CASIA-E: A Large Comprehensive Dataset for Gait Recognition-Reference-Cited by-同舟云学术

CASIA-E: A Large Comprehensive Dataset for Gait Recognition

Published:2022 Issue: Volume: Page:1-16
ISSN:0162-8828
Container-title:IEEE Transactions on Pattern Analysis and Machine Intelligence
language:
Short-container-title:IEEE Trans. Pattern Anal. Mach. Intell.

Author:

Song Chunfeng¹^ORCID,Huang Yongzhen²^ORCID,Wang Weining¹^ORCID,Wang Liang¹

Affiliation:

1. Center for Research on Intelligent Perception and Computing (CRIPAC), National Laboratory of Pattern Recognition (NLPR), Center for Excellence in Brain Science and Intelligence Technology (CEBSIT), Institute of Automation, Chinese Academy of Sciences ( CASIA), and the University of Chinese Academy of Sciences (UCAS), Beijing, China

2. School of Artificial Intelligence, Beijing Normal University (BNU), Beijing, China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Applied Mathematics,Artificial Intelligence,Computational Theory and Mathematics,Computer Vision and Pattern Recognition,Software

Link

http://xplorestaging.ieee.org/ielx7/34/4359286/09796582.pdf?arnumber=9796582

Reference75 articles.

1. A survey of biometric gait recognition: Approaches, security and challenges;gafurov,2007

2. Fusion of Static and Dynamic Body Biometrics for Gait Recognition

3. GaitPart: Temporal Part-Based Model for Gait Recognition

4. A Review of Vision-Based Gait Recognition Methods for Human Identification

5. The CMU motion of body (mobo)database;gross,2001

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