A conditional random field model for image parsing

Authors:
Lingling Li;Taisong Jin;Guohua Zhang
Affiliations:
Zhengzhou Institute of Aeronautical, Zhengzhou, China;Xiamen University, Xiamen, china;Science and technology on electro-optic control laboratory, Luoyang, china
Venue:
ICIMCS '10 Proceedings of the Second International Conference on Internet Multimedia Computing and Service
Year:
2010

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Abstract

The paper presented a novel discriminative model for efficient and effective recognition and simultaneous semantic segmentation of objects in images. The images are first segmented to give 'super-pixels'. Then the super-pixels are merged together and semantically labeled using a Condition Random Field (CRF) model. The use of a conditional random field allows us to incorporate different cues in a single unified model. The test on the standard dataset shows that compared with existing systems, the proposed system produces a detailed segmentation of a test image into coherent regions, with a semantic label associated with each region in the image.