Multiple view geometry in computer visiond
Multiple view geometry in computer visiond
A Theory of Shape by Space Carving
International Journal of Computer Vision - Special issue on Genomic Signal Processing
The Visual Hull Concept for Silhouette-Based Image Understanding
IEEE Transactions on Pattern Analysis and Machine Intelligence
Silhouette and stereo fusion for 3D object modeling
Computer Vision and Image Understanding - Model-based and image-based 3D scene representation for interactive visalization
A Comparison and Evaluation of Multi-View Stereo Reconstruction Algorithms
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
Multiview Stereo via Volumetric Graph-Cuts and Occlusion Robust Photo-Consistency
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Point-Cloud-Based Multiview Stereo Algorithm for Free-Viewpoint Video
IEEE Transactions on Visualization and Computer Graphics
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In many multi-view stereo (MVS) algorithms, a point-cloud evolution is performed, based on the matching process. For most of them, an assumption is usually employed for the matching, which indicates that the matching windows have the same shape. This assumption lays a great limit to the quality of the reconstructed result. To improve the point-cloud obtained from other algorithms, and break the limit laid by the regular matching, we propose our refinement method using exact matching. The exact matching enables more accurate matching windows for the points, by taking the normal vector into consideration. By maximizing the exact matching result, the point's coordinate and normal vectors are optimized, and we can thus make the original point-cloud much better.