Finding Camera Overlap in Large Surveillance Networks
Finding Camera Overlap in Large Surveillance Networks
- Neue Suche nach: van den Hengel, Anton
- Neue Suche nach: Dick, Anthony
- Neue Suche nach: Detmold, Henry
- Neue Suche nach: Cichowski, Alex
- Neue Suche nach: Hill, Rhys
- Neue Suche nach: Yagi, Yasushi
- Neue Suche nach: Kang, Sing Bing
- Neue Suche nach: Kweon, In So
- Neue Suche nach: Zha, Hongbin
- Neue Suche nach: van den Hengel, Anton
- Neue Suche nach: Dick, Anthony
- Neue Suche nach: Detmold, Henry
- Neue Suche nach: Cichowski, Alex
- Neue Suche nach: Hill, Rhys
Recent research on video surveillance across multiple cameras has typically focused on camera networks of the order of 10 cameras. In this paper we argue that existing systems do not scale to a network of hundreds, or thousands, of cameras. We describe the design and deployment of an algorithm called exclusion that is specifically aimed at finding correspondence between regions in cameras for large camera networks. The information recovered by exclusion can be used as the basis for other surveillance tasks such as tracking people through the network, or as an aid to human inspection. We have run this algorithm on a campus network of over 100 cameras, and report on its performance and accuracy over this network.
Dokumentinformationen
Finding Camera Overlap in Large Surveillance Networks
Asian Conference on Computer Vision ; 2007 ; Tokyo, Japan November 18, 2007 - November 22, 2007
2007-01-01
10 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
Foreground Object , Multiple Camera , Camera Network , Occupancy Data , Surveillance Task Computer Science , Image Processing and Computer Vision , Computer Imaging, Vision, Pattern Recognition and Graphics , Pattern Recognition , Artificial Intelligence , Biometrics , Algorithm Analysis and Problem Complexity