Abstract
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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Notes
- 1.
General-purpose computing on graphics processing.
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This research was partially supported by projects TIN2015-69542-C2-1-R and MTM2014-57158-R.
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Alcaín, E., Muñoz, A.I., Ramírez, I., Schiavi, E. (2019). Modelling Sparse Saliency Maps on Manifolds: Numerical Results and Applications. In: García Guirao, J., Murillo Hernández, J., Periago Esparza, F. (eds) Recent Advances in Differential Equations and Applications. SEMA SIMAI Springer Series, vol 18. Springer, Cham. https://doi.org/10.1007/978-3-030-00341-8_10
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