NDLI: Gait recognition based on stochastic switched auto-regressive model

Content Provider	IEEE Xplore Digital Library
Author	Dapeng Zhang Inagaki, S. Suzuki, T.
Copyright Year	2012
Description	Author affiliation: Dept. of Mechanical Science and Engineering, Nagoya University, Chikusa, Nagoya 464-8603, Japan (Dapeng Zhang; Inagaki, S.; Suzuki, T.)
Abstract	A robust and compact gait model is desirable in many security applications because gait recognition is a promising non-intrusive biometric method. Only a few gait recognition systems adopted kinematical cues exclusively, but the dynamics model of parametric human body, including mass, length, inertia are seldom considered thoroughly. Furthermore, almost all these cues are velocity-dependent. The proposed model has a unique and flexible structure to deal with temporal features of gait like the timing and proportion of different phases in a gait cycle. It has a circular structure and 2 classes of states. In oder to fit the velocity-invariant features of gait, a special learning algorithm is proposed under the model's 2 kinds of structures. A 2-link virtual passive walking model plays an important role both in the configuration of the parameter matrix and the selection of the parameters' initial values. By evaluation the recognition rates of different models, the velocity-robust characteristics of the new model and its low computational load compared with conventional HMM are verified.
Starting Page	584
Ending Page	590
File Size	501330
Page Count	7
File Format	PDF
ISBN	9781467322591
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-08-20
Publisher Place	Japan
Access Restriction	Subscribed
Rights Holder	SICE
Subject Keyword	Hidden Markov models Computational modeling Legged locomotion Mathematical model Load modeling Biological system modeling Equations gait recognition robust gait proposed learning algorithm nonintrusive biometrics passive walking human motion modeling
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

Velocity-robust gait recognition based on stochastic switched auto-regressive model

Velocity-Robust Gait Analysis for Human Identification through Constrained Learning of Stochastic Switched Auto-Regressive Model

Adaptive gait recognition model and automatic velocity-robust feature selection based on a new Constrained Expectation Conditional-Maximization learning algorithm

HMM-based gait modeling and recognition under different walking scenarios

Robust human motion modeling strategy and its application on driver identification and gait recognition

Frame difference history image for gait recognition

Using gait information for gender recognition

General methods and development actuality of gait recognition

Gait recognition based on Fourier descriptors

Gait recognition based on stochastic switched auto-regressive model

Similar Documents

Velocity-robust gait recognition based on stochastic switched auto-regressive model

Velocity-Robust Gait Analysis for Human Identification through Constrained Learning of Stochastic Switched Auto-Regressive Model

Adaptive gait recognition model and automatic velocity-robust feature selection based on a new Constrained Expectation Conditional-Maximization learning algorithm

HMM-based gait modeling and recognition under different walking scenarios

Robust human motion modeling strategy and its application on driver identification and gait recognition

Frame difference history image for gait recognition

Using gait information for gender recognition

General methods and development actuality of gait recognition

Gait recognition based on Fourier descriptors

Gait recognition based on stochastic switched auto-regressive model