Object recognition through the principal component analysis of spatial relationship amongst lines

Shekar, B. H. and Guru, D. S. and Nagabhushan, P. (2006) Object recognition through the principal component analysis of spatial relationship amongst lines. COMPUTER VISION - ACCV 2006, PT I, 3851. pp. 170-179. ISSN 978-3-540-32433-1

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Official URL: https://doi.org/10.1007/11612032_18

Abstract

This paper introduces a novel scheme which works on symbolizing every line in an object image for object recognition. Symbolizing is accomplished in terms of angles of intersection with regard to a line under consideration. Spatial relationship existing among the symbolized lines is represented using the notion of Triangular Spatial Relationship (TSR). A set of quadruples which preserves the TSR is subjected to principal component analysis to obtain the principal component vectors. These vectors are then stored in the knowledgebase for the purpose of recognition. Experimental results demonstrate that the proposed approach is efficient, invariant to linear transformations and capable of learning. To substantiate the success of the proposed model, a comparative study is performed with Murase and Nayar approach.

Item Type: Article
Subjects: D Physical Science > Computer Science
Divisions: Department of > Computer Science
Depositing User: lpa manjunath user
Date Deposited: 28 Aug 2019 10:12
Last Modified: 28 Aug 2019 10:12
URI: http://eprints.uni-mysore.ac.in/id/eprint/7262

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