A Theory of Human Stereo Vision
A Theory of Human Stereo Vision
Depth from edge and intensity based stereo
Depth from edge and intensity based stereo
Contour-Based Correspondence for Stereo
ECCV '00 Proceedings of the 6th European Conference on Computer Vision-Part I
An Experimental Comparison of Stereo Algorithms
ICCV '99 Proceedings of the International Workshop on Vision Algorithms: Theory and Practice
Parallel Trellis Based Stereo Matching Using Constraints
BMVC '00 Proceedings of the First IEEE International Workshop on Biologically Motivated Computer Vision
Computing in Cortical Columns: Curve Inference and Stereo Correspondence
BMVC '00 Proceedings of the First IEEE International Workshop on Biologically Motivated Computer Vision
Object Detection and Localization by Dynamic Template Warping
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Physically-Valid View Synthesis by Image Interplation
VSR '95 Proceedings of the IEEE Workshop on Representation of Visual Scenes
Dynamic Time Warp Pattern Matching Using an Integrated Multiprocessing Array
IEEE Transactions on Computers
Resolving stereo matching errors due to repetitive structures using model information
Pattern Recognition Letters
Video-rate stereo depth measurement on programmable hardware
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Surface reconstruction via helmholtz reciprocity with a single image pair
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
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
Parallel patch-based texture synthesis
EGGH-HPG'12 Proceedings of the Fourth ACM SIGGRAPH / Eurographics conference on High-Performance Graphics
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The past few years have seen a growing interest in the application" of three-dimensional image processing. With the increasing demand for 3-D spatial information for tasks of passive navigation [7,12], automatic surveillance [9], aerial cartography [10,13], and inspection in industrial automation, the importance of effective stereo analysis has been made quite clear. A particular challenge is to provide reliable and accurate depth data for input to object or terrain modelling systems (such as [5]. This paper describes an algorithm for such stereo sensing It uses an edge-based line-by-line stereo correlation scheme, and appears to be fast, robust, and parallel implementable. The processing consists of extracting edge descriptions for a stereo pair of images, linking these edges to their nearest neighbors to obtain the edge connectivity structure, correlating the edge descriptions on the basis of local edge properties, then cooperatively removmg those edge correspondences determined to be in error - those which violate the connectivity structure of the two images. A further correlation process, using a technique similar to that used for the edges, is applied to the image intensity values over intervals defined by the previous correlation The result of the processing is a full image array disparity map of the scene viewed.