Implementing motion Markov detection on general purpose processor and associative mesh

J. Denoulet, Ghilès Mostafaoui, L. Lacassagne, A. Mérigot
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引用次数: 15

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.
在通用处理器和关联网格上实现运动马尔可夫检测
我们提出了一种基于马尔可夫松弛的运动检测算法的鲁棒实现,该算法既适用于通用处理器,也适用于专用架构,即关联网格。网格结构是关联网络模型的一个实例,目标是实时执行低级图像算法和视觉soc实现。描述了两种体系结构上的算法实现,以及加快执行所需的优化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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