Occlusion is one of the challenging problems in stereo. In this paper, we solve the problem in a segment-based style. Both images are segmented, and we propose a novel patchbased stereo algorithm that cuts the segments of one image using the segments of the other, and handles occlusion areas in a proper way. A symmetric graph-cuts optimization framework is used to find correspondence and occlusions simultaneously. The experimental results show superior performance of the proposed algorithm, especially on occlusions, untextured areas and discontinuities.

Many traditional stereo correspondence methods emphasized on utilizing epipolar constraint and ignored the information embedded in inter-epipolar lines. Actually some researchers have already proposed several grid-based algorithms for fully utilizing information embodied in both intra-and inter-epipolar lines. Though their performances are greatly improved, they are very time-consuming. The new graph-cut and believe-propagation methods have made the grid-based algorithms more efficient, but time-consuming still remains a hard problem for many applications. Recently, a tree dynamic programming algorithm is proposed. Though the computation speed is much higher than that of grid-based methods, the performance is degraded apparently. We think that the problem stems from the pixel-based tree construction. Many edges in the original grid are forced to be cut out, and much information embedded in these edges is thus lost. In this paper, a novel line segment based stereo correspondence algorithm using tree dynamic programming (LSTDP) is presented. Each epipolar line of the reference image is segmented into segments first, and a tree is then constructed with these line segments as its vertexes. The tree dynamic programming is adopted to compute the correspondence of each line segment. By using line segments as the vertexes instead of pixels, the connection between neighboring pixels within the same region can be reserved as completely as possible. Experimental results show that our algorithm can obtain comparable performance with state-of-the-art algorithms but is much more time-efficient.

Abstract-A novel patch-based correspondence model is presented in this paper. Many segment-based correspondence approaches have been proposed in recent years. Untextured pixels and boundaries of discontinuities are imposed with hard constraints by the discontinuity assumption that large disparity variation only happens at the boundaries of segments in the above approaches. Significant improvements on performance of untextured and discontinuity area have been reported. But, the performance near occlusion is not satisfactory because a segmented region in one image may be only partially visible in the other one. To solve this problem, we utilize the observation that the shared edge of a visible area and an occluded area corresponds to the discontinuity in the other image. So, the proposed model conducts color segmentation on both images first and then a segment in one image is further cut into smaller patches corresponding to the boundaries of segments in the other when it is assigned with a disparity. Different visibility of patches in one segment is allowed. The uniqueness constraint in a segment level is used to compute the occlusions. An energy minimization framework using graph-cuts is proposed to find a global optimal configuration including both disparities and occlusions. Besides, some measurements are taken to make our segment-based algorithm suffer less from violation of the discontinuity assumption. Experimental results have shown superior performance of the proposed approach, especially on occlusions, untextured areas, and near discontinuities.

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An explicit process model is vital in business processes. However, it is complicated and time consuming to create a workflow design. Also discords usually occur between the perceived management processes and the actual workflow processes. Under this condition, the process discovery techniques emerge. The aim is to rebuild a workflow model (e.g. a Petri net) of a business process based on the execution log. The model should give an abstract representation of the system and reproduce the log. This model can be further applied for process redesign/improvement and performance/reliability evaluation. In this paper, we present a new algorithm derived from α-algorithm for process discovery in term of Petri nets, where statistic long distance causal relationship is taken into consideration. Also this algorithm covers some shortages in α-algorithm.