Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article Joint Wavelet Video Denoising and Motion Activity Detection in Multimodal Human Activity Analysis: Application to Video-Assisted | Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2008 Article ID 792028 19 pages doi 2008 792028 Research Article Joint Wavelet Video Denoising and Motion Activity Detection in Multimodal Human Activity Analysis Application to Video-Assisted Bioacoustic Psychophysiological Monitoring C. A. Dimoulas K. A. Avdelidis G. M. Kalliris and G. V. Papanikolaou Laboratory of Electroacoustics and TV Systems Department of Electrical and Computer Engineering Laboratory of Electronic Media Department of Journalism and Mass Communication Aristotle University of Thessaloniki 54124 Thessaloniki Greece Correspondence should be addressed to C. A. Dimoulas babis@ Received 28 February 2007 Revised 31 July 2007 Accepted 8 October 2007 Recommended by Eric Pauwels 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 2008 C. A. Dimoulas et al. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any medium provided the
