NDLI: Using Evolution to Learn How to Perform Interest Point Detection

Content Provider	IEEE Xplore Digital Library
Author	Trujillo, L. Olague, G.
Copyright Year	2006
Description	Author affiliation: Departamento de Ciencias de la Comput., Centro de Investigation Cientifica y de Educ. Superior de Ensenada (Trujillo, L.; Olague, G.)
Abstract	The performance of high-level computer vision applications is tightly coupled with the low-level vision operations that are commonly required. Thus, it is advantageous to have low-level feature extractors that are optimal with respect to a desired performance criteria. This paper presents a novel approach that uses genetic programming as a learning framework that generates a specific type of low-level feature extractor: interest point detector. The learning process is posed as an optimization problem. The optimization criterion is designed to promote the emergence of the detectors' geometric stability under different types of image transformations and global separability between detected points. This concept is represented by the operators repeatability rate. Results prove that our approach is effective at automatically generating low-level feature extractors. This paper presents two different evolved operators: IPGP1 and IPGP2. Their performance is comparable with the Harris operator given their excellent repeatability rate. Furthermore, the learning process was able to rediscover the DET corner detector proposed by Beaudet
Sponsorship	IEEE CPS
Starting Page	211
Ending Page	214
File Size	1509758
Page Count	4
File Format	PDF
ISBN	0769525210
ISSN	10514651
DOI	10.1109/ICPR.2006.1153
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-08-20
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Detectors Computer vision Feature extraction Genetic programming Application software Measurement Design optimization Stability criteria Evolutionary computation Learning systems
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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