Publication: A generative model for concurrent image retrieval and ROI segmentation
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2012
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Ieee - The Institute Of Electrical And Electronics Engineers, Inc
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Abstract
This paper proposes a probabilistic generative model that concurrently tackles the problems of image retrieval and detection of the region-of-interest (ROI). By introducing a latent variable that classifies the matches as true or false, we specifically focus on the application of geometric constrains to the keypoint matching process and the achievement of robust estimates of the geometric transformation between two images showing the same object. Our experiments in a challenging image retrieval database demonstrate that our approach outperforms the most prevalent approach for geometrically constrained matching, and compares favorably to other state-of-the-art methods. Furthermore, the proposed technique concurrently provides very good segmentations of the region of interest.
Description
Proceedings of: 10th International Workshop on Content-Based Multimedia Indexing (CBMI). Annecy, France, 27-29 June 2012.
Keywords
Image retrieval, Image segmentation
Bibliographic citation
2012 10th International Workshop pon Content- Based Multimedia Indexing (CBMI). (pp. 90-95). IEEE.