Shape from contour methods using object-based heuristics

Ari David Gross

doi:10.1117/12.142170

9 April 1993 Shape from contour methods using object-based heuristics

Ari David Gross

Proceedings Volume 1832, Vision Geometry; (1993) https://doi.org/10.1117/12.142170
Event: Applications in Optical Science and Engineering, 1992, Boston, MA, United States

Abstract

Recovering the 3D shape of an object from its 2D image contour is an important problem in computer vision. This paper begins with a survey and critique of some of the previous shape from contour methods that have been proposed. The author then develops two object-based heuristics and uses them to recover shape constraints from contour. The basic assumption guiding these object-based heuristics is that objects tend to be highly structured and can be parametrized with respect to an object-centered, orthogonal coordinate system. The structured nature of objects is the motivation for the non-accidental alignment criterion: parallel lines within the object's bounding contour are significant and are related to the 3D object-centered coordinate system. The regularity and symmetry inherent in many man-made objects, coupled with a human preference for an orthogonal perceptual space, is the motivation for the orthogonal basis constraint: an oblique set of coordinate axes in the image is presumed to be the projection of an orthogonal set of coordinate axes in the scene. These object-based heuristic methods are demonstrated on both real and synthetic image contours.

Citation Download Citation

Ari David Gross "Shape from contour methods using object-based heuristics", Proc. SPIE 1832, Vision Geometry, (9 April 1993); https://doi.org/10.1117/12.142170

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