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A split-and-merge framework based on a maximum variance criterion is proposed for disparity clustering. The proposed algorithm transforms low-level stereo disparity information to mid-level planar surface information which can be used further to carry out high-level computer vision tasks such as shape classification. Unlike conventional clustering, the proposed algorithm assumes that the number of...
An efficient and robust framework for two-view multiple structure and motion segmentation is proposed. To handle this otherwise recursive problem, hypotheses for the models are generated by local sampling. Once these hypotheses are available, a model selection problem is formulated which takes into account the hypotheses likelihoods and model complexity. An explicit model for outliers is also added...
An iterative split-and-merge framework for the segmentation of planar surfaces in the disparity space is presented. Disparity of a scene is modeled by approximating various surfaces in the scene to be planar. In the split phase, the number of planar surfaces along with the underlying plane parameters is assumed to be known from the initialization or from the previous merge phase. Based on these parameters,...
Perforator flaps have been widely used in plastic surgery for greater survivability and decreased morbidity. However, quantitative analysis of three dimensional (3D) blood flow direction and location has not been examined yet. In this paper, we reconstruct the 3D vascular tree with the incorporation of temporal information (4D) from contrast-agent propagation. A novel computational framework by adopting...
Understanding the motility of subcellular particles like organelles, vesicles, or mRNAs is critical to understand how cells regulate delivery of specific proteins from the site of synthesis to the site of action. The goal of this paper is to present a framework of feature selection, matching, and evaluation for the segmentation and tracking of green fluorescent protein (GFP) labeled subcellular structures...
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