NDLI: Component based fuzzy geometrical configuration classifier

Content Provider	IEEE Xplore Digital Library
Author	Iqbal, R.T. Qidwai, U.
Copyright Year	2005
Description	Author affiliation: Dept. of EECS, Tulane Univ., New Orleans, LA, USA (Iqbal, R.T.; Qidwai, U.)
Abstract	Component based object detection approaches have been shown to significantly improve object detection performance in adverse conditions such as occlusion, variations in pose, in and out of plane rotation and poor illumination. Even the best object detectors are prone to errors when used in a global object detection scheme (one that uses the whole object as a single entity for detection purpose), due to the above mentioned problems. We propose a fuzzy approach to object detection that treats an object as a set of constituent components rather than a single entity. The object detection task is completed in two steps. In the first step, candidates for respective components are selected based on their appearance match and handed over to the geometrical configuration classifier. The geometrical configuration classifier is a fuzzy inference engine that selects one candidate for each component such that each candidate is a reasonable match to the corresponding component in terms of appearance and also a good fit for the overall geometrical model. The detected object consists of candidates that are not necessarily the best in terms of appearance match score or the closest to the geometrical model in terms of placement. The output is a set of candidates that is an optimal combination satisfying both criteria.
Starting Page	562
Ending Page	566
File Size	3752314
Page Count	5
File Format	PDF
ISBN	078039187X
DOI	10.1109/NAFIPS.2005.1548597
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-06-26
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Object detection Detectors Lighting Solid modeling Image matching Humans Vehicles Shape Uncertainty Decision making
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

Visual pattern based approach to object recognition

Object Detection Using Principal Contour Fragments

2D objects recognition by graph matching

Model based corner detection

Regions of interest for accurate object detection

Cascade scheme face detection using a non-liniar classifier

Vehicle matching and recognition under large variations of pose and illumination

TSK Fuzzy modeling approach for Face detection

Feature based parametric eigenspace method for object extraction

Component based fuzzy geometrical configuration classifier

Similar Documents

Visual pattern based approach to object recognition

Object Detection Using Principal Contour Fragments

2D objects recognition by graph matching

Model based corner detection

Regions of interest for accurate object detection

Cascade scheme face detection using a non-liniar classifier

Vehicle matching and recognition under large variations of pose and illumination

TSK Fuzzy modeling approach for Face detection

Feature based parametric eigenspace method for object extraction

Component based fuzzy geometrical configuration classifier