NDLI: Shape matching and object recognition using low distortion correspondences

Content Provider	IEEE Xplore Digital Library
Author	Berg, A.C. Berg, T.L. Malik, J.
Copyright Year	2005
Description	Author affiliation: Dept. of Electr. Eng. & Comput. Sci., U.C. Berkeley, US (Berg, A.C.; Berg, T.L.; Malik, J.)
Abstract	We approach recognition in the framework of deformable shape matching, relying on a new algorithm for finding correspondences between feature points. This algorithm sets up correspondence as an integer quadratic programming problem, where the cost function has terms based on similarity of corresponding geometric blur point descriptors as well as the geometric distortion between pairs of corresponding feature points. The algorithm handles outliers, and thus enables matching of exemplars to query images in the presence of occlusion and clutter. Given the correspondences, we estimate an aligning transform, typically a regularized thin plate spline, resulting in a dense correspondence between the two shapes. Object recognition is then handled in a nearest neighbor framework where the distance between exemplar and query is the matching cost between corresponding points. We show results on two datasets. One is the Caltech 101 dataset (Fei-Fei, Fergus and Perona), an extremely challenging dataset with large intraclass variation. Our approach yields a 48% correct classification rate, compared to Fei-Fei et al 's 16%. We also show results for localizing frontal and profile faces that are comparable to special purpose approaches tuned to faces.
Sponsorship	IEEE Comput. Soc
Starting Page	26
Ending Page	33
File Size	3088796
Page Count	8
File Format	PDF
ISBN	0769523722
ISSN	10636919
DOI	10.1109/CVPR.2005.320
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-06-20
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Shape Object recognition Computer vision Algorithms Deformable models Quadratic programming Cost function Spline Nearest neighbor searches Face detection
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition Software

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

Shape Matching and Object Recognition using Low Distortion Correspondences (2004)

Shape matching and object recognition using low distortion correspondence (2005)

Shape matching and object recognition using low distortion correspondence (2005)

Shape matching and object recognition using low distortion correspondence (2005)

Shape Matching and Object Recognition (2006)

Articulated Shape Matching Using Locally Linear Embedding and Orthogonal Alignment

Representation and detection of deformable shapes

Learning a Hierarchical Deformable Template for Rapid Deformable Object Parsing

Learning a discriminative classifier using shape context distances

Shape matching and object recognition using low distortion correspondences

Similar Documents

Shape Matching and Object Recognition using Low Distortion Correspondences (2004)

Shape matching and object recognition using low distortion correspondence (2005)

Shape matching and object recognition using low distortion correspondence (2005)

Shape matching and object recognition using low distortion correspondence (2005)

Shape Matching and Object Recognition (2006)

Articulated Shape Matching Using Locally Linear Embedding and Orthogonal Alignment

Representation and detection of deformable shapes

Learning a Hierarchical Deformable Template for Rapid Deformable Object Parsing

Learning a discriminative classifier using shape context distances

Shape matching and object recognition using low distortion correspondences