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Merit maximization approach to binocular vision using dynamicprogramming,

机译:利用动态规划的双目视觉优点最大化方法,

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Abstract: In this paper, we cast stereo matching as a problem in merit maximization. This is achieved by the formulation of a merit function which influences the similarity between primitives in the right and left images and the mutual dependency between primitives. Stereo matching is done by finding the `best' paths that maximize the merit function. This is handled by using the dynamic programming technique. With this algorithm, a global optimum matching can be obtained. We give a mathematical description for the merit function and the algorithm has been implemented. The experimental results are presented to show the efficacy of the proposed stereo matching method. !10
机译:摘要:在本文中,我们将立体声匹配视为价值最大化中的一个问题。这是通过制定价值函数来实现的,该函数会影响左右图像中图元之间的相似性以及图元之间的相互依赖性。立体匹配是通过找到使性能函数最大化的“最佳”路径来完成的。这是通过使用动态编程技术来处理的。使用该算法,可以获得全局最优匹配。我们给出了价值函数的数学描述,该算法已经实现。实验结果表明,提出的立体声匹配方法是有效的。 !10

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