Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/41811
|Title:||Motion smoothing strategies for 2D video stabilization||Authors:||Sánchez, Javier
|UNESCO Clasification:||220990 Tratamiento digital. Imágenes||Issue Date:||2018||Journal:||SIAM Journal on Imaging Sciences||Abstract:||Video stabilization aims at removing the undesirable effects of camera motion by estimating its shake and applying a smoothing compensation. This paper proposes a unified mathematical analysis and classification of existing smoothing strategies. We assume that the apparent velocity induced by the camera is estimated as a set of global parametric models, typically those of a homography. We classify the existing smoothing strategies into compositional and additive methods and discuss their technical issues, particularly the definition of the boundary conditions. Our discussion of the various alternatives leads to clear-cut conclusions. It rules out the global compositional methods in favor of local linear methods and finds the adequate boundary conditions. We also show that the best smoothing strategy yields a scale-space analysis of the camera ego-motion parameters. Analyzing this scale-space on examples, we show how it is highly characteristic of the camera path, permitting us to compute ego-motion frequencies and to detect periodic ego-motions like walking or running.||URI:||http://hdl.handle.net/10553/41811||ISSN:||1936-4954||DOI:||10.1137/17M1127156||Source:||SIAM Journal on Imaging Sciences,v. 11, p. 219-251|
|Appears in Collections:||Artículos|
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