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http://hdl.handle.net/10553/52767
Título: | Symmetric optical flow | Autores/as: | Alvarez, L Castaño, C. A. García, M. Krissian, K. Mazorra, L. Salgado, A. Sánchez, J. |
Clasificación UNESCO: | 120601 Construcción de algoritmos 120602 Ecuaciones diferenciales 220990 Tratamiento digital. Imágenes 120326 Simulación 120304 Inteligencia artificial |
Palabras clave: | Registration | Fecha de publicación: | 2007 | Editor/a: | 0302-9743 | Publicación seriada: | Lecture Notes in Computer Science | Conferencia: | 11th International Conference on Computer Aided Systems Theory, EUROCAST 2007 | Resumen: | One of the main technique used to recover motion analysis from two images or to register them is variational optical flow, where the pixels of one image are matched to the pixels of the second image by minimizing an energy functional. In the standard formulation of variational optical flow, the estimated motion vector field depends on the reference image and is asymmetric. However, in most application the solution should be independent of the reference image. Only few symmetrical formulations of the optical flow has been proposed in the literature, where the solution is constraint to be symmetric using a combination of the flow in both directions. We propose a new symmetric variational formulation of the optical flow problem, where the flow is naturally symmetric. Results on the Yosemite sequence show an improved accuracy of our symmetric flow with respect to standard optical flow algorithm. | URI: | http://hdl.handle.net/10553/52767 | ISBN: | 978-3-540-75866-2 | ISSN: | 0302-9743 | DOI: | 10.1007/978-3-540-75867-9_85 | Fuente: | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)[ISSN 0302-9743],v. 4739 LNCS, p. 676-683 |
Colección: | Actas de congresos |
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