Estimate Large Motions Using the Reliability-Based Motion Estimation Algorithm |
| |
Authors: | Minglun Gong Yee-Hong Yang |
| |
Affiliation: | (1) Department of Math and Computer Science, Laurentian University, Sudbury, ON, Canada;(2) Department of Computing Science, University of Alberta, Edmonton, AB, Canada |
| |
Abstract: | Detecting and estimating motions of fast moving objects has many important applications. However, most existing motion estimation
techniques have difficulties in handling large motions in the scene. In this paper, we extend our recently proposed reliability-based
stereo vision technique to solving large motion estimation problem. Compared with our stereo vision approach, the new algorithm
removes the constant penalty assumption and explicitly enforces the inter-scanline consistency constraint. The resulting algorithm
can handle sequences that contain large motions and can produce optical flows with 100% density over the entire image domain.
The experimental results indicate that it can generate more accurate optical flows than existing approaches. |
| |
Keywords: | motion estimation optical flow dynamic programming reliability-based dynamic programming |
本文献已被 SpringerLink 等数据库收录! |
|