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Human detection from images and videos: a survey

Journal Article


Abstract


  • The problem of human detection is to automatically locate people in an image or video sequence and has been actively researched in the past decade. This paper aims to provide a comprehensive survey on the recent development and challenges of human detection. Different from previous surveys, this survey is organised in the thread of human object descriptors. This approach has advantages in providing a thorough analysis of the state-of-the-art human detection methods and a guide to the selection of appropriate methods in practical applications. In addition, challenges such as occlusion and real-time human detection are analysed. The commonly used evaluation of human detection methods such as the datasets, tools, and performance measures are presented and future research directions are highlighted.

Publication Date


  • 2016

Citation


  • Nguyen, D., Li, W. & Ogunbona, P. O. (2016). Human detection from images and videos: a survey. Pattern Recognition, 51 148-175.

Scopus Eid


  • 2-s2.0-84955600326

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers/4992

Has Global Citation Frequency


Number Of Pages


  • 27

Start Page


  • 148

End Page


  • 175

Volume


  • 51

Place Of Publication


  • Netherlands

Abstract


  • The problem of human detection is to automatically locate people in an image or video sequence and has been actively researched in the past decade. This paper aims to provide a comprehensive survey on the recent development and challenges of human detection. Different from previous surveys, this survey is organised in the thread of human object descriptors. This approach has advantages in providing a thorough analysis of the state-of-the-art human detection methods and a guide to the selection of appropriate methods in practical applications. In addition, challenges such as occlusion and real-time human detection are analysed. The commonly used evaluation of human detection methods such as the datasets, tools, and performance measures are presented and future research directions are highlighted.

Publication Date


  • 2016

Citation


  • Nguyen, D., Li, W. & Ogunbona, P. O. (2016). Human detection from images and videos: a survey. Pattern Recognition, 51 148-175.

Scopus Eid


  • 2-s2.0-84955600326

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers/4992

Has Global Citation Frequency


Number Of Pages


  • 27

Start Page


  • 148

End Page


  • 175

Volume


  • 51

Place Of Publication


  • Netherlands