Human Attribute Recognition— A Comprehensive Survey

Human Attribute Recognition (HAR) is a highly active research field in computer vision and pattern recognition domains with various applications such as surveillance or fashion. Several approaches have been proposed to tackle the particular challenges in HAR. However, these approaches have dramatica...

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Bibliographic Details
Published in:Applied sciences 2020-08, Vol.10 (16), p.5608
Main Authors: Yaghoubi, Ehsan, Khezeli, Farhad, Borza, Diana, Kumar, SV Aruna, Neves, João, Proença, Hugo
Format: Article
Language:English
Subjects:
Biometrics
Cameras
clothing attributes
Computer vision
Datasets
Drones
Gender
human attribute recognition
imbalanced learning
Pattern recognition
pedestrian recognition
Polls & surveys
privacy concerns
Semantics
soft biometrics
Surveillance
Unmanned aerial vehicles
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Summary:Human Attribute Recognition (HAR) is a highly active research field in computer vision and pattern recognition domains with various applications such as surveillance or fashion. Several approaches have been proposed to tackle the particular challenges in HAR. However, these approaches have dramatically changed over the last decade, mainly due to the improvements brought by deep learning solutions. To provide insights for future algorithm design and dataset collections, in this survey, (1) we provide an in-depth analysis of existing HAR techniques, concerning the advances proposed to address the HAR’s main challenges; (2) we provide a comprehensive discussion over the publicly available datasets for the development and evaluation of novel HAR approaches; (3) we outline the applications and typical evaluation metrics used in the HAR context.
ISSN:2076-3417
2076-3417
DOI:10.3390/app10165608