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