Human detection from images and videos: A survey. (March 2016)

• Record Type: Journal Article
• Authors: Nguyen, Duc Thanh; Li, Wanqing; Ogunbona, Philip O.
• Is Part Of: Pattern recognition. Volume 51(2016:Mar.)
• Page Start: 148
• Page End: 175
• Publication Date: 2016-03
• Subjects: Human detection -- Human description -- Object detection -- Object description; Pattern perception -- Periodicals; Perception des structures -- Périodiques; Patroonherkenning; 006.4
• DOI: 10.1016/j.patcog.2015.08.027
• Languages: English
• ISSNs: 0031-3203

Abstract

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. Abstract : Highlights: A review on the state-of-the-art of human detection. This review is organised in the thread of human object descriptors. Challenges such as occlusion and real-time human detection are analysed. The commonly used datasets, tools, and performance measures are presented. Open issues and future research directions are highlighted. A guide to the selection of detection methods for applications is provided.