High-precision stereo disparity estimation using HMMF models
Image and Vision Computing
Correspondence as energy-based segmentation
Image and Vision Computing
A proposed stereo matching algorithm for noisy sets of color images
Computers & Geosciences
Object detection by global contour shape
Pattern Recognition
Iterated dynamic programming and quadtree subregioning for fast stereo matching
Image and Vision Computing
Bilayer representation for three dimensional visual communication
Journal of Visual Communication and Image Representation
Fast acquisition of dense depth data by a new structured light scheme
Computer Vision and Image Understanding
A new perceptual organization approach to 3D measuring system based on the fuzzy integral
Image and Vision Computing
Temporal consistent real-time stereo for intelligent vehicles
Pattern Recognition Letters
A fast stereo matching algorithm suitable for embedded real-time systems
Computer Vision and Image Understanding
Extracting dense features for visual correspondence with graph cuts
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Design and hardware implementation of a stereo-matching system based on dynamic programming
Microprocessors & Microsystems
Contour analysis-based matching of ground objects in aerial images
Journal of Computer and Systems Sciences International
Fast and robust semi-local stereo matching using possibility distributions
International Journal of Computational Vision and Robotics
How Accurate Can Block Matches Be in Stereo Vision?
SIAM Journal on Imaging Sciences
A noise-driven paradigm for solving the stereo correspondence problem
MICAI'05 Proceedings of the 4th Mexican international conference on Advances in Artificial Intelligence
Concurrent stereo matching: an image noise-driven model
EMMCVPR'05 Proceedings of the 5th international conference on Energy Minimization Methods in Computer Vision and Pattern Recognition
High-Order differential geometry of curves for multiview reconstruction and matching
EMMCVPR'05 Proceedings of the 5th international conference on Energy Minimization Methods in Computer Vision and Pattern Recognition
A review and evaluation of methods estimating ego-motion
Computer Vision and Image Understanding
Detecting and localising obstacles in front of a moving vehicle using linear stereo vision
Mathematical and Computer Modelling: An International Journal
A new level-set based algorithm for bimodal depth segmentation
ACIVS'12 Proceedings of the 14th international conference on Advanced Concepts for Intelligent Vision Systems
Detecting and reconstructing 3d mirror symmetric objects
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part II
Hierarchical stereo matching based on image bit-plane slicing
ACCV'12 Proceedings of the 11th international conference on Computer Vision - Volume 2
Fast and Accurate Stereo Vision System on FPGA
ACM Transactions on Reconfigurable Technology and Systems (TRETS)
A High Quality Depth Map Upsampling Method Robust to Misalignment of Depth and Color Boundaries
Journal of Signal Processing Systems
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This paper presents a stereo matching algorithm using the dynamic programming technique. The stereo matching problem, that is, obtaining a correspondence between right and left images, can be cast as a search problem. When a pair of stereo images is rectified, pairs of corresponding points can be searched for within the same scanlines. We call this search intra-scanline search. This intra-scanline search can be treated as the problem of finding a matching path on a two-dimensional (2D) search plane whose axes are the right and left scanlines. Vertically connected edges in the images provide consistency constraints across the 2D search planes. Inter-scanline search in a three-dimensional (3D) search space, which is a stack of the 2D search planes, is needed to utilize this constraint. Our stereo matching algorithm uses edge-delimited intervals as elements to be matched, and employs the above mentioned two searches: one is inter-scanline search for possible correspondences of connected edges in right and left images and the other is intra-scanline search for correspondences of edge-delimited intervals on each scanline pair. Dynamic programming is used for both searches which proceed simultaneously: the former supplies the consistency constraint to the latter while the latter supplies the matching score to the former. An interval-based similarity metric is used to compute the score. The algorithm has been tested with different types of images including urban aerial images, synthesized images, and block scenes, and its computational requirement has been discussed.