Bilayer Segmentation Augmented with Future Evidence

Author(s)

Rodrigues Sanches, Silvio Ricardo ; da Silva, Valdinei Freire ; Tori, Romero ; Murgante, B ; Gervasi, O ; Misra, S ; Nedjah, N ; Rocha, AMAC ; Taniar, D ; Apduhan, BO

• Document type: Journal article
• Source: COMPUTATIONAL SCIENCE AND ITS APPLICATIONS - ICCSA 2012, PT II; v. 7334, p. 13-pg., 2012-01-01.

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. (AU)

• FAPESP's process: 11/19280-8 - CogBot: integrating perceptual information and semantic knowledge in cognitive robotics
• Grantee: Anna Helena Reali Costa
• Support Opportunities: Regular Research Grants