Recovery of 3-D objects with multiple curved surfaces from 2-D contours

Cataloged from PDF version of article.Inference of 3-D shape from 2-D contours in a single image is an important problem in machine vision. Often, techniques to solve this problem examine each surface in the scene separately whereas our perception of their shapes clearly depends on the interplay between them as well. In this paper, we describe a technique that attempts to recover the shapes of all the surfaces of an object simultaneously, though it is limited to objects made of zero-Gaussian curvature surfaces. Our technique is based on an analysis of three kinds of symmetries defined in the paper and the constraints that derive from them, and from other boundaries. This technique uses some of the constraints developed in an earlier paper that was limited to examining a zero-Gaussian curvature surface cut by parallel planes. This restriction has been removed here and the constraints have been reformulated to allow integration of constraints from all the neighboring surfaces. Results on some complex examples are shown

Recovery of 3-D objects with multiple curved surfaces from 2-D contours

Inference of 3-D shape from 2-D contours in a single image is an important problem in machine vision. Often, techniques to solve this problem examine each surface in the scene separately whereas our perception of their shapes clearly depends on the interplay between them as well. In this paper, we describe a technique that attempts to recover the shapes of all the surfaces of an object simultaneously, though it is limited to objects made of zero-Gaussian curvature surfaces. Our technique is based on an analysis of three kinds of symmetries defined in the paper and the constraints that derive from them, and from other boundaries. This technique uses some of the constraints developed in an earlier paper that was limited to examining a zero-Gaussian curvature surface cut by parallel planes. This restriction has been removed here and the constraints have been reformulated to allow integration of constraints from all the neighboring surfaces. Results on some complex examples are shown. © 1994

Perception of 3-D Surfaces from 2-D Contours

Inference of 3-D shape from 2-D contours in a single image is an important problem in machine vision. We survey classes of techniques proposed in the past and provide a critical analysis. We propose that two kinds of symmetries in figures, which are known as parallel and skew symmetries, give significant information about surface shape for a variety of objects. We derive the constraints imposed by these symmetries and show how to use them to infer 3-D shape. We discuss the zero Gaussian curvature (ZGC) surfaces in depth and show results on the recovery of surface orientation for various ZGC surfaces. © 1993 IEE

Superquadric-Based Object Recognition

This paper proposes a technique for object recognition using superquadric built models. Superquadrics, which are three dimensional models suitable for part-level representation of objects, are reconstructed from range images using the recover-and-select paradigm. Using an interpretation three, the presence of an object in the scene from the model database can be hypothesized. These hypotheses are verified by projecting and re-fitting the object model to the range image which at the same time enables a better localization of the object in the scene