Structural Stereopsis for 3-D Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Surfaces from Stereo: Integrating Feature Matching, Disparity Estimation, and Contour Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Matching Two Perspective Views
IEEE Transactions on Pattern Analysis and Machine Intelligence
3-D Surface Description from Binocular Stereo
IEEE Transactions on Pattern Analysis and Machine Intelligence
International Journal of Computer Vision
Motion Estimation with Quadtree Splines
IEEE Transactions on Pattern Analysis and Machine Intelligence
Parametric Shape-from-Shading by Radial Basis Functions
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multi-Primitive Hierarchical (MPH) Stereo Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Implicit and Explicit Camera Calibration: Theory and Experiments
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Stereo Matching Algorithm with an Adaptive Window: Theory and Experiment
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image Registration Using Wavelet-Based Motion Model
International Journal of Computer Vision
Uncertainty Propagation and the Matching of Junctions as Feature Groupings
IEEE Transactions on Pattern Analysis and Machine Intelligence
Building 3-D Human Face Models from Two Photographs
Journal of VLSI Signal Processing Systems - Special issue on multimedia signal processing
Inference of Segmented Overlapping Surfaces from Binocular Stereo
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fast Stereo Matching Using Rectangular Subregioning and 3D Maximum-Surface Techniques
International Journal of Computer Vision
Probabilistic regularisation and symmetry in binocular dynamic programming stereo
Pattern Recognition Letters - In memory of Professor E.S. Gelsema
An Area-Based Stereo Matching Using Adaptive Search Range and Window Size
ICCS '01 Proceedings of the International Conference on Computational Science-Part II
Binocular Stereo by Maximizing the Likelihood Ratio Relative to a Random Terrain
RobVis '01 Proceedings of the International Workshop on Robot Vision
Stereo Correspondence Using a Fuzzy Approach
AFSS '02 Proceedings of the 2002 AFSS International Conference on Fuzzy Systems. Calcutta: Advances in Soft Computing
A Comparative Study of Performance and Implementation of Some Area-Based Stereo Algorithms
CAIP '01 Proceedings of the 9th International Conference on Computer Analysis of Images and Patterns
Fast Distance Computation with a Stereo Head-Eye System
BMVC '00 Proceedings of the First IEEE International Workshop on Biologically Motivated Computer Vision
Stereovision matching through support vector machines
Pattern Recognition Letters
Information Theoretic Deformable Registration Using Local Image Information
International Journal of Computer Vision
A People Counting System Based on Dense and Close Stereovision
ICISP '08 Proceedings of the 3rd international conference on Image and Signal Processing
ICCS'03 Proceedings of the 2003 international conference on Computational science: PartII
View synthesis using stereo vision
View synthesis using stereo vision
Accurate hardware-based stereo vision
Computer Vision and Image Understanding
Stereo matching using gradient similarity and locally adaptive support-weight
Pattern Recognition Letters
Artificial neural receptive field for stereovision
ICANN'05 Proceedings of the 15th international conference on Artificial Neural Networks: biological Inspirations - Volume Part I
A hybrid matching algorithm based on contour and motion information for depth estimation
Proceedings of the 7th International Conference on Ubiquitous Information Management and Communication
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In this paper, we propose a stereo correspondence method by minimizing intensity and gradient errors simultaneously. In contrast to conventional use of image gradients, the gradients are applied in the deformed image space. Although a uniform smoothness constraint is imposed, it is applied only to nonfeature regions. To avoid local minima in the function minimization, we propose to parameterize the disparity function by hierarchical Gaussians. Both the uniqueness and the ordering constraints can be easily imposed in our minimization framework. Besides, we propose a method to estimate the disparity map and the camera response difference parameters simultaneously. Experiments with various real stereo images show robust performances of our algorithm.