The virtual time domain depth estimation of stereo-scopic sequence using optical flow

In this paper we present an efficient technique for the stereoscopic video sequence of robot vision, which yields a fast and acceptable solution for the path planning of the robot. To derive the depth information in the two-camera vision system the exploit of the relative geometric discrepancies between two scenes should be made. But finding the corresponding points by using the technique like dynamic programming takes a lot of times. We developed a fast depth estimation algorithm using the optical flow based on the method by Horn and Schunck. The merit of this scheme is that the computational burden can be greatly reduced while obtaining a reasonable solution.

[1]  Michael J. Black,et al.  Estimating Optical Flow in Segmented Images Using Variable-Order Parametric Models With Local Deformations , 1996, IEEE Trans. Pattern Anal. Mach. Intell..

[2]  Milan Sonka,et al.  Image Processing, Analysis and Machine Vision , 1993, Springer US.

[3]  Joseph S.-C. Yuan A general photogrammetric method for determining object position and orientation , 1989, IEEE Trans. Robotics Autom..

[4]  Berthold K. P. Horn Robot vision , 1986, MIT electrical engineering and computer science series.

[5]  Berthold K. P. Horn,et al.  Determining Optical Flow , 1981, Other Conferences.

[6]  Allan D. Jepson,et al.  Simple method for computing 3D motion and depth , 1990, [1990] Proceedings Third International Conference on Computer Vision.

[7]  Kai-Tai Song,et al.  Fast optical flow estimation and its application to real-time obstacle avoidance , 2001, Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164).

[8]  P. Anandan,et al.  A computational framework and an algorithm for the measurement of visual motion , 1987, International Journal of Computer Vision.

[9]  Hassan Foroosh A closed-form solution for optical flow by imposing temporal constraints , 2001, Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205).