3D object recognition based on low frequency response and random feature selection

Roberto A. Vázquez, Humberto Sossa, Beatriz A. Garro

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

9 Scopus citations

Abstract

In this paper we propose a view-based method for 3D object recognition based on some biological aspects of infant vision. The biological hypotheses of this method are based on the role of the response to low frequencies at early stages, and some conjectures concerning how an infant detects subtle features (stimulating points) from an object. In order to recognize an object from different images of it (different orientations from 0° to 100°) we make use of a dynamic associative memory (DAM). As the infant vision responds to low frequencies of the signal, a low-filter is first used to remove high frequency components from the image. Then we detect subtle features in the image by means of a random feature selection detector. At last, the DAM is fed with this information for training and recognition. To test the accuracy of the proposal we use the Columbia Object Image Library (COIL 100) database.

Original languageEnglish
Title of host publicationMICAI 2007
Subtitle of host publicationAdvances in Artificial Intelligence - 6th Mexican International Conference on Artificial Intelligence, Proceedings
PublisherSpringer Verlag
Pages694-704
Number of pages11
ISBN (Print)9783540766308
DOIs
StatePublished - 2007
Event6th Mexican International Conference on Artificial Intelligence, MICAI 2007 - Aguascalientes, Mexico
Duration: 4 Nov 200710 Nov 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4827 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference6th Mexican International Conference on Artificial Intelligence, MICAI 2007
Country/TerritoryMexico
CityAguascalientes
Period4/11/0710/11/07

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