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Moving obstacles have potentially higher risks of collision than stationary obstacles in traffic. Therefore, it is meaningful to detect moving obstacles by sensors equipped on a car for drive assistance applications. We propose two algorithms to detect moving obstacles using camera(s) depending on the relative motion between cameras and obstacles. Since camera(s) moves along with the subjective car, it is challenging to find actually moving obstacles in image sequences. The first algorithm identifies moving obstacle regions in images by checking conflicts between image motion and epipolar constraint when obstacles move in different direction from cameras' motion. The second algorithm identifies moving obstacle regions in images by finding disparity differences between stereo and motion especially when obstacles move in same direction as cameras' motion. Experiments show not only qualitative performance of our detection algorithm, but also quantitative accuracy of egomotion and optical flow estimation in our algorithm.