Optical Flow Based on Feature Match and Super Pixel Segmentation

Optical Flow estimation is used to estimate displacement vectors for each pixels in two frames of a video. This displacement vector says how quickly a pixel is moving across the image and direction of movement of each pixel. According to the direction of movement, a color is assigned to each flow vector and intensity of color varies according to the magnitude of velocity. In this paper, optical flow is estimated by using feature match algorithm and super pixel based optical flow estimation. Feature match method is a widely used method for optical flow estimation. The optic flow computation by feature match algorithm is based on the matching between features of patches of adjacent frames in a video. This displacement vectors obtained by feature match algorithm are modified by using super pixel segmentation based optical flow estimation. The best optical flow associated with each superpixel is computed by optimizing a cost function.Super pixel based optical flow estimation improves feature match algorithm and increase the quality of optical flow estimation.