NDLI: Object Detection Using Haar Feature Selection Optimization

Content Provider	IEEE Xplore Digital Library
Author	Demirkir, C. Sankur, B.
Copyright Year	2006
Description	Author affiliation: Elektrik ve Elektron. Muhendisligi Bolumu, Hava Harp Okulu, Istanbul (Demirkir, C.)
Abstract	Object detection in still images is one of the common problems which is needed to be solved in a robust and reliable manner. Main focus on this work is the designing of classifiers based on Haar like simple features to obtain a good and efficient detection performance. This problem corresponds to the so called feature selection problem which is common in the pattern classifier systems. Classifiers used to detect objects are based on the simple Haar like features and these features are selected using systematic and general evolutionary based algorithm. The objective is to build a set of classifiers which respond stronger to the features present in object patterns than to non-object patterns, thereby improving the class discrimination between these two classes. This approach combines the classifier design with feature selection by using a genetic algorithm (GA). In the feature selection part of the algorithm a GA algorithm which the Haar features are encoded using their parameters in a single chromosome and optimized using genetic operators. During optimization the features which show similar characteristics in the parameter space are selected using a cluster based partitioning algorithm and thereby redundancy in the features is eliminated and a more compact Haar feature set can be obtained. Performances of the resulting chromosomes are measured using a fitness measure which is based on the separation of the two classes samples over a validation set. The resulting object detection structure is tested for near frontal face images in the cluttered background images
Starting Page	1
Ending Page	4
File Size	3255378
Page Count	4
File Format	PDF
ISBN	1424402387
DOI	10.1109/SIU.2006.1659787
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-04-17
Publisher Place	Turkey
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis Performance evaluation Computer vision Redundancy Clustering algorithms Object detection Robustness Partitioning algorithms Biological cells Genetic algorithms
Content Type	Text
Resource Type	Article

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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