Fast and robust progressive stereo reconstruction by symmetry guided fusion

H. Zhang, S. Negahdaripour
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引用次数: 10

Abstract

Acquiring photorealistic 3D computer models of objects has been a very active research area with most important applications in Virtual Reality and Multimedia systems. This paper deals with a generalization of dense stereo reconstruction, which forms the basis for incremental fusing of stereo sequences to construct a 3-D model of underwater natural objects. The approach is fast and robust. Initialized with a set of robust feature matches over the left and right images, efficient left-to-right and right-to-left stereo matching are carried out by match propagation [Q. Chen, G. Medioni, 1999]. Symmetry relation between the two stereo matchings is utilized to guide robust fusion. Where a large difference exists between the two dense stereo reconstructions, it is most probable that at least one estimate is erroneous, thus is rejected. Conversely, small differences are expected because of the discrete nature of the disparity values. When fused these two estimates, better results are expected. Experimental results demonstrate the efficacy of the proposed approach.
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基于对称制导融合的快速鲁棒渐进立体重建
获取物体的逼真三维计算机模型一直是一个非常活跃的研究领域,在虚拟现实和多媒体系统中有着重要的应用。本文对密集立体重建进行了推广,为立体序列增量融合构建水下自然物体三维模型奠定了基础。该方法快速且健壮。在左右图像上初始化一组鲁棒特征匹配,通过匹配传播进行有效的从左到右和从右到左的立体匹配[Q]。陈,G. Medioni, 1999]。利用两种立体匹配之间的对称关系指导鲁棒融合。当两个密集立体重建之间存在较大差异时,很可能至少有一个估计是错误的,因此被拒绝。相反,由于视差值的离散性,预计会有较小的差异。当将这两种估计融合在一起时,预期会得到更好的结果。实验结果证明了该方法的有效性。
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