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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© 1992 Springer-Verlag Berlin Heidelberg
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Bergen, J.R., Anandan, P., Hanna, K.J., Hingorani, R. (1992). Hierarchical model-based motion estimation. In: Sandini, G. (eds) Computer Vision — ECCV'92. ECCV 1992. Lecture Notes in Computer Science, vol 588. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-55426-2_27
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DOI: https://doi.org/10.1007/3-540-55426-2_27
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