Stereo vision correspondance using a multichannel graph matching technique
Image and Vision Computing
ACM Computing Surveys (CSUR)
New Measurements and Corner-Guidance for Curve Matching with Probabilistic Relaxation
International Journal of Computer Vision
A distributed stereocorrelation algorithm
ICCCN '95 Proceedings of the 4th International Conference on Computer Communications and Networks
Contextual Inference in Contour-Based Stereo Correspondence
International Journal of Computer Vision
Fuzzy Cognitive Maps for stereovision matching
Pattern Recognition
A Geometric Approach for Regularization of the Data Term in Stereo-Vision
Journal of Mathematical Imaging and Vision
Mixed color/level lines and their stereo- matching with a modified Hausdorff distance
Integrated Computer-Aided Engineering
A statistical operator for detecting weak edges in low contrast images
ICIAR'12 Proceedings of the 9th international conference on Image Analysis and Recognition - Volume Part I
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A multichannel feature-based stereo vision technique where curve segments are used as feature primitives in the matching process is described. The left image and the right image are filtered by using several Laplacian-of-Gaussian operators of different widths (channels). Curve segments are extracted by a tracking algorithm, and their centroids are obtained. At each channel, the generalized Hough transform of each curve segment in the left and the right image is evaluated. The epipolar constraint on the centroids of the curve segment and the channel size is used to limit the searching space in the right image. To resolve the ambiguity of the false targets (multiple matches), a relaxation technique is used where the initial scores of the node assignments are updated by the compatibility measures between the centroids of the curve segments. The node assignments with the highest score are chosen as the matching curve segments.