Collaborative 3D Target Tracking in Distributed Smart Camera Networks for Wide-Area Surveillance
With the evolution and fusion of wireless sensor network and embedded camera technologies, distributed smart camera networks have emerged as a new class of systems for wide-area surveillance applications. Wireless networks, however, introduce a number of constraints to the system that need to be con...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2013-05-01
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| Series: | Journal of Sensor and Actuator Networks |
| Subjects: | |
| Online Access: | http://www.mdpi.com/2224-2708/2/2/316 |
| _version_ | 1819171072469106688 |
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| author | Xenofon Koutsoukos Manish Kushwaha |
| author_facet | Xenofon Koutsoukos Manish Kushwaha |
| author_sort | Xenofon Koutsoukos |
| collection | DOAJ |
| description | With the evolution and fusion of wireless sensor network and embedded camera technologies, distributed smart camera networks have emerged as a new class of systems for wide-area surveillance applications. Wireless networks, however, introduce a number of constraints to the system that need to be considered, notably the communication bandwidth constraints. Existing approaches for target tracking using a camera network typically utilize target handover mechanisms between cameras, or combine results from 2D trackers in each camera into 3D target estimation. Such approaches suffer from scale selection, target rotation, and occlusion, drawbacks typically associated with 2D tracking. In this paper, we present an approach for tracking multiple targets directly in 3D space using a network of smart cameras. The approach employs multi-view histograms to characterize targets in 3D space using color and texture as the visual features. The visual features from each camera along with the target models are used in a probabilistic tracker to estimate the target state. We introduce four variations of our base tracker that incur different computational and communication costs on each node and result in different tracking accuracy. We demonstrate the effectiveness of our proposed trackers by comparing their performance to a 3D tracker that fuses the results of independent 2D trackers. We also present performance analysis of the base tracker along Quality-of-Service (QoS) and Quality-of-Information (QoI) metrics, and study QoS vs. QoI trade-offs between the proposed tracker variations. Finally, we demonstrate our tracker in a real-life scenario using a camera network deployed in a building. |
| first_indexed | 2024-12-22T19:45:28Z |
| format | Article |
| id | doaj.art-e7627c00e9a14d868781a516e724d00e |
| institution | Directory Open Access Journal |
| issn | 2224-2708 |
| language | English |
| last_indexed | 2024-12-22T19:45:28Z |
| publishDate | 2013-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Sensor and Actuator Networks |
| spelling | doaj.art-e7627c00e9a14d868781a516e724d00e2022-12-21T18:14:42ZengMDPI AGJournal of Sensor and Actuator Networks2224-27082013-05-012231635310.3390/jsan2020316Collaborative 3D Target Tracking in Distributed Smart Camera Networks for Wide-Area SurveillanceXenofon KoutsoukosManish KushwahaWith the evolution and fusion of wireless sensor network and embedded camera technologies, distributed smart camera networks have emerged as a new class of systems for wide-area surveillance applications. Wireless networks, however, introduce a number of constraints to the system that need to be considered, notably the communication bandwidth constraints. Existing approaches for target tracking using a camera network typically utilize target handover mechanisms between cameras, or combine results from 2D trackers in each camera into 3D target estimation. Such approaches suffer from scale selection, target rotation, and occlusion, drawbacks typically associated with 2D tracking. In this paper, we present an approach for tracking multiple targets directly in 3D space using a network of smart cameras. The approach employs multi-view histograms to characterize targets in 3D space using color and texture as the visual features. The visual features from each camera along with the target models are used in a probabilistic tracker to estimate the target state. We introduce four variations of our base tracker that incur different computational and communication costs on each node and result in different tracking accuracy. We demonstrate the effectiveness of our proposed trackers by comparing their performance to a 3D tracker that fuses the results of independent 2D trackers. We also present performance analysis of the base tracker along Quality-of-Service (QoS) and Quality-of-Information (QoI) metrics, and study QoS vs. QoI trade-offs between the proposed tracker variations. Finally, we demonstrate our tracker in a real-life scenario using a camera network deployed in a building.http://www.mdpi.com/2224-2708/2/2/316distributed smart camerastarget trackingwide-area surveillance |
| spellingShingle | Xenofon Koutsoukos Manish Kushwaha Collaborative 3D Target Tracking in Distributed Smart Camera Networks for Wide-Area Surveillance Journal of Sensor and Actuator Networks distributed smart cameras target tracking wide-area surveillance |
| title | Collaborative 3D Target Tracking in Distributed Smart Camera Networks for Wide-Area Surveillance |
| title_full | Collaborative 3D Target Tracking in Distributed Smart Camera Networks for Wide-Area Surveillance |
| title_fullStr | Collaborative 3D Target Tracking in Distributed Smart Camera Networks for Wide-Area Surveillance |
| title_full_unstemmed | Collaborative 3D Target Tracking in Distributed Smart Camera Networks for Wide-Area Surveillance |
| title_short | Collaborative 3D Target Tracking in Distributed Smart Camera Networks for Wide-Area Surveillance |
| title_sort | collaborative 3d target tracking in distributed smart camera networks for wide area surveillance |
| topic | distributed smart cameras target tracking wide-area surveillance |
| url | http://www.mdpi.com/2224-2708/2/2/316 |
| work_keys_str_mv | AT xenofonkoutsoukos collaborative3dtargettrackingindistributedsmartcameranetworksforwideareasurveillance AT manishkushwaha collaborative3dtargettrackingindistributedsmartcameranetworksforwideareasurveillance |