Proceedings of the 27th annual conference on Computer graphics and interactive techniques
The Visual Hull Concept for Silhouette-Based Image Understanding
IEEE Transactions on Pattern Analysis and Machine Intelligence
ICCV '99 Proceedings of the International Workshop on Vision Algorithms: Theory and Practice
Photorealistic Scene Reconstruction by Voxel Coloring
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
3-D Object Reconstruction Using Spatially Extended Voxels and Multi-Hypothesis Voxel Coloring
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 1
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
A survey of motion-parallax-based 3-D reconstruction algorithms
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
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Three-dimensional (3-D) object reconstruction from multiple two-dimensional (2-D) images is one of the most important topics in computer vision. In this paper, we review two common methods for 3-D object reconstruction: shape from silhouette and voxel coloring. The shape from silhouette method recovers the 3-D shape of an object from silhouette images. This method is based on the visual hull that is formed by intersecting volumes from silhouette cones. Voxel coloring is another reconstruction method that uses the measure of color consistency to build a 3-D model of the object. In this paper, we present a different 3-D object reconstruction algorithm, where the initial 3-D object that was generated by the visual hull is carved to represent details of the 3-D object using color consistency. In this algorithm, visibility checking is proposed to reconstruct the 3-D object well. Experimental results show that the proposed algorithm reconstructs natural 3-D models efficiently.