DocumentCode :
1997192
Title :
Implementing motion Markov detection on general purpose processor and associative mesh
Author :
Denoulet, J. ; Mostafaoui, G. ; Lacassagne, L. ; Mérigot, A.
Author_Institution :
Inst. d´´Electronique Fondamentale, Univ. Paris Sud, France
fYear :
2005
fDate :
4-6 July 2005
Firstpage :
288
Lastpage :
293
Abstract :
We present a robust implementation of a motion detection algorithm based on a Markovian relaxation both on general purpose processors, and on a specialized architecture, the associative mesh. The mesh architecture is an instance of the associative nets model targeting real time execution of low level image algorithms and vision-SoC implementation. The algorithm implementation on both architectures is described, and also the required optimizations to speedup the execution.
Keywords :
Markov processes; associative processing; computer vision; motion estimation; real-time systems; system-on-chip; associative mesh; associative nets model; general purpose processor; low level image algorithms; motion Markov detection; real time execution; speedup; vision-SoC implementation; Bandwidth; Circuit topology; Color; Image converters; Image motion analysis; Image processing; Instruments; Markov random fields; Motion detection; Robustness; Markov Random Field.; SIMD; Vision-SoC; associative nets model; motion detection;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Architecture for Machine Perception, 2005. CAMP 2005. Proceedings. Seventh International Workshop on
Print_ISBN :
0-7695-2255-6
Type :
conf
DOI :
10.1109/CAMP.2005.31
Filename :
1508200
Link To Document :
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