3D reconstruction with automatic foreground segmentation from multi-view images acquired from a mobile device

2Citations
Citations of this article
5Readers
Mendeley users who have this article in their library.
Get full text

Abstract

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.

Cite

CITATION STYLE

APA

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

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free