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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Xiaotao Zou Bir Bhanu Bi Song Roy-Chowdhury, A.K. |
| Copyright Year | 2007 |
| Description | Author affiliation: California Univ., Riverside (Xiaotao Zou; Bir Bhanu; Bi Song; Roy-Chowdhury, A.K.) |
| Abstract | Recently, 'entry/exit' events of objects in the field-of-views of cameras were used to learn the topology of the camera network. The integration of object appearance was also proposed to employ the visual information provided by the imaging sensors. A problem with these methods is the lack of robustness to appearance changes. This paper integrates face recognition in the statistical model to better estimate the correspondence in the time-varying network. The statistical dependence between the entry and exit nodes indicates the connectivity and traffic patterns of the camera network, which are represented by a weighted directed graph and transition time distributions. A nine-camera network with 25 nodes is analyzed both in simulation and in real-life experiments, and compared with the previous approaches. |
| File Size | 360737 |
| File Format | |
| ISBN | 9781424414369 |
| ISSN | 15224880 |
| DOI | 10.1109/ICIP.2007.4379783 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2007-09-16 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Network topology Smart cameras Intelligent networks Intelligent sensors Image sensors Humans Monte Carlo methods Clothing Bismuth Intelligent systems statistical model camera network topology |
| Content Type | Text |
| Resource Type | Article |
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