Using angle densities for 3D recognition

Raashid Malik; Taegkeun Whangbo

doi:10.1117/12.189099

13 October 1994 Using angle densities for 3D recognition

Raashid Malik, Taegkeun Whangbo

Proceedings Volume 2354, Intelligent Robots and Computer Vision XIII: 3D Vision, Product Inspection, and Active Vision; (1994) https://doi.org/10.1117/12.189099
Event: Photonics for Industrial Applications, 1994, Boston, MA, United States

Abstract

Using computer vision to recognize 3-D objects is complicated by the fact that geometric features vary with view orientation. The key in designing recognition algorithms is therefore based on understanding and quantifying the variation of certain cardinal features. The features selected for study in the research reported in this paper are the angles between landmarks in a scene. The spatial arrangement of landmarks on an object may constitute a unique characteristic of that object. As an example the angles between the wing tips and the nose cone of an aircraft may be adequate in distinguishing amongst a given class of aircraft. In a class of polyhedral objects the angles at certain vertices may form a distinct and characteristic alignment of faces. For many other classes of objects it may be possible to identify distinctive spatial arrangements of some readily identifiable landmarks. In this paper we derive the two dimensional joint density function of two angles in a scene given an isotropic view orientation and an orthographic projection. This analytic expression is useful in deriving likelihood functions which may be used to obtain measures of the likelihood of angle combinations in images of known objects or scenes. These likelihood functions allow us to establish statistical decision schemes to recognize objects. Experiments have been conducted to evaluate the usefulness of the proposed methods.

Citation Download Citation

Raashid Malik and Taegkeun Whangbo "Using angle densities for 3D recognition", Proc. SPIE 2354, Intelligent Robots and Computer Vision XIII: 3D Vision, Product Inspection, and Active Vision, (13 October 1994); https://doi.org/10.1117/12.189099

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KEYWORDS

Optical spheres

Commercial off the shelf technology

Cameras

3D vision

Machine vision

Computer vision technology

Data modeling

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