Three-dimensional computer vision
Three-dimensional computer vision
Introduction to statistical pattern recognition (2nd ed.)
Introduction to statistical pattern recognition (2nd ed.)
Using chromatic information in edge-based stereo correspondence
CVGIP: Image Understanding
Three-dimensional computer vision: a geometric viewpoint
Three-dimensional computer vision: a geometric viewpoint
What can two images tell us about a third one?
International Journal of Computer Vision
Computer Vision: Three-Dimensional Data from Images
Computer Vision: Three-Dimensional Data from Images
Signal Processing for Computer Vision
Signal Processing for Computer Vision
An Experimental Comparison of Appearance and Geometric Model Based Recognition
ECCV '96 Proceedings of the International Workshop on Object Representation in Computer Vision II
Automatic line matching across views
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
IEEE Transactions on Signal Processing
The non-parametric Parzen's window in stereo vision matching
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A low level real-time vision system using specific computing architectures
ISCGAV'06 Proceedings of the 6th WSEAS International Conference on Signal Processing, Computational Geometry & Artificial Vision
Continuous dimensionality characterization of image structures
Image and Vision Computing
Short Communication: A method for sparse disparity densification using voting mask propagation
Journal of Visual Communication and Image Representation
Image processing architecture for local features computation
ARC'07 Proceedings of the 3rd international conference on Reconfigurable computing: architectures, tools and applications
Increasing efficiency in disparity calculation
BVAI'07 Proceedings of the 2nd international conference on Advances in brain, vision and artificial intelligence
A two-level real-time vision machine combining coarse- and fine-grained parallelism
Journal of Real-Time Image Processing
BVAI'05 Proceedings of the First international conference on Brain, Vision, and Artificial Intelligence
Three dilemmas of signal- and symbol-based representations in computer vision
BVAI'05 Proceedings of the First international conference on Brain, Vision, and Artificial Intelligence
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We introduce a compact coding of image information in terms of local multi-modal image descriptors. This coding allows for an explicit separation of the local image information into different visual sub-modalities: geometric information (orientation) and structural image information (contrast transition and colour). Based on this image representation, we derive a similarity function that compares visual information in each of these sub-modalities. This allows for an investigation of the importance of the different factors for stereo matching on a large data set. From this investigation we conclude that it is the combination of visual modalities that gives the best results. Concrete weights for their relative importance are measured. In addition to these quantitative results, we can demonstrate by our simulations that although our image representation reduces image information by 97% we achieve a matching performance which is comparable to block matching techniques. This shows that our very condensed representation preserves the relevant visual information.