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Page 510
... projected locations of noncoplanar points , obtained at three different instants of time . His analysis is based on the orthographic projection model . The treatment also considered the correspondence of the four projected points ...
... projected locations of noncoplanar points , obtained at three different instants of time . His analysis is based on the orthographic projection model . The treatment also considered the correspondence of the four projected points ...
Page 585
... projection model , he derived the maximum likelihood estimators ofthe slant and tilt angles . Although the isotropic assumption is a general one , there are many natural scenes that do not agree with this assumption . In our formulation ...
... projection model , he derived the maximum likelihood estimators ofthe slant and tilt angles . Although the isotropic assumption is a general one , there are many natural scenes that do not agree with this assumption . In our formulation ...
Page 586
... projection with the following process . a . First , the region S is projected onto the plane -Z = d , which plane is parallel to the image plane and includes the mass center of the region S. The projection is performed by using the rays ...
... projection with the following process . a . First , the region S is projected onto the plane -Z = d , which plane is parallel to the image plane and includes the mass center of the region S. The projection is performed by using the rays ...
Contents
Depth from Three Camera Stereo | 2 |
The Calibration Problem for Stereo | 15 |
Model Based Analysis of Industrial Scenes | 28 |
Copyright | |
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Common terms and phrases
affine transform algorithm analysis angle applied approach approximation array Artificial Intelligence axis binary boundary calibration camera clustering component Computer Vision connected constraints contour convolution coordinate system corresponding curvature curve defined derivative described detector determined direction edge detection elements equation error estimate filter function Gaussian geometric given gradient histogram Hough transform IEEE IEEE Trans image plane Image Processing implementation input label line segments linear machine machine vision matching matrix measure merging method motion node noise object obtained octree operations optical flow orientation output parallel parameters Pattern Recognition perspective projection pixel planar polygon problem Proc procedure processors projection quadtree region representation rotation scene shape SIMD smoothing solution space step stereo structure surface surface normal technique template tensor texture Theorem threshold tion transformation tree values vector visual window zero-crossings