期刊
COMPUTER VISION AND IMAGE UNDERSTANDING
卷 134, 期 -, 页码 1-21出版社
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.cviu.2015.02.008
关键词
Optical flow; Motion estimation; Regularization; Parametric models; Optimization; Feature matching; Occlusions
资金
- France-Biolmaging project - Investissement d'Avenir program
- UMR 144 CNRS of Institut Curie
- OSEO, French State agency for innovation
Optical flow estimation is one of the oldest and still most active research domains in computer vision. In 35 years, many methodological concepts have been introduced and have progressively improved performances, while opening the way to new challenges. In the last decade, the growing interest in evaluation benchmarks has stimulated a great amount of work. In this paper, we propose a survey of optical flow estimation classifying the main principles elaborated during this evolution, with a particular concern given to recent developments. It is conceived as a tutorial organizing in a comprehensive framework current approaches and practices. We give insights on the motivations, interests and limitations of modeling and optimization techniques, and we highlight similarities between methods to allow for a clear understanding of their behavior. (C) 2015 Elsevier Inc. All rights reserved.
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