Computing Local Surface Orientation and Shape from Texture forCurved Surfaces
International Journal of Computer Vision
A Cooperative Algorithm for Stereo Matching and Occlusion Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Determining Three-Dimensional Shape from Orientation and Spatial Frequency Disparities
ECCV '92 Proceedings of the Second European Conference on Computer Vision
A Computational Framework for Determining Stereo Correspondence from a Set of Linear Spatial Filters
ECCV '92 Proceedings of the Second European Conference on Computer Vision
Measuring the Affine Transform Using Gaussian Filters
ECCV '94 Proceedings of the Third European Conference-Volume II on Computer Vision - Volume II
A Wavelet Tour of Signal Processing, Third Edition: The Sparse Way
A Wavelet Tour of Signal Processing, Third Edition: The Sparse Way
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Position disparity between two stereoscopic images, combined with camera calibration information, allow depth recovery. The measurement of position disparity is known to be ambiguous when the scene reflectance displays repetitive patterns. This problem is reduced if one analyzes scale disparity, as in shape from texture, which relies on the deformations of repetitive patterns to recover scene geometry from a single view.These observations lead us to introduce a new correlation measure based not only on position disparity, but on position and scale disparity. Local scale disparity is expressed as a change in the scale of wavelet coefficients. Our work is related to the spatial frequency disparity analysis of Jones and Malik (ECCV92). We introduce a new wavelet-based correlation measure, and we show its application to stereopsis. We demonstrate its ability to reproduce perceptual results which no other method of our knowledge had accounted for.