Bilayer segmentation augmented with future evidence

Authors:
Silvio Ricardo Rodrigues Sanches;Valdinei Freire da Silva;Romero Tori
Affiliations:
Escola Politécnica, Universidade de São Paulo, São Paulo, SP, Brazil;Escola de Artes, Ciências e Humanidades da Universidade de São Paulo, São Paulo, SP, Brazil;Escola Politécnica, Universidade de São Paulo, São Paulo, SP, Brazil
Venue:
ICCSA'12 Proceedings of the 12th international conference on Computational Science and Its Applications - Volume Part II
Year:
2012

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Abstract

This paper presents an algorithm that augments a previous model known in the literature for the automatic segmentation of monocular videos into foreground and background layers. The original model fuses visual cues such as color, contrast, motion and spatial priors within a Conditional Random Field. Our augmented model makes use of bidirectional motion priors by exploiting future evidence. Although our augmented model processes more data, it does so with the same time performance of the original model. We evaluate the augmented model within ground truth data and the results show that the augmented model produces better segmentation.