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SVD and Matrix Polynomial Interpolation for Lossy Progressive Transmission of 3D Images
Range Image Registration A Survey
Not all Motions are Equivalent in Terms of Depth Recovery
MULTIPERSPECTIVE PANORAMIC DEPTH IMAGING
algebraic curves ambiguities analysis angle cp bas-relief valley blobs captured image column Computer Vision configurations coordinate Cremona transformation curvature defined depth image depth recovery direction distance dual curve epipolar constraint epipolar geometry epipolar line equation error surface false matches feature points Figure focal length forward motion frame homogeneous polynomials homography horizontal ICP algorithm IEEE image curve image data image plane image registration image sequences iso-distortion surfaces lateral motion linear local minima matrix method motion estimation motion parameters moving point navigation noise obtained opposite minimum optical flow optimization ordinal depth panoramic images pixels planar planar algebraic point correspondences position possible depth estimates Proc progressive transmission projection quaternion range image registration recovered depth region residual error rigid robust scene SFM algorithms shape singular solution space stereo correspondences stereo pair structure from motion tangent target trajectory transformation translation true FOE values vector vertical visual
Page 24 - The work described in this paper was substantially supported by a grant from the Research Grants Council of the Hong Kong Special Administrative Region, China (Project No.