An Images Monitoring System based on Multi-Format Streaming Grid Architecture
This paper proposes a novel multi-format stream grid
architecture for real-time image monitoring system. The system, based
on a three-tier architecture, includes stream receiving unit, stream
processor unit, and presentation unit. It is a distributed computing and
a loose coupling architecture. The benefit is the amount of required
servers can be adjusted depending on the loading of the image
monitoring system. The stream receive unit supports multi capture
source devices and multi-format stream compress encoder. Stream
processor unit includes three modules; they are stream clipping
module, image processing module and image management module.
Presentation unit can display image data on several different platforms.
We verified the proposed grid architecture with an actual test of image
monitoring. We used a fast image matching method with the
adjustable parameters for different monitoring situations. Background
subtraction method is also implemented in the system. Experimental
results showed that the proposed architecture is robust, adaptive, and
powerful in the image monitoring system.
[1] S. I. Lin, F. P. Lin, C. L. Chang, S. W. Lo, P. Mai, P. W. Chen, and Y. H.
Shiau, "Development of grid-based tiled display wall for networked
visualization," Cellular Neural Networks and Their Applications, 2005 9th
International Workshop on, 2005.
[2] TDW: http://tdw.nchc.org.tw.
[3] H. Nguyen, P. Duhamel, J. Brouet, and D. Rouffet, "Robust vlc sequence
decoding exploiting additional video stream properties with reduced
complexity," IEEE International Conference on Multimedia and Expo
(ICME), 2004.
[4] VLC: http://www.videolan.org/vlc.
[5] T. Nakajima, "Realtime feedback and on-demand playback system for
teaching skill improvement," Computers and Advanced Technology in
Education, 2005.
[6] C. Traiperm, and S. Kittitomkun, "High-performance MPEG-4 multipoint
conference unit," Networks and Communication System, 2005.
[7] FFMPEG: http://ffmpeg.mplayerhq.hu.
[8] S. Y. Chien, Y. M. Huang, B. Y. Hsieh, S. Y. Ma, and L. G. Chen, "Fast
video segmentation algorithm with shadow, cancellation global motion
compensation and adaptive threshold technique," IEEE Trans Multimedia,
vol. 6, no. 5, pp. 732-748, Oct. 2004.
[9] D. S. Lee, J. J. Hull, and B. Erol, "A Bayesian framework for gaussian
mixture background modeling," IEEE Proc. ICIP, vol.3, pp. 973-976,
2003.
[10] K. Kim, T. H. Chalidabhongse, D. Harwood, and L. Davis, "Real-time
foreground-background segmentation using codebook model real-time
imaging," vol. 11, issue 3, pp. 167-256, Jun. 2005.
[11] Ganglia: http://ganglia.info.
[1] S. I. Lin, F. P. Lin, C. L. Chang, S. W. Lo, P. Mai, P. W. Chen, and Y. H.
Shiau, "Development of grid-based tiled display wall for networked
visualization," Cellular Neural Networks and Their Applications, 2005 9th
International Workshop on, 2005.
[2] TDW: http://tdw.nchc.org.tw.
[3] H. Nguyen, P. Duhamel, J. Brouet, and D. Rouffet, "Robust vlc sequence
decoding exploiting additional video stream properties with reduced
complexity," IEEE International Conference on Multimedia and Expo
(ICME), 2004.
[4] VLC: http://www.videolan.org/vlc.
[5] T. Nakajima, "Realtime feedback and on-demand playback system for
teaching skill improvement," Computers and Advanced Technology in
Education, 2005.
[6] C. Traiperm, and S. Kittitomkun, "High-performance MPEG-4 multipoint
conference unit," Networks and Communication System, 2005.
[7] FFMPEG: http://ffmpeg.mplayerhq.hu.
[8] S. Y. Chien, Y. M. Huang, B. Y. Hsieh, S. Y. Ma, and L. G. Chen, "Fast
video segmentation algorithm with shadow, cancellation global motion
compensation and adaptive threshold technique," IEEE Trans Multimedia,
vol. 6, no. 5, pp. 732-748, Oct. 2004.
[9] D. S. Lee, J. J. Hull, and B. Erol, "A Bayesian framework for gaussian
mixture background modeling," IEEE Proc. ICIP, vol.3, pp. 973-976,
2003.
[10] K. Kim, T. H. Chalidabhongse, D. Harwood, and L. Davis, "Real-time
foreground-background segmentation using codebook model real-time
imaging," vol. 11, issue 3, pp. 167-256, Jun. 2005.
[11] Ganglia: http://ganglia.info.
@article{"International Journal of Information, Control and Computer Sciences:60117", author = "Yi-Haur Shiau and Sun-In Lin and Shi-Wei Lo and Hsiu-Mei Chou and Yi-Hsuan Chen", title = "An Images Monitoring System based on Multi-Format Streaming Grid Architecture", abstract = "This paper proposes a novel multi-format stream grid
architecture for real-time image monitoring system. The system, based
on a three-tier architecture, includes stream receiving unit, stream
processor unit, and presentation unit. It is a distributed computing and
a loose coupling architecture. The benefit is the amount of required
servers can be adjusted depending on the loading of the image
monitoring system. The stream receive unit supports multi capture
source devices and multi-format stream compress encoder. Stream
processor unit includes three modules; they are stream clipping
module, image processing module and image management module.
Presentation unit can display image data on several different platforms.
We verified the proposed grid architecture with an actual test of image
monitoring. We used a fast image matching method with the
adjustable parameters for different monitoring situations. Background
subtraction method is also implemented in the system. Experimental
results showed that the proposed architecture is robust, adaptive, and
powerful in the image monitoring system.", keywords = "Motion detection, grid architecture, image
monitoring system, and background subtraction.", volume = "3", number = "5", pages = "1403-5", }