We propose a novel foreground object segmentation algorithm for a silhouette-based 3D reconstruction system. Our system requires several multi-view images as input to reconstruct a complete 3D model. The proposed foreground segmentation algorithm is based on graph-cut optimization with the energy function developed for planar background assumption. We parallelize parts of our program with GPU programming. The 3D reconstruction system consists of camera calibration, foreground segmentation, visual hull reconstruction, surface reconstruction, and texture mapping. The proposed 3D reconstruction process is accelerated with GPU implementation. In the experimental result, we demonstrate the improved accuracy by using the proposed segmentation method and show the reconstructed 3D models computed from several image sets.
CITATION STYLE
Kuo, P. C., Chen, C. A., Chang, H. C., Su, T. F., & Lai, S. H. (2015). 3D reconstruction with automatic foreground segmentation from multi-view images acquired from a mobile device. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9010, pp. 352–365). Springer Verlag. https://doi.org/10.1007/978-3-319-16634-6_26
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