Joint Wavelet Video Denoising and Motion Activity Detection in Multimodal Human Activity Analysis: Application to Video-Assisted Bioacoustic/Psychophysiological Monitoring. (5th December 2007)

• Record Type: Journal Article
• Authors: Dimoulas Dimoulas, C. A. C. A.; Avdelidis Avdelidis, K. A. K. A.; Kalliris Kalliris, G. M. G. M.; Papanikolaou Papanikolaou, G. V. G. V.
• Other Names: Pauwels Pauwels Eric Eric Academic Editor.
• Is Part Of: EURASIP journal on advances in signal processing. Volume 2008(2008)
• Publication Date: 2007-12-05
• Subjects: Signal processing -- Periodicals; Traitement du signal; Signal processing; Periodicals; 621.3822
• DOI: 10.1155/2008/792028
• Languages: English
• ISSNs: 1687-6172

Abstract

Abstract : 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.