NDLI: Person identification using automatic height and stride estimation

Content Provider	IEEE Xplore Digital Library
Author	BenAbdelkader, C. Cutler, R. Davis, L.
Copyright Year	2002
Description	Author affiliation: Maryland Univ., College Park, MD, USA (BenAbdelkader, C.)
Abstract	We present a parametric method to automatically identify people in monocular low-resolution video by estimating the height and stride parameters of their gait. Stride parameters (stride length and cadence) are functions of body height, weight, and gender Previous work has demonstrated an effective use of these biometrics for identification and verification of people. In this paper, we show that performance is significantly improved by using height as an additional discriminant feature. Height is estimated by segmenting the person from the background and fitting their apparent height to a time-dependent model. With a database of 45 people and 4 samples of each, we show that a person is correctly identified with 49% probability when using both height and stride parameters, compared with 21% when using stride parameters only. Height estimates for this configuration are accurate to within /spl sigma/=3.5 cm. This method works with low-resolution images of people, and is robust to changes in lighting, clothing, and tracking errors.
Starting Page	377
Ending Page	380
File Size	363296
Page Count	4
File Format	PDF
ISBN	076951695X
ISSN	10514651
DOI	10.1109/ICPR.2002.1047474
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2002-08-11
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Legged locomotion Robustness Educational institutions Biometrics Clothing Humans Surveillance Cameras Biomechanics Extremities
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition

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

Stride and cadence as a biometric in automatic person identification and verification

Can gait biometrics be Spoofed?

Person Reidentification Using Spatiotemporal Appearance

Gait recognition using multiple views

Gait recognition by dynamic cues

Person identification from spatio-temporal volumes

On the relationship of human walking and running: automatic person identification by gait

Using Bilinear Models for View-invariant Action and Identity Recognition

A Framework for Evaluating the Effect of View Angle, Clothing and Carrying Condition on Gait Recognition

Person identification using automatic height and stride estimation

Similar Documents

Stride and cadence as a biometric in automatic person identification and verification

Can gait biometrics be Spoofed?

Person Reidentification Using Spatiotemporal Appearance

Gait recognition using multiple views

Gait recognition by dynamic cues

Person identification from spatio-temporal volumes

On the relationship of human walking and running: automatic person identification by gait

Using Bilinear Models for View-invariant Action and Identity Recognition

A Framework for Evaluating the Effect of View Angle, Clothing and Carrying Condition on Gait Recognition

Person identification using automatic height and stride estimation