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We consider the problem of how to simultaneously and well correct the over- and under-exposure regions in a single low dynamic range (LDR) image. Recent methods typically focus on global visual quality but cannot well-correct much potential details in extremely wrong exposure areas, and some are also time consuming. In this paper, we propose a fast and detail-enhanced correction method based on automatic...
In this paper, we present a method to extract moving objects in monocular image sequences. The proposed method is based on graph cuts defined on a spatio-temporal region adjacency graph (RAG). First, we initially over-segment each frame in the video, and take the over-segmented regions as the vertices in the 3D spatio-temporal graph. Second, multiple cues are fused together to extract objects accurately...
We propose a new approach to motion segmentation that is based on auto-generated strokes. The novelty of the approach is twofold. First, inspired by recent work of other researchers we formulate the problem as that of interactive segmentation. Instead of inputting the strokes by the user, the strokes in our approach are auto-generated. The second novelty of the paper is formulation in which, unlike...
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