Robust event detection by radial reach filter (RRF)
Robust event detection by radial reach filter (RRF)
复制标题
通过径向到达滤波器 (RRF) 进行稳健的事件检测
DOI：
10.1109/icpr.2002.1048379
复制
发表时间：
2002
期刊：
影响因子：
--
通讯作者：
Kazuhiko Yamamoto
中科院分区：
文献类型：
--
作者：
Y. Satoh;H. Tanahashi;Caihua Wang;S. Kaneko;Y. Niwa;Kazuhiko Yamamoto
我们提出了一种新的统计措施，强大的事件检测，称为“径向到达过滤器”（RRF）。从时间序列图像中检测新目标（事件）的能力是视觉系统的一个重要问题。检测新目标的常用方法是简单的背景减法，即从背景图像中减去当前图像。然而，简单的背景减除容易受到诸如阴影的照明变化的影响。此外，当事件和背景之间的亮度差很小时，它无法检测到该差异。为了解决这些问题，我们提出了RRF评估的局部纹理，实现了强大的事件检测。使用真实的图像的实验表明了所提出方法的有效性。此外，使用来自立体全向系统（SOS）的全向图像的实验显示了应用于环境监测系统的可能性。
We propose a novel statistical measure for robust event detection, called 'Radial Reach filter' (RRF). The capability of detecting new objects (events) from a time-series image is an important problem of vision systems. The usual method of detecting new objects is simple background subtraction, that is to subtract current image from a background image. However, simple background subtraction is susceptible to illumination change such as shadows. Moreover, when the brightness difference between events and a background is small, it cannot detect the difference. In order to solve such problems, we propose the RRF which evaluates a local texture and realizes robust event detection. Experiments using real images show the effectiveness of the proposed methods. Furthermore, an experiment using an all-directional image from a stereo omni-directional system (SOS) shows the possibility of application to an environment-monitoring system.