Fall event detection with global and temporal local information in real-world videos

• Published in: Multimedia tools and applications Vol. 81; no. 5; pp. 6943 - 6956
• Main Authors: Pang, Wenfeng, He, Qianhua, Chen, Yuanfeng, Li, Yanxiong
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.02.2022; Springer Nature B.V
• Subjects: Cameras; Computer Communication Networks; Computer Science; Data Structures and Information Theory; Datasets; Injury prevention; Mathematical analysis; Modules; Multimedia; Multimedia Information Systems; Neural networks; Robots; Special Purpose and Application-Based Systems; Surveillance; Temporal local information; Real-world fall dataset; Fall event detection; Multiple instance module

Fall event detection is a task to determine whether a video includes falls, which can offer timely alarms to help reduce fall injury outcomes. This study applied typical 3D-convoultional network (C3D) as the classifier, but the basic C3D tends to extract the global information ignoring frame-wise in...