Yunyoung Nam and Junghun Ryu and Yoo-Joo Choi and We-Duke Cho
Learning SpatioTemporal Topology of a MultiCamera Network by Tracking Multiple People
1549 - 1554
2007
1
6
International Journal of Computer and Information Engineering
https://publications.waset.org/pdf/7797
https://publications.waset.org/vol/6
World Academy of Science, Engineering and Technology
This paper presents a novel approach for representing
the spatiotemporal topology of the camera network with overlapping
and nonoverlapping fields of view (FOVs). The topology is
determined by tracking moving objects and establishing object
correspondence across multiple cameras. To track people successfully
in multiple camera views, we used the MergeSplit (MS) approach for
object occlusion in a single camera and the gridbased approach for
extracting the accurate object feature. In addition, we considered the
appearance of people and the transition time between entry and exit
zones for tracking objects across blind regions of multiple cameras
with nonoverlapping FOVs. The main contribution of this paper is to
estimate transition times between various entry and exit zones, and to
graphically represent the camera topology as an undirected weighted
graph using the transition probabilities.
Open Science Index 6, 2007