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Search-based structured prediction methods have shown promising successes in both computer vision and natural language processing recently. However, most existing search-based approaches lead to a complex multi-stage learning process, which is ill-suited for scene labeling problems with a high-dimensional output space. In this paper, a stacked learning to search method is proposed to address scene...
We propose a cross-trees structure to perform the non-local cost aggregation for dense stereo matching. The cross-trees structure consists of a horizontal-tree and a vertical-tree. Compared to other spanning trees, the significant superiority of the cross-trees is that the trees' constructions are efficient and independent on any local or global property. Moreover, the trees are exactly unique. By...
In this paper, an effective constraint is proposed to leverage the stereo matching in early vision literature. Firstly, some particular edges are extracted to compose the new smooth constraint by categorizing the color edges into different groups. Then the optimal support windows can be established based on the proposed constraint. Finally, the disparity map would be estimated by using match propagation...
In this paper, we address the problem of stereo matching. Edge information is sufficiently explored in our algorithm to compose the Global Edge Constraint (GEC). By using the GEC, an optimal correlation window for each specific match (i.e. seed match) can be estimated and pixels within the window would be quickly matched with propagation. We evaluate our algorithm with real stereo pairs and both high...
We propose a novel method on stereo matching based on the Global Edge Constraint (GEC) and Graph Cuts. Firstly, the GEC composed of particular image edges is employed to generate the initial disparity maps. And then the reliable disparity maps consistent with the observed data are extracted to construct the data term of the energy function. Finally, we incorporate the GEC as a soft constraint into...
We present a novel method on dense stereo matching; both high accuracy results and a handling of occlusions can be achieved with the edge constraint we prove in this paper. Though a lot of efforts had been made to solve the problems such as occlusions and disparity discontinuities, dense stereo matching is still very challenging in the field of stereo vision. Variable window methods seem to be a good...
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