Title :
Automated visual analysis in large scale sensor networks
Author :
Rasheed, Z. ; Cao, X. ; Shafique, K. ; Liu, H. ; Yu, L. ; Lee, M. ; Ramnath, K. ; Choe, T. ; Javed, O. ; Haering, N.
Author_Institution :
Center for Video Understanding Excellence, ObjectVideo Inc., Reston, VA
Abstract :
Modern automated video analysis systems consist of large networks of heterogeneous sensors. These systems must extract, integrate and present relevant information from the sensors in real-time. This paper addresses some of the major challenges such systems face: efficient video processing for high-resolution sensors; data fusion across multiple modalities; robustness to changing environmental conditions and video processing errors; and intuitive user interfaces for visualization and analysis. The paper discusses enabling technologies to overcome these challenges and presents a case study of a wide area video analysis system deployed at a port in the state of Florida, USA. The components of the system are also detailed and justified using quantitative and qualitative results.
Keywords :
data visualisation; geophysical signal processing; image registration; image sensors; real-time systems; sensor fusion; user interfaces; video signal processing; Florida; automated visual analysis; data fusion; geo-registration; heterogeneous sensors; high-resolution sensors; intuitive user interfaces; large scale sensor networks; modern automated video analysis systems; real-time sensors; video data visualization; video processing errors; wide area video analysis system; Computer errors; Data mining; Data visualization; Face; Large-scale systems; Real time systems; Robustness; Sensor fusion; Sensor systems; User interfaces; Geo-Registration; Monitoring; Video Analysis; Visual Sensor Networks;
Conference_Titel :
Distributed Smart Cameras, 2008. ICDSC 2008. Second ACM/IEEE International Conference on
Conference_Location :
Stanford, CA
Print_ISBN :
978-1-4244-2664-5
Electronic_ISBN :
978-1-4244-2665-2
DOI :
10.1109/ICDSC.2008.4635678