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We address the problem of single-image geo-calibration, in which an estimate of the geographic location, viewing direction and field of view is sought for the camera that captured an image. The dominant approach to this problem is to match features of the query image, using color and texture, against a reference database of nearby ground imagery. However, this fails when such imagery is not available...
In this paper, we propose a robust probability based sparse method to solve single sample face recognition, which harvests the advantages of both local and global representation. Different from previous sparse representation methods that generate sparse coefficients by 𝑙1, we produce sparse class probability distribution by proposing a multi-phase sparse probability (MSP) framework. To create class...
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