Object Recognition Based on Local Features Using Camera – Equipped Mobile Phone

Koceski, Saso and Koceska, Natasa and Krstev, Aleksandar (2011) Object Recognition Based on Local Features Using Camera – Equipped Mobile Phone. Communications in Computer and Information Science - ICT Innovations 2010 , 83. pp. 296-305. ISSN 1865-0929

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Official URL: http://link.springer.com/chapter/10.1007%2F978-3-6...

Abstract

The work presented in this paper analyses the viability of using a cell-phone as students' guidance for literature selection. The integrated cell-phone camera is used to recognize the book covers in the bookstores and libraries. The chosen solution is based on client-server architecture and the object recognition is based on local features. Detecting, identifying, and recognizing salient regions or feature points in images is a very important and fundamental problem to the artificial intelligence and computer vision community. This paper mainly focuses on the comparison, in terms of time and performance, of two promising new approaches for markerless object recognition algorithms: the Scale-Invariant Feature Transform (SIFT) and the Speeded Up Robust Features (SURF). The study was performed using a smart cell-phone with Symbian OS and the results are reported.

Item Type: Article
Subjects: Natural sciences > Computer and information sciences
Engineering and Technology > Electrical engineering, electronic engineering, information engineering
Divisions: Faculty of Computer Science
Depositing User: Saso Koceski
Date Deposited: 12 Dec 2012 11:59
Last Modified: 12 Dec 2012 11:59
URI: http://eprints.ugd.edu.mk/id/eprint/3269

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