A Pixel Dissimilarity Measure That Is Insensitive to Image Sampling
IEEE Transactions on Pattern Analysis and Machine Intelligence
International Journal of Computer Vision
Depth Discontinuities by Pixel-to-Pixel Stereo
International Journal of Computer Vision
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
Stereo Matching Using Belief Propagation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Near Real-Time Reliable Stereo Matching Using Programmable Graphics Hardware
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Stereo Correspondence by Dynamic Programming on a Tree
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Accurate and Efficient Stereo Processing by Semi-Global Matching and Mutual Information
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Adaptive Support-Weight Approach for Correspondence Search
IEEE Transactions on Pattern Analysis and Machine Intelligence
Efficient Belief Propagation for Early Vision
International Journal of Computer Vision
Stereo Vision in Structured Environments by Consistent Semi-Global Matching
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Region-Tree Based Stereo Using Dynamic Programming Optimization
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
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
High-Quality Real-Time Stereo Using Adaptive Cost Aggregation and Dynamic Programming
3DPVT '06 Proceedings of the Third International Symposium on 3D Data Processing, Visualization, and Transmission (3DPVT'06)
Stereo for Image-Based Rendering using Image Over-Segmentation
International Journal of Computer Vision
International Journal of Computer Vision
Curious George: An attentive semantic robot
Robotics and Autonomous Systems
Little Ben: The Ben Franklin Racing Team's entry in the 2007 DARPA Urban Challenge
Journal of Field Robotics - Special Issue on the 2007 DARPA Urban Challenge, Part II
IEEE Transactions on Pattern Analysis and Machine Intelligence
Real-Time Stereo Vision: Making More Out of Dynamic Programming
CAIP '09 Proceedings of the 13th International Conference on Computer Analysis of Images and Patterns
Local stereo matching using geodesic support weights
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
A fast stereo matching algorithm suitable for embedded real-time systems
Computer Vision and Image Understanding
Accurate hardware-based stereo vision
Computer Vision and Image Understanding
A New Tree Structure for Weighted Dynamic Programming Based Stereo Algorithm
ICIG '11 Proceedings of the 2011 Sixth International Conference on Image and Graphics
A fast line segment based dense stereo algorithm using tree dynamic programming
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part III
Surfaces with occlusions from layered stereo
IEEE Transactions on Pattern Analysis and Machine Intelligence
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In recent years, stereo matching based on dynamic programming (DP) has been widely studied and various tree structures are proposed to improve the matching accuracy. However, previous DP-based algorithms do not incorporate all the smoothness functions determined by the edges between the adjacent pixels in the image, which will usually lead to lower matching accuracies. In this paper, we propose a novel stereo matching algorithm based on weighted dynamic programming on a single-direction four-connected (SDFC) tree. The SDFC tree structure is a new tree structure which includes all the edges in the image and the disparity of a pixel can be affected by all the edges in the image. However, in the SDFC tree, conventional DP-based algorithms will make the pixels that are far away from the root node provide higher energy than the nearby pixels, which will decrease the matching accuracy. So, the weighted dynamic programming approach is proposed to optimize the energy function on the new tree structure, and all the pixels in the SDFC tree are treated equivalently. Dynamic programming in the SDFC tree of every pixel in the image separately is very time-consuming, so a fast DP optimization method is designed for the SDFC tree, which reduces the computational complexity of the proposed weighted DP algorithm to 12 times of conventional DP based algorithm. Experiments show that our algorithm not only produces quite smooth and reasonable disparity maps which are close to the state-of-the-art results, but also can be implemented quite efficiently. Performance evaluations on the Middlebury data set show that our method ranks top in all the DP-based stereo matching algorithms, even better than the algorithms that apply segmentation techniques. Experimental results in an unmanned ground vehicle (UGV) test bed show that our algorithm gets very good matching results in different outdoor conditions, even on the asphaltic road which is considered to be textureless. This illustrates the robustness of our algorithm.