NDLI: Classification of Local Eigen-Dissimilarities for Person Re-Identification

Content Provider	IEEE Xplore Digital Library
Author	Martinel, N. Micheloni, C.
Copyright Year	1994
Abstract	The task of re-identifying a person that moves across cameras fields-of-view is a challenge to the community known as the person re-identification problem. State-of-the art approaches are either based on direct modeling and matching of the human appearance or on machine learning-based techniques. In this work we introduce a novel approach that studies densely localized image dissimilarities in a low dimensional space and uses those to re-identify between persons in a supervised classification framework. To achieve the goal: i) we compute the localized image dissimilarity between a pair of images; ii) we learn the lower dimensional space of such localized image dissimilarities, known as the “local eigen-dissimilarities” (LEDs) space; iii) we train a binary classifier to discriminate between LEDs computed for a positive pair (images are for a same person) from the ones computed for a negative pair (images are for different persons). We show the competitive performance of our approach on two publicly available benchmark datasets.
Sponsorship	IEEE Signal Processing Society
Starting Page	455
Ending Page	459
Page Count	5
File Size	831302
File Format	PDF
ISSN	10709908
Volume Number	22
Issue Number	4
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-01-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Cameras Light emitting diodes Principal component analysis Measurement Computational modeling Vectors Image color analysis person re-identification Eigen-representation pairwise appearance modeling
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Signal Processing Electrical and Electronic Engineering

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

Learning pairwise feature dissimilarities for person re-identification

Person re-identification by modelling principal component analysis coefficients of image dissimilarities

Person re-identification by free energy score space encoding

Appearance-based person re-identification by intra-camera discriminative models and rank aggregation

Dense appearance modeling and efficient learning of camera transitions for person re-identification

Local Fisher Discriminant Analysis for Pedestrian Re-identification

Person Re-identification by Efficient Impostor-Based Metric Learning

Bagging based metric learning for person re-identification

Person re-identification by improved Local Maximal Occurrence with color names

Classification of Local Eigen-Dissimilarities for Person Re-Identification

Similar Documents

Learning pairwise feature dissimilarities for person re-identification

Person re-identification by modelling principal component analysis coefficients of image dissimilarities

Person re-identification by free energy score space encoding

Appearance-based person re-identification by intra-camera discriminative models and rank aggregation

Dense appearance modeling and efficient learning of camera transitions for person re-identification

Local Fisher Discriminant Analysis for Pedestrian Re-identification

Person Re-identification by Efficient Impostor-Based Metric Learning

Bagging based metric learning for person re-identification

Person re-identification by improved Local Maximal Occurrence with color names

Classification of Local Eigen-Dissimilarities for Person Re-Identification