Automatic extraction and localization of multiple moving objects with stereo camera in motion

In this paper, we propose a technique for automatic extraction and localization of multiple moving objects captured by a moving stereo camera. Depth information obtained from the stereo matching is applied to initialize a background mask which is refined further by clustering optical flow. Simultaneous estimate for camera motion is also obtained and video frames are compensated accordingly. Refined background mask is used to model displaced frame difference (DFD) of the background. The objects are detected as outliers to this model. We also present a region boundary based change detection approach for frame difference. This approach assures change detection for uniform intensity regions. Finally we present experimental results for indoor and outdoor stereo video sequences captured with moving camera.