NDLI: The influence of segmentation on individual gait recognition

Content Provider	IEEE Xplore Digital Library
Author	Ning Jia Sanchez, V. Chang-Tsun Li Mansour, H.
Copyright Year	2015
Description	Author affiliation: Dept. of Comput. Sci., Univ. of Warwick, Coventry, UK (Ning Jia; Sanchez, V.; Chang-Tsun Li) \|\| Mitsubishi Electr. Res. Labs., Cambridge, MA, USA (Mansour, H.)
Abstract	The quality of the extracted gait silhouettes can hinder the performance and practicability of gait recognition algorithms. In this paper, we analyse the influence of silhouette quality caused by segmentation disparities, and propose a feature fusion strategy to improve recognition accuracy. Specifically, we first generate a dataset containing gait silhouette with various qualities generated by different segmentation algorithms, based on the CASIA Dataset B. We then project data into an embedded subspace, and fuse gallery features of different quality levels. To this end, we propose a fusion strategy based on Least Square QR-decomposition method. We perform classification based on the Euclidean distance between fused gallery features and probe features. Evaluation results show that the proposed fusion strategy attains important improvements on recognition accuracy.
Starting Page	1
Ending Page	6
File Size	1659428
Page Count	6
File Format	PDF
e-ISBN	9781467368025
DOI	10.1109/WIFS.2015.7368563
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-11-16
Publisher Place	Italy
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image segmentation Feature extraction Eigenvalues and eigenfunctions Probes Covariance matrices Gait recognition Principal component analysis
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

On Reducing the Effect of Silhouette Quality on Individual Gait Recognition: A Feature Fusion Approach

Supervised fractional eigenfaces

Image authenticity implementing Principal Component Analysis (PCA)

Fingerprint image enhancement using Principal Component Analysis (PCA) filters

Regularized eigenspace-based gait recogntion system for human identification

Research on Face Recognition Based on PCA

Moving object segmentation and tracking in video

A Comparison of Principal Component Analysis and Adaptive Principal Component Extraction for Palmprint Recognition

Multilinear mean component analysis for gait recognition

The influence of segmentation on individual gait recognition

Similar Documents

On Reducing the Effect of Silhouette Quality on Individual Gait Recognition: A Feature Fusion Approach

Supervised fractional eigenfaces

Image authenticity implementing Principal Component Analysis (PCA)

Fingerprint image enhancement using Principal Component Analysis (PCA) filters

Regularized eigenspace-based gait recogntion system for human identification

Research on Face Recognition Based on PCA

Moving object segmentation and tracking in video

A Comparison of Principal Component Analysis and Adaptive Principal Component Extraction for Palmprint Recognition

Multilinear mean component analysis for gait recognition

The influence of segmentation on individual gait recognition