Toward object-based heuristics

Author

Gross, Ari D.

Author_Institution

Dept. of Comput. Sci., City Univ. of New York, Flushing, NY, USA

Volume

16

Issue

8

fYear

1994

fDate

8/1/1994 12:00:00 AM

Firstpage

794

Lastpage

802

Abstract

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

Keywords

computer vision; image recognition; 2-D image contour; 3-D shape recovery; bounding contour; computer vision; man-made objects; nonaccidental alignment criterion; object-based heuristics; object-centered coordinate axes; orthogonal basis constraint; parallel coordinate axes; real images; regularity; symmetry; synthetic images; Computer science; Computer vision; Geometry; Graphics; Intelligent systems; Labeling; Layout; Object recognition; Parametric statistics; Shape;

fLanguage

English

Journal_Title

Pattern Analysis and Machine Intelligence, IEEE Transactions on

Publisher

ieee

ISSN

0162-8828

Type

jour

DOI

10.1109/34.308474

Filename

308474