An efficient data structure for feature extraction in a foveated environment

Efri Nattel, Yehezkel Yeshurun

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

1 Scopus citations

Abstract

Foveated sampling and representation of images is a powerful tool for various vision applications. However,there are many inherent difficulties in implementing it. We present a simple and efficient mechanism to manipulate image analysis operators directly on the foveated image; A single typed table-based structure is used to represent various known operators. Using the Complex Log as our foveation method,w e show how several operators such as edge detection and Hough transform could be efficiently computed almost at frame rate,and discuss the complexity of our approach.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditorsTomaso Poggio, Seong-Whan Lee, Heinrich H. Bulthoff
PublisherSpringer Verlag
Pages217-226
Number of pages10
ISBN (Print)3540675604, 9783540675600
DOIs
StatePublished - 2000
Event1st IEEE International Workshop on Biologically Motivated Computer Vision, BMCV 2000 - Seoul, Korea, Republic of
Duration: 15 May 200017 May 2000

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume1811
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference1st IEEE International Workshop on Biologically Motivated Computer Vision, BMCV 2000
Country/TerritoryKorea, Republic of
CitySeoul
Period15/05/0017/05/00

Funding

FundersFunder number
ISF Center of Excellence
Ministry of Science and Technology

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