAL IMAGING; MOTION ESTIMATION;

COMPUTATIONAL MODELS; MOTION APERTURE PROBLEM; NEURAL ACTIVATION; RECURRENT INFORMATION PROCESSING; RECURRENT MOTION ESTIMATION;

NEUROLOGY;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; BIOMIMETICS; BRAIN; COMPUTER ASSISTED DIAGNOSIS; EVALUATION; HUMAN; IMAGE ENHANCEMENT; METHODOLOGY; MOTION; MOVEMENT PERCEPTION; NERVE CELL NETWORK; PHYSIOLOGY;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; BIOMIMETICS; BRAIN; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MOTION; MOTION PERCEPTION; NERVE NET; PATTERN RECOGNITION, AUTOMATED;

EID: 33947217821     PISSN: 01628828     EISSN: None     Source Type: Journal    
DOI: 10.1109/TPAMI.2007.24     Document Type: Article

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