Analysis of Optical Flow Estimation Using Epipolar Plane Images

摘要

Image flow, the apparent motion of brightness patterns on the image plane, canprovide important visual information such as distance, shape, surface orientation, and boundaries. It can be determined by either feature tracking or spatio-temporal analysis. The authors consider spatio-temporal methods, and show how differential range can be estimated from time-space imagery. The authors generate a time-space image by considering only one scan line of the image obtained from a camera moving in the horizontal direction at each time interval. At the next instant of time, the authors shift the previous line up by one pixel, and obtain another line from the image. The authors continue the procedure to obtain a time-space image, where each horizontal line represents the spatial relationship of the pixels, and each vertical line the temporal relationship. Each feature along the horizontal scan line generates an edge in the time-space image, the slope of which depends upon the distance of the feature from the camera. The authors apply two mutually perpendicular edge operators to the time-space image, and determine the slope of each edge. The authors show that this corresponds to optical flow. The authors use the result to obtain the differential range, and show how this can be implemented on the Pipelined Image Processing Engine (PIPE). The authors use a simple technique to calibrate the camera and show how the depth can be obtained from optical flow. The authors provide a statistical analysis of the results of 3-D reconstruction of the scenes using optical flow determined from 3x3, 5x5, and 7x7 edge operators.