Motion Field Estimation from Alternate Exposure Images

—Traditional optical flow algorithms rely on consecutive short-exposed images. In this work, we make use of an additional long-exposed image for motion field estimation. Long-exposed images integrate motion information directly in form of motion-blur. With this additional information more robust and accurate motion fields can be estimated. In addition the moment of occlusion can be determined. Considering the basic signal-theoretical problem in motion field estimation, we exploit the fact that long-exposed images integrate motion information to prevent temporal aliasing. A suitable image formation model relates the long-exposed image to preceding and succeeding short-exposed images in terms of dense 2D motion and per-pixel occlusion/disocclusion timings. Based on our image formation model, we describe a practical variational algorithm to estimate the motion field not only for visible image regions but also for regions getting occluded. Results for synthetic as well as real-world...

• Type: Journal
• Year: 2011
• Where: PAMI
• Authors: Anita Sellent, Martin Eisemann, Bastian Goldlücke, Daniel Cremers, Marcus A. Magnor
• Keywords: 2D Motion, Computer Networks, Image Regions, Motion Blur, PAMI 2011