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Low operational amount silhouette extraction and its application to video understanding based on statistical processing

基于统计处理的低运算量剪影提取及其在视频理解中的应用

基本信息

批准号：
22500162
负责人：
NISHITANI Takao
金额：
$ 2.58万
依托单位：
Tokyo Metropolitan University
依托单位国家：
日本
项目类别：
Grant-in-Aid for Scientific Research (C)
财政年份：
2010
资助国家：
日本
起止时间：
2010 至 2012
项目状态：
已结题

项目摘要

The research project is to establish an only 10% operation amount sight/vision function, compared to the conventional one, in order to give the sight capability to robots as well as mobile terminal, because these applications should be powered by battery cells. Thesight/vision fundamental function is based on the extraction of silhouette of person in a scene. This fundamental function is composed of the clear separation of foreground objects, followed by the elimination of shadows from the foreground objects; both of the functions require tremendous operations in the conventional approach. In order to achieve the target performance, new modification of Multi-scale Reinex and a novel shadow assumption have been employed. The resulted silhouette has also been applied to walk identification trial and shows the effectiveness. In order to show the possibility of battery support applications, foreground segmentation processor has been developed: the result of power dissipation is 150mW for FPGA, equivalently 30mW for ASIC design.

研究项目是建立一个只有10%的操作量的视觉/视觉功能，与传统的相比，为了给机器人和移动终端提供视觉能力，因为这些应用需要由电池供电。视觉基础功能是基于场景中人物轮廓的提取。这个基本功能是由前景物体的清晰分离，其次是消除前景物体的阴影；在传统方法中，这两个函数都需要大量的操作。为了达到目标性能，采用了新的多尺度Reinex修正方法和新的阴影假设。所得到的轮廓也已应用于步行识别试验，并显示了有效性。为了显示电池支持应用的可能性，开发了前景分割处理器：FPGA的功耗结果为150mW， ASIC设计的功耗为30mW。