Hierarchical model-based motion estimation

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Abstract

This paper describes a hierarchical estimation framework for the computation of diverse representations of motion information. The key features of the resulting framework (or family of algorithms) are a global model that constrains the overall structure of the motion estimated, a local model that is used in the estimation process, and a coarse-fine refinement strategy. Four specific motion models: affine flow, planar surface flow, rigid body motion, and general optical flow, are described along with their application to specific examples.

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Bergen, J. R., Anandan, P., Hanna, K. J., & Hingorani, R. (1992). Hierarchical model-based motion estimation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 588 LNCS, pp. 237–252). Springer Verlag. https://doi.org/10.1007/3-540-55426-2_27

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