Fast Approximate Energy Minimization via Graph Cuts
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms
International Journal of Computer Vision
Occlusions, Discontinuities, and Epipolar Lines in Stereo
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume I - Volume I
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Stereo Matching Using Belief Propagation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Estimation of Homogeneous Regions for Segmentation of Textured Images
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 3
What Energy Functions Can Be Minimizedvia Graph Cuts?
IEEE Transactions on Pattern Analysis and Machine Intelligence
An Experimental Comparison of Min-Cut/Max-Flow Algorithms for Energy Minimization in Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Beyond distance measurement: constructing neighborhood similarity for video annotation
IEEE Transactions on Multimedia - Special section on communities and media computing
Overview of FTV (free-viewpoint television)
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
Using One Graph-Cut to Fuse Multiple Candidate Maps in Depth Estimation
CVMP '09 Proceedings of the 2009 Conference for Visual Media Production
Location Discriminative Vocabulary Coding for Mobile Landmark Search
International Journal of Computer Vision
Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
A new diamond search algorithm for fast block-matching motion estimation
IEEE Transactions on Image Processing
A novel four-step search algorithm for fast block motion estimation
IEEE Transactions on Circuits and Systems for Video Technology
IEEE Transactions on Circuits and Systems for Video Technology
Readjusting Unstable Regions to Improve the Quality of High Accuracy Optical Flow
IEEE Transactions on Circuits and Systems for Video Technology
Real-Time and Accurate Stereo: A Scalable Approach With Bitwise Fast Voting on CUDA
IEEE Transactions on Circuits and Systems for Video Technology
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Depth video is vital to the representation of the dynamic 3-D video, which is the fundamental for the rapidly growing 3-D video applications. The issues of accuracy and temporal consistency are the main concerns of the researches on depth videos. In previous works, the stereo matching methods with global optimization can generate accurate and dense depth videos. However, the global optimization is computationally intensive, and the temporal consistency is obtained with difficulty in the optimization procedure. In this paper, a Bayesian framework is proposed to generate accurate and temporal consistent dense depth videos in an efficient way. Firstly, the spatial and temporal correlations in 3-D videos from different viewpoints are used to generate the candidates for depth, and these correlations are further measured by extracted features. These features are adopted to estimate the risk of initial depth in our Bayesian framework. Then, a two-stage decision method is designed to select candidates of depth value in the initial depth map with the minimum risk probability. Finally, depth videos are refined by improved graph cuts algorithm with global optimization. An improved graph construction method is designed and applied on graph cuts algorithm to reduce the number of nodes in graph and thus the complexity of global optimization. The experimental results demonstrate that the proposed algorithm can achieve accurate depth videos with higher efficiency up to 68.14% than traditional methods.