TY - JOUR
T1 - Camera handoff and placement for automated tracking systems with multiple omnidirectional cameras
AU - Chen, Chung Hao
AU - Yao, Yi
AU - Page, David
AU - Abidi, Besma
AU - Koschan, Andreas
AU - Abidi, Mongi
PY - 2010/2
Y1 - 2010/2
N2 - In a multi-camera surveillance system, both camera handoff and placement play an important role in generating an automated and persistent object tracking, typical of most surveillance requirements. Camera handoff should comprise three fundamental components, time to trigger handoff process, the execution of consistent labeling, and the selection of the next optimal camera. In this paper, we design an observation measure to quantitatively formulate the effectiveness of object tracking so that we can trigger camera handoff timely and select the next camera appropriately before the tracked object falls out of the field of view (FOV) of the currently observing camera. In the meantime, we present a novel solution to the consistent labeling problem in omnidirectional cameras. A spatial mapping procedure is proposed to consider both the noise inherent to the tracking algorithms used by the system and the lens distortion introduced by omnidirectional cameras. This does not only avoid the tedious process, but also increases the accuracy, to obtain the correspondence between omnidirectional cameras without human interventions. We also propose to use the Wilcoxon Signed-Rank Test to improve the accuracy of trajectory association between pairs of objects. In addition, since we need a certain amount of time to successfully carry out the camera handoff procedure, we introduce an additional constraint to optimally reserve sufficient cameras' overlapped FOVs for the camera placement. Experiments show that our proposed observation measure can quantitatively formulate the effectiveness of tracking, so that camera handoff can smoothly transfer objects of interest. Meanwhile, our proposed consistent labeling approach can perform as accurately as the geometry-based approach without tedious calibration processes and outperform Calderara's homography-based approach. Our proposed camera placement method exhibits a significant increase in the camera handoff success rate at the cost of slightly decreased coverage, as compared to Erdem and Sclaroff's method without considering the requirement on overlapped FOVs.
AB - In a multi-camera surveillance system, both camera handoff and placement play an important role in generating an automated and persistent object tracking, typical of most surveillance requirements. Camera handoff should comprise three fundamental components, time to trigger handoff process, the execution of consistent labeling, and the selection of the next optimal camera. In this paper, we design an observation measure to quantitatively formulate the effectiveness of object tracking so that we can trigger camera handoff timely and select the next camera appropriately before the tracked object falls out of the field of view (FOV) of the currently observing camera. In the meantime, we present a novel solution to the consistent labeling problem in omnidirectional cameras. A spatial mapping procedure is proposed to consider both the noise inherent to the tracking algorithms used by the system and the lens distortion introduced by omnidirectional cameras. This does not only avoid the tedious process, but also increases the accuracy, to obtain the correspondence between omnidirectional cameras without human interventions. We also propose to use the Wilcoxon Signed-Rank Test to improve the accuracy of trajectory association between pairs of objects. In addition, since we need a certain amount of time to successfully carry out the camera handoff procedure, we introduce an additional constraint to optimally reserve sufficient cameras' overlapped FOVs for the camera placement. Experiments show that our proposed observation measure can quantitatively formulate the effectiveness of tracking, so that camera handoff can smoothly transfer objects of interest. Meanwhile, our proposed consistent labeling approach can perform as accurately as the geometry-based approach without tedious calibration processes and outperform Calderara's homography-based approach. Our proposed camera placement method exhibits a significant increase in the camera handoff success rate at the cost of slightly decreased coverage, as compared to Erdem and Sclaroff's method without considering the requirement on overlapped FOVs.
KW - Automated surveillance systems
KW - Camera handoff
KW - Camera placement
KW - Consistent labeling
KW - Multi-object multi-camera tracking
KW - Omnidirectional camera
UR - https://www.scopus.com/pages/publications/74849133723
U2 - 10.1016/j.cviu.2009.04.004
DO - 10.1016/j.cviu.2009.04.004
M3 - Article
AN - SCOPUS:74849133723
SN - 1077-3142
VL - 114
SP - 179
EP - 197
JO - Computer Vision and Image Understanding
JF - Computer Vision and Image Understanding
IS - 2
ER -