Joint wavelet video denoising and motion activity detection in multimodal human activity analysis: Application to video-assisted bioacoustic/psychophysiological monitoring

作     者：Dimoulas, A. Avdelidis, K. A. Kalliris, G. M. Papanikolaou, G. V. 

作者机构：Aristotle Univ Thessaloniki Dept Journalism & Mass Commun Lab Elect MediaLab Electroacoust & TV Syst Dept Elect & Comp Engn Thessaloniki 54124 Greece 

出 版 物：《EURASIP JOURNAL ON ADVANCES IN SIGNAL PROCESSING》 (EURASIP信号处理进展杂志)

年 卷 期：2008年第2008卷第unknown期

页      面：792028-1-792028-19-0页

核心收录：

学科分类：0808[工学-电气工程] 081203[工学-计算机应用技术] 08[工学] 0835[工学-软件工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：Videotapes Activity Detection Motion detection Biomedical monitoring Human Activities darkness Noise reduction Detection algorithms Wiener filters 

摘      要：The current work focuses on the design and implementation of an indoor surveillance application for long-term automated analysis of human activity, in a video-assisted biomedical monitoring system. Video processing is necessary to overcome noise-related problems, caused by suboptimal video capturing conditions, due to poor lighting or even complete darkness during overnight recordings. Modified wavelet-domain spatiotemporal Wiener filtering and motion-detection algorithms are employed to facilitate video enhancement, motion-activity-based indexing and summarization. Structural aspects for validation of the motion detection results are also used. The proposed system has been already deployed in monitoring of long-term abdominal sounds, for surveillance automation, motion-artefacts detection and connection with other psychophysiological parameters. However, it can be used to any video-assisted biomedical monitoring or other surveillance application with similar demands. Copyright (c) 2008.