Modelling Sparse Saliency Maps on Manifolds: Numerical Results and Applications.
Saliency detection is an image processing task which aims at automatically estimating visually salient object regions in a digital image mimicking human visual attention and eyes fixation. A number of different computational approaches for visual saliency estimation has recently appeared in Computer...
| Autores: | , , , |
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| Tipo de recurso: | capítulo de libro |
| Fecha de publicación: | 2023 |
| País: | España |
| Institución: | Universidad Rey Juan Carlos |
| Repositorio: | BURJC-Digital. Repositorio Institucional de la Universidad Rey Juan Carlos |
| OAI Identifier: | oai:burjcdigital.urjc.es:10115/27262 |
| Acceso en línea: | https://hdl.handle.net/10115/27262 |
| Access Level: | acceso abierto |
| Palabra clave: | Saliency detection and segmentation superpixeles non local total variation on graphs energy minimization primal-dual algorithm |
| Sumario: | Saliency detection is an image processing task which aims at automatically estimating visually salient object regions in a digital image mimicking human visual attention and eyes fixation. A number of different computational approaches for visual saliency estimation has recently appeared in Computer and Artificial Vision. Relevant and new applications can be found everywhere varying from automatic image segmentation and understanding, localization and quantification for biomedical and aerial images to fast video tracking and surveillance. In this contribution, we present a new variational model on finite dimensional manifolds generated by some characteristic features of the data. A Primal-Dual method is implemented for the numerical resolution showing promising preliminary results. |
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