Proceedings of the 1997 symposium on Interactive 3D graphics
Mean Shift: A Robust Approach Toward Feature Space Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms
International Journal of Computer Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multi-camera Scene Reconstruction via Graph Cuts
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part III
A Space-Sweep Approach to True Multi-Image Matching
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
Dense Matching of Multiple Wide-baseline Views
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
High-quality video view interpolation using a layered representation
ACM SIGGRAPH 2004 Papers
Multi-Camera Reconstruction based on Surface Normal Estimation and Best Viewpoint Selection
3DPVT '04 Proceedings of the 3D Data Processing, Visualization, and Transmission, 2nd International Symposium
Efficient Belief Propagation for Early Vision
International Journal of Computer Vision
Segment-Based Stereo Matching Using Belief Propagation and a Self-Adapting Dissimilarity Measure
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 03
Simplified Belief Propagation for Multiple View Reconstruction
3DPVT '06 Proceedings of the Third International Symposium on 3D Data Processing, Visualization, and Transmission (3DPVT'06)
Scene Representation Technologies for 3DTV—A Survey
IEEE Transactions on Circuits and Systems for Video Technology
3-D Time-Varying Scene Capture Technologies—A Survey
IEEE Transactions on Circuits and Systems for Video Technology
Information permeability for stereo matching
Image Communication
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A novel dense depth map estimation algorithm is proposed in order to meet the requirements of N-view plus N-depth representation, which is one of the standardization efforts for the upcoming 3D display technologies. Hence, extraction of multiple depth maps is achieved from multi-view video. Starting from the piecewise planarity assumption of the scene, estimation of 3D structure of the patches, obtained through color-based over-segmentation, is achieved by plane- and angle-sweeping for every view independently. Markov Random Field (MRF) modeling is utilized for each view in pixel-wise manner in order to relax and refine the estimated planar models while incorporating visibility and consistency constraints. In this algorithm, the fusion of multiple depth maps is performed by updating belief values on the observed nodes based on depth and color consistency during the refinement step. The proposed method handles untextured surfaces, as well as depth discontinuities at object boundaries, due to its initial modeling of the scene as piecewise planar regions. The experimental results illustrate reliability and the robustness of the proposed algorithm for different type of scenes.