Motion Field Estimation from Alternate Exposure Images Anita Sellent, Martin Eisemann, Bastian Goldlücke, Daniel Cremers, Marcus Magnor

Anita Sellent, Martin Eisemann, Bastian Goldlücke, Daniel Cremers, and Marcus Magnor: "Motion Field Estimation from Alternate Exposure Images", IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), vol. 33, no. 8, pp. 1577–1589, August 2011. Part of project "Alternate Exposure Imaging". [pdf] [bib]

Abstract

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 scenes demonstrate the validity of the approach.

TU Braunschweig - Fakultät für Mathematik und Informatik - Computer Graphics - Publications - Motion Field Estimation from Alternate Exposure Images