Abstract
This paper presents a multi-view stereo algorithm for piecewise planar scene reconstruction and optimization. Our segmentation-based reconstruction algorithm is iterative to minimize our defined energy function, consisting of reconstruction, refinement and optimization steps. The first step is a plane initialization to allow each segment to have a set of initial plane candidates. Then a plane refinement based on non-linear optimization improves the accuracy of the segment planes. Finally a plane optimization with a segment-adjacency graph leads to optimal segment planes, each of which is chosen among possible plane candidates by evaluating its relationship with adjacent planes in 3D. This algorithm yields better accuracy and performance, compared to the previous algorithms described in this paper. The results show our method is suitable for outdoor or aerial urban scene reconstruction, especially in wide baselines and images with textureless regions.
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Kim, H., Xiao, H., Max, N. (2013). Piecewise Planar Scene Reconstruction and Optimization for Multi-view Stereo. In: Lee, K.M., Matsushita, Y., Rehg, J.M., Hu, Z. (eds) Computer Vision – ACCV 2012. ACCV 2012. Lecture Notes in Computer Science, vol 7727. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37447-0_15
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DOI: https://doi.org/10.1007/978-3-642-37447-0_15
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