Determination of Optical Flow and its Discontinuities using Non-Linear Diffusion

A new method for optical flow computation by means of a coupled set of non-linear diffusion equations is presented. This approach integrates the classical differential approach with the correlation type of motion detectors. A measure of inconsistency within the optical flow field which indicates optical flow boundaries. This information is fed back to the optical flow equations in a non-linear way and allows the flow field to be reconstructed while preserving the discontinuities. The whole scheme is also applicable to stereo matching. The model is applied to a set of synthetic and real image sequences to illustrate the behaviour of the coupled diffusion equations.

[1]  Shahriar Negahdaripour,et al.  A generalized brightness change model for computing optical flow , 1993, 1993 (4th) International Conference on Computer Vision.

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

[3]  Yee-Hong Yang,et al.  Experimental evaluation of motion constraint equations , 1991, CVGIP Image Underst..

[4]  David J. Fleet,et al.  Performance of optical flow techniques , 1992, Proceedings 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[5]  Alessandro Verri,et al.  Computing optical flow from an overconstrained system of linear algebraic equations , 1990, [1990] Proceedings Third International Conference on Computer Vision.

[6]  Hans-Hellmut Nagel,et al.  Displacement vectors derived from second-order intensity variations in image sequences , 1983, Comput. Vis. Graph. Image Process..

[7]  Jitendra Malik,et al.  Scale-Space and Edge Detection Using Anisotropic Diffusion , 1990, IEEE Trans. Pattern Anal. Mach. Intell..

[8]  Jayant Shah A nonlinear diffusion model for discontinuous disparity and half-occlusions in stereo , 1993, Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.

[9]  Janet Aisbett,et al.  Optical Flow with an Intensity-Weighted Smoothing , 1989, IEEE Trans. Pattern Anal. Mach. Intell..

[10]  Luc Van Gool,et al.  Image enhancement using coupled anisotropic diffusion equations , 1993 .

[11]  Jayant Shah Segmentation by nonlinear diffusion , 1991, Proceedings. 1991 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[12]  Hans-Hellmut Nagel,et al.  An Investigation of Smoothness Constraints for the Estimation of Displacement Vector Fields from Image Sequences , 1983, IEEE Transactions on Pattern Analysis and Machine Intelligence.