Illumination invariant stationary object detection

A real-time system for the detection and tracking of moving objects that becomes stationary in a restricted zone. A new pixel classification method based on the Segmentation History Image (SHI) is used to identify stationary objects in the scene. These objects are then tracked using a novel adaptive edge orientation based tracking method. Experimental results have shown that the tracking technique gives more than a 95% detection success rate, even if objects are partially occluded. The tracking results, together with the historic edge maps, are analyzed to remove objects that are no longer stationary or are falsely identified as foreground regions due to sudden changes in the illumination conditions. The technique has been tested on over seven hours of video recorded at different locations and time of day, both outdoors and indoors. The results obtained are compared with other available state of the art methods.