Decentralized discovery of camera network topology

Farrell, Ryan; Davis, Larry S.

doi:10.1109/icdsc.2008.4635696

Cited by 16 publications

(9 citation statements)

References 13 publications

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“…A promising and generic approach for probabilistic object tracking with corresponding spatio-temporal events was proposed by Farrel et al [11], [12]. In this approach, a number of up to 100 simulated camera nodes process visual information in a distributed manner and notify other nodes about local events.…”

Section: Related Work In Topology Estimationmentioning

confidence: 99%

Efficient communication for large-scale robust image processing with smart camera devices

Golembewski

Schaefer

Gerlach

2012

2012 IEEE Symposium on Computational Intelligence for Security and Defence Applications

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Large-scale data acquisition and distributed processing of video material requires smart camera devices to collaborate over arbitrary transport networks with no further centralized coordinating instances. Especially in the context of surveillance and security in public transportation networks, the knowledge of spatio-temporal traffic flows can support applications like anomaly detection, smart navigation, or prosecution. Therefore, the problem of autonomously estimating a logical camera topology with respect to scalability, agility and robustness must be solved by efficient communication about distributed detected events. Simple broadcasting or flooding of information does not scale well with the number of nodes and leads to strong requirements on bandwidth and processing power. Thus, a generic system model, describing the process of generating eventbased distributed knowledge without making use of flooding, broadcast or multicast, is introduced and evaluated. The results of a conducted simulation study reveal the potential of saving a significant amount of messages on the one hand, and being able to handle poor performance of object recognition algorithms on the other hand.

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Section: Related Work In Topology Estimationmentioning

confidence: 99%

Efficient communication for large-scale robust image processing with smart camera devices

Golembewski

Schaefer

Gerlach

2012

2012 IEEE Symposium on Computational Intelligence for Security and Defence Applications

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“…Farrell and Davis (Farrell and Davis, 2008) proposed a different decentralized algorithm for topology discovery based on an information-theoretic appearance matching criterion on tracked objects moving through the network. More distinctive objects contribute proportionally more to the estimated transition model between cameras.…”

Section: Non-overlapping Topology Estimationmentioning

confidence: 99%

A Survey of Distributed Computer Vision Algorithms

Radke

2010

Handbook of Ambient Intelligence and Smart Environments

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Recent years have seen great advances in computer vision research dealing with large numbers of cameras. However, many multi-camera computer vision algorithms assume that the information from all cameras is losslessly communicated to a central processor that solves the problem. This assumption is unrealistic for emerging wireless camera networks, which may contain processors with limited capability, antennas with limited power, and batteries with limited life. In this chapter, we will overview algorithms that solve computer vision problems in a distributed manner, making them well-suited for implementation on a visual sensor network.

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“…These networks can also enable multi-resolution views (Akyildiz et al, 2007). Furthermore, the ability of object tracking in large areas is another advantage of these networks (Farrel and Davis, 2008).…”

Section: Introductionmentioning

confidence: 99%