Abstract
Lucas-Kanade (LK) optical flow algorithm is widely used for moving object detection and tracking by computing the motion vectors of pixels in image sequences. Due to the high computation complexity, optical flow computation is one of the crucial operations in many computer vision applications. This paper presents a low-cost hardware implementation of the LK optical flow algorithm. In particular, we design a low-cost divider used in the matrix inversion, leading to significant reduction in delay and area for calculation of small optical flow vectors. Furthermore, we also design a pyramidal LK optical flow computation unit that can process images of different sizes in order to increase the magnitude range of optical flow vectors.
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