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Toward object-based heuristics

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1 Author(s)
Gross, A.D. ; Dept. of Comput. Sci., City Univ. of New York, Flushing, NY, USA

Recovering the 3-D shape of an object from its 2-D image contour is an important problem in computer vision. In this correspondence, the author motivates and develops two object-based heuristics. The structured nature of objects is the motivation for the nonaccidental alignment criterion: parallel coordinate axes within the object's bounding contour correspond to object-centered coordinate axes. The regularity and symmetry inherent in many man-made objects 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 3-D coordinate axes in the scene. These object-based heuristics are used to recover shape in both real and synthetic images

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Pattern Analysis and Machine Intelligence, IEEE Transactions on  (Volume:16 ,  Issue: 8 )