Abstract

Model-based recognition and motion tracking depends upon the ability to solve for projection and model parameters that will best fit a 3-D model to matching 2-D image features. This paper extends current methods of parameter solving to handle objects with arbitrary curved surfaces and with any number of internal parameters representing articulations, variable dimensions, or surface deformations. Numerical

Citations

2447	Random sample consensus: A paradigm for model fitting with applications to image analysis and automated cartography - FISCHLER, BOLLES - 1981
842	Theory of Edge Detection - Marr - 1980
734	An algorithm for least-squares estimation of nonlinear parameters - Marquardt - 1963
449	Perceptual Organization and Visual Recognition - Lowe - 1985
384	Three-Dimensional Object Recognition from Single Two-Dimensional Images - Lowe - 1987
244	Machine perception of threedimensional solids - Roberts - 1965
239	Computational vision and regularization theory - Poggio, Torre, et al. - 1985
228	The representation, recognition and locating of 3-D objects - Faugeras, Hebert - 1986
224	A method for the solution of certain nonlinear problems in least squares, Quart - Levenberg - 1944
218	Introduction to perception - Rock - 1975
186	Symbolic reasoning among 3-D models and 2-D images - Brooks - 1981
174	Visual perception by computer - Binford - 1971
170	Object recognition using alignment - Huttenlocher, Ullman - 1987
163	Pose Estimation From Corresponding Point Data - Haralick - 1989
156	Perceptual organization and the representation of natural form - Pentland - 1986
112	Determination of the attitude of 3D objects from a single perspective view - Dhome, Richetin, et al. - 1989
91	recognizing and positioning curved 3D objects from image contours,” Trans - Kriegman, Ponce - 1990
89	An analytic solution for the perspective 4-point problem - Horaud, Conio, et al. - 1989
72	Organization of smooth image curves at multiple scales - Lowe - 1988
64	The viewpoint consistency constraint - Lowe - 1987
60	Faugeras. Determination of camera location from 2-d to 3-d line and point correspondences - Liu, Huang, et al. - 1990
42	Special Purpose Automatic programming for 3D Model Based Vision - Goad - 1983
29	Solving for the parameters of object models from image descriptions - Lowe - 1980
13	Determination of Camera Location and Orientation - Kumar - 1989
11	Tracking objects using image disparities - Bray - 1990
8	A 3-D sensor system for teaching robot paths and environments - Ishii, Sakane, et al. - 1987
6	Motion-based motion analysis: Motion from motion - Thompson, Mundy - 1988
6	Model based perspective inversion - Worrall, Baker, et al. - 1988
5	An Analysis of Lowe’s Model-based Vision System - McIvor - 1968
4	Verification of 3D parametric models in 2D image data - Goldberg, Lowe - 1987
2	Thomás Lozano-Pérez, “Model-based recognition and localization from sparse range or tactile data,” Int - Grimson - 1984