DMCtrac: Distributed multi camera tracking

Hoffmann, Martin; Wittke, Michael; Bernard, Yvonne; Soleymani, Roghayeh; Hähner, Jörg

doi:10.1109/icdsc.2008.4635684

Cited by 16 publications

(8 citation statements)

References 13 publications

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“…His work focuses on theoretical coordination and image processing topics, networking issues are not discussed. With DMCtrac [6], the authors of this paper present a similar approach to the task of object tracking that has been tailored to suit the needs of wireless networked camera systems.…”

Section: Velastin Et Al Have Worked On Intelligent Surveillancementioning

confidence: 99%

“…[3]). Therefore, cameras make use of our tracking and partitioning algorithms as described in [6], [7]. Additionally, security staff patrols the area that is observed by the cameras.…”

Section: Notificationmentioning

confidence: 99%

“…Apart from research concerning computer vision and embedded systems, the networked system architecture of large vision networks needs to be considered further. Previous work carried out by the authors of this paper dealt with self-organisation of smart cameras with respect to the alignment of the cameras' PTZ (pan, tilt, zoom) heads to achieve a high surveillance coverage and the seamless tracking of objects with multiple cameras [6], [7]. By aligning the cameras' heads with drives, the fields of view of the cameras can be adjusted to varying user demands.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Design and Evaluation of a Notification System for Alarm Management in Distributed Vision Networks

Hoffmann

Wittke

Hähner

2009

2009 29th IEEE International Conference on Distributed Computing Systems Workshops

Self Cite

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Latest research results in the areas of computer vision and embedded systems have made way for smart cameras. These cameras use a built-in computing unit to analyse images directly at the CCD sensor. Smart cameras can cooperate in order to analyse scenes from different perspectives and track objects autonomously. In large smart camera systems (also known as distributed vision networks), distributed algorithms are needed that allow for cooperation and self-organisation among cameras. This paper focuses on alarm management in distributed vision networks, in which security staff is equipped with mobile terminals. These terminals and cameras are connected via an adhoc network. We present a robust and lightweight algorithm that allows to notify guards quickly in case serious incidents have happened. This algorithm has been evaluated by simulation experiments and in a modestly sized real world testbed. Results show that the algorithm takes reasonable time to terminate (10s) in a network of 100 cameras.

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Section: Velastin Et Al Have Worked On Intelligent Surveillancementioning

confidence: 99%

“…[3]). Therefore, cameras make use of our tracking and partitioning algorithms as described in [6], [7]. Additionally, security staff patrols the area that is observed by the cameras.…”

Section: Notificationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Design and Evaluation of a Notification System for Alarm Management in Distributed Vision Networks

Hoffmann

Wittke

Hähner

2009

2009 29th IEEE International Conference on Distributed Computing Systems Workshops

Self Cite

View full text Add to dashboard Cite

show abstract

“…While a number of advances have been made in the area of camera networks, many of them seem to be geared towards having a central processing unit that takes the raw (or, at most, low-level processed) data from the cameras, in order to provide tracking across multiple cameras [1], [2], [3]. To the best of our knowledge, there are no intelligent cameras dedicated to multiple human tracking (as opposed to human detection) currently available off-the-shelf, although some efforts in that direction have been made in the last few years, such as FPGA-based single target trackers [4], [5] or DSPbased trackers [6].…”

Section: Introductionmentioning

confidence: 99%

Multiple-person tracking devoted to distributed multi smart camera networks

Zuriarrain

Aizpurua

Lerasle

et al. 2010

2010 IEEE/RSJ International Conference on Intelligent Robots and Systems

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Camera networks are an important component of modern complex systems, be it for surveillance, human/machine interaction or healthcare. Having smart cameras that can, by themselves, perform part of the data processing improves scalability both in processing and network resources. In this paper, we present the HYBRID algorithm for multiple person tracking intended for implementation on a smart camera platform, along with the development methodology to implement said algorithm in an FPGA-based smart camera. The HYBRID strategy outperforms the well-known Markov Chain Monte Carlo based particle filter (MCMC-PF) in terms of (i) parallelization capabilities as the MCMC-PF sequentially processes the particles, and (ii) tracking performances (i.e., robustness and precision).

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“…Moreover, due to the limited visual coverage of the camera, the active tracking system with single camera is not suitable for large area applications. To improve the active tracking coverage, many of these active tracking systems have been extended to incorporate multiple cameras [6][7][8][9][10].…”

Section: Introductionmentioning

confidence: 99%

Sector Based Multiple Camera Collaboration for Active Tracking Applications

Hong¹,

Kim²,

Moon³

2017

J Inf Process Syst

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This paper presents a scalable multiple camera collaboration strategy for active tracking applications in large areas. The proposed approach is based on distributed mechanism but emulates the master-slave mechanism. The master and slave cameras are not designated but adaptively determined depending on the object dynamic and density distribution. Moreover, the number of cameras emulating the master is not fixed. The collaboration among the cameras utilizes global and local sectors in which the visual correspondences among different cameras are determined. The proposed method combines the local information to construct the global information for emulating the master-slave operations. Based on the global information, the load balancing of active tracking operations is performed to maximize active tracking coverage of the highly dynamic objects. The dynamics of all objects visible in the local camera views are estimated for effective coverage scheduling of the cameras. The active tracking synchronization timing information is chosen to maximize the overall monitoring time for general surveillance operations while minimizing the active tracking miss. The real-time simulation result demonstrates the effectiveness of the proposed method

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DMCtrac: Distributed multi camera tracking

Cited by 16 publications

References 13 publications

Design and Evaluation of a Notification System for Alarm Management in Distributed Vision Networks

Design and Evaluation of a Notification System for Alarm Management in Distributed Vision Networks

Multiple-person tracking devoted to distributed multi smart camera networks

Sector Based Multiple Camera Collaboration for Active Tracking Applications

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