Fall detection in dusky environment

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Please use this identifier to cite or link to this item: https://ir.lib.ncu.edu.tw/handle/987654321/101741

Title:	Fall detection in dusky environment
Authors:	陳映濃;Chen, Ying-Nong;Chuang, Chi-Hung;Lee, Hsin-Min;Yu, Chih-Chang;Fan, Kuo-Chin
Contributors:	太空及遙測研究中心
Keywords:	Biometrics;CCD cameras;Coarsening;Engineering;Environmental monitoring;Feature extraction;Human body;Illumination;Image Processing and Computer Vision;Pattern Recognition;Signal,Image and Speech Processing;Strategy
Date:	2016-12-01
Issue Date:	2026-04-21 14:42:25 (UTC+8)
Publisher:	Springer Publishing Company;Cham: Springer International Publishing
Abstract:	摘要： Accidental fall is the most prominent factor that causes the accidental death of elder people due to their slow body reaction. Automatic fall detection technology integrated in a health-care system can assist human monitoring the occurrence of fall, especially in dusky environments. In this paper, a novel fall detection system focusing mainly on dusky environments is proposed. In dusky environments, the silhouette images of human bodies extracted from conventional CCD cameras are usually imperfect due to the abrupt change of illumination. Thus, our work adopts a thermal imager to detect human bodies. The proposed approach adopts a coarse-to-fine strategy. Firstly, the downward optical flow features are extracted from the thermal images to identify fall-like actions in the coarse stage. The horizontal projection of motion history images (MHI) extracted from fall-like actions are then designed to verify the incident by the proposed nearest neighbor feature line embedding (NNFLE) in the fine stage. Experimental results demonstrate that the proposed method can distinguish the fall incidents with high accuracy even in dusky environments and overlapping situations. 其他題名： J Image Video Proc 出版者： Cham: Springer International Publishing 出版日期： 2016-03-31 出處： EURASIP journal on image and video processing, 2016-03, Vol.2016 (1), p.1-14, Article 16 資源來源： Publicly Available Content Database 版權： Chen et al. 2016 版權： The Author(s) 2016 識別號： ISSN: 1687-5281 識別號： ISSN: 1687-5176 識別號： EISSN: 1687-5281 識別號： DOI: 10.1186/s13640-016-0115-8
Appears in Collections:	[Center for Space and Remote Sensing Research ] journal & Dissertation

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