A Generalized Local Feature Structure for Model - Based 3D Object Recognition


The KIPS Transactions:PartB , Vol. 8, No. 5, pp. 573-578, Oct. 2001
10.3745/KIPSTB.2001.8.5.573,   PDF Download:

Abstract

This research proposes a generalized local feature structure named "LSG (Local Surface Group) for model-based 3D object recognition". An LSG consists of a surface and its immediately adjacent surfaces that are simultaneously visible for a given viewpoint. That is, LSG is not a simple feature but a viewpoint-dependent feature structure that contains several attributes such as surface type, color, area, radius, and simultaneously adjacent surfaces. In addition, we have developed a new method based on Bayesian theory that computes a measure of how distinct an LSG is compared to other LSGs for the purpose of object recognition. We have experimented the proposed methods on an object database composed of twenty 3D objects. The experimental results show that LSG and the Bayesian computing method can be successfully employed to achieve rapid 3D object recognition.


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Cite this article
[IEEE Style]
J. H. Yi, "A Generalized Local Feature Structure for Model - Based 3D Object Recognition," The KIPS Transactions:PartB , vol. 8, no. 5, pp. 573-578, 2001. DOI: 10.3745/KIPSTB.2001.8.5.573.

[ACM Style]
June Ho Yi. 2001. A Generalized Local Feature Structure for Model - Based 3D Object Recognition. The KIPS Transactions:PartB , 8, 5, (2001), 573-578. DOI: 10.3745/KIPSTB.2001.8.5.573.