Robust event detection by radial reach filter (RRF)

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. And when the brightness difference between events and a background is small, it cannot detect the difference. In order to solve such kind of problems, we propose the RRF which evaluates a local texture and realize robust event detection. The experiment using the real image shows the effectiveness of the proposed methods. Furthermore, the experiment using all-directional image from a stereo omni-directional system (SOS) shows the possibility of the application to an environment-monitoring system etc.