Hardware acceleration for tracking by computing low-order geometric moments

J. Vijverberg, P. D. With
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引用次数: 5

Abstract

With the growing number of video content analysis applications, efficient implementation has become increasingly important. Video-object tracking using image moments is an important subtask in video-content analysis content algorithms. In this paper, we will present a method of accelerating the computation of geometrical moments and the resulting moment engine to a throughput of 130-fps. Furthermore, the effect of the accelerator on the performance of two object-tracking applications in a multi-processor platform will be evaluated. The conclusion is that the moment engine is relatively inexpensive in terms of required gate area, but its integration efficiency into a domain-specific multi-processor platform remains to be further analyzed.
通过计算低阶几何矩实现跟踪的硬件加速
随着视频内容分析应用的不断增多,高效的实现变得越来越重要。利用图像矩跟踪视频目标是视频内容分析算法中的一个重要子任务。在本文中,我们将提出一种加速几何矩计算的方法,并将产生的矩引擎的吞吐量提高到130-fps。此外,还将评估加速器对多处理器平台上两个目标跟踪应用程序性能的影响。结论是,从所需的栅极面积来看,矩引擎相对便宜,但其在特定领域的多处理器平台中的集成效率有待进一步分析。
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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