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We present a fast algorithm for achieving motion-based object detection in an image sequence. While in most existing object-detection algorithms, segmentation of the image is done as the first step followed by grouping of segments, the proposed algorithm first uses motion information to identify what we call a region of interest. Segmentation (which is computationally very expensive) is done only within a square of interest (whose area is smaller than that of the entire image), which ensures a speed up. The segments are then combined to obtain the final segment, which closely matches the shape of the object to be detected. Since the square of interest is always smaller than the image, the proposed algorithm is 2 to 4 times faster than every existing algorithm for object detection. In terms of the accuracy with which a desired object is detected, the performance of our algorithm is comparable to existing algorithms.