|Conference/Proceedings||IEEE Int. Conf. on Image Processing (ICIP '05)|
|Author(s)||Jang-Heon Kim, Thomas Sikora|
|Title||Hybrid Recursive Energy-based Method for Robust Optical Flow on Large Motion Fields|
|Abstract||Abstract—We present a new reliable hybrid recursive method|
for optical flow estimation. The method efficiently combines the
advantage of discrete motion estimation and optical flow estimation in a recursive block-to-pixel estimation scheme.
Integrated local and global approaches using the robust statistic
of anisotropic diffusion remove outliers from the estimated
motion field. We separately describe the process with two
frameworks i.e. an incremental updating framework and a robust energy minimization framework. With robust error norms of Perona and Marik anisotropic diffusion, the
formulation usually leads to non-convex optimization problems.
Thus, the solution has many local minima, and convergence to
the global minima is not guaranteed. Our hybrid recursive
energy-based method employs a hierarchical block-to-pixel
estimation concept to prevent this problem. The experimental
results prove the excellent performance on several large motion fields.
|Key words||hybrid recursive method, dense optical flow, discrete motion estimation, block-to-pixel estimation|