Abstract
Recently, by means of the cheap GPUs and appropriate parallel algorithms, it is possible to perform real-time 3-D reconstruction. In this paper, a real-time 3-D surface reconstruction system has been set up to achieve dense geometry reconstruction from multiple cameras. Pose of the cameras are accurately estimated with the help of a self-calibration system. The depth map of the recorded scene is computed by means of a dense multi-view stereo algorithm. Matching cost aggregation and global optimization method are used to obtain the accurate depth values. We merge our works into the Meshlab, where the depth information is used for generating the surface model. High-quality results are finally presented to prove the feasibility of our system and reconstruction algorithms.
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Acknowledgments
This work is supported by the National High Technology Research and Development Program of China under Grant No. 2012AA011903, and by Postgraduate Research Innovation Projects of Jiangsu Province of China under Grant No. CXLX 13_158.
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Liu, Y., Gong, H., Zhang, Z. (2015). Real–Time 3-D Surface Reconstruction from Multiple Cameras. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2015. Lecture Notes in Computer Science(), vol 9475. Springer, Cham. https://doi.org/10.1007/978-3-319-27863-6_9
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DOI: https://doi.org/10.1007/978-3-319-27863-6_9
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