Invariant Properties of Straight Homogeneous Generalized Cylinders and Their Contours
IEEE Transactions on Pattern Analysis and Machine Intelligence
Perceptual organization for computer vision
Perceptual organization for computer vision
On Recognizing and Positioning Curved 3-D Objects from Image Contours
IEEE Transactions on Pattern Analysis and Machine Intelligence
Shape constraints from parametric and non-parametric models
Shape constraints from parametric and non-parametric models
Perceptual Organization and Visual Recognition
Perceptual Organization and Visual Recognition
Recovery of SHGCs From a Single Intensity View
IEEE Transactions on Pattern Analysis and Machine Intelligence
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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.