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Visual data association for real‐time video tracking using genetic and estimation of distribution algorithms
Author(s) -
Patricio Miguel A.,
García Jesús,
Berlanga Antonio,
Molina José M.
Publication year - 2009
Publication title -
international journal of imaging systems and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.359
H-Index - 47
eISSN - 1098-1098
pISSN - 0899-9457
DOI - 10.1002/ima.20196
Subject(s) - computer science , frame (networking) , set (abstract data type) , heuristic , algorithm , sequence (biology) , process (computing) , visual search , association (psychology) , limit (mathematics) , data set , function (biology) , eye tracking , video tracking , data association , data mining , artificial intelligence , mathematics , video processing , telecommunications , mathematical analysis , philosophy , epistemology , biology , probabilistic logic , genetics , programming language , operating system , evolutionary biology
Abstract In this article, an efficient and novel approach for video data association is developed. This new method is formulated as a search across the hypotheses space defined by the possible association among tracks and detections, carried out for each frame of a video sequence. The full data association problem in visual tracking is formulated as a combinatorial hypotheses search with a heuristic evaluation function taking into account structural and specific information such as distance, shape, color, etc. To guarantee real‐time performance, a time limit is set for the search process explore alternative solutions. This time limit defines the upper bound of the number of evaluations depending on search algorithm efficiency. Estimation distribution algorithms are proposed as an efficient evolutionary computation technique to search in this hypothesis space. Finally, an exhaustive comparison of the performance of alternative algorithms is carried out considering complex representative situations in real video sets. © 2009 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 19, 208–220, 2009