Open AccessRobust gait recognition: a comprehensive survey
Author(s) -
Rida Imad,
Almaadeed Noor,
Almaadeed Somaya
Publication year - 2019
Publication title -
iet biometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.434
H-Index - 28
eISSN - 2047-4946
pISSN - 2047-4938
DOI - 10.1049/iet-bmt.2018.5063
Subject(s) - biometrics , gait , identification (biology) , computer science , clothing , data science , artificial intelligence , human–computer interaction , machine learning , physical medicine and rehabilitation , geography , medicine , botany , archaeology , biology
Gait recognition has emerged as an attractive biometric technology for the identification of people by analysing the way they walk. However, one of the main challenges of the technology is to address the effects of inherent various intra‐class variations caused by covariate factors such as clothing, carrying conditions, and view angle that adversely affect the recognition performance. The main aim of this survey is to provide a comprehensive overview of existing robust gait recognition methods. This is intended to provide researchers with state of the art approaches in order to help advance the research topic through an understanding of basic taxonomies, comparisons, and summaries of the state‐of‐the‐art performances on several widely used gait recognition datasets.