Fast Moving Object Detection from Overlapping Cameras

In this work, we address the problem of moving object detection from overlapping cameras. We based on homographic transformation of the foreground information from multiple cameras to reference image. We introduce a new algorithm based on Codebook to get each single views foreground information. This method integrates a region based information into the original codebook algorithm and uses CIE L*a*b* color space information. Once the foreground pixels are detected in each view, we approximate their contours with polygons and project them into the ground plane (or into the reference plane). After this, we fuse polygons in order to obtain foreground area. This fusion is based on geometric properties of the scene and on the quality of each camera detection. Assessment of experiments using public datasets proposed for the evaluation of single camera object detection demonstrate the performance of our codebook based method for moving object detection in single view. Results using multi-camera open dataset also prove the efficiency of our multi-view detection approach.