Distributed online visual sensor network reconfiguration for resource-aware coverage and task assignment

Dieber, Bernhard; Rinner, Bernhard

doi:10.1109/glocom.2013.6831086

Cited by 3 publications

(6 citation statements)

References 17 publications

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“…Quality of service is other way to determine content quality. An example is requiring that the targets must be covered by a determined frame rate and quantity of pixels on targets, under the constraint of not exceeding the available resources (processing, memory and energy) [83,84].…”

Section: Miscellaneousmentioning

confidence: 99%

A Survey on Monitoring Quality Assessment for Wireless Visual Sensor Networks

et al. 2022

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Wireless visual sensor networks have been adopted in different contexts to provide visual information in a more flexible and distributed way, supporting the development of different innovative applications. Although visual data may be central for a considerable set of applications in areas such as Smart Cities, Industry 4.0, and Vehicular Networks, the actual visual data quality may be not easily determined since it may be associated with many factors that depend on the characteristics of the considered application scenario. This entails several aspects from the quality of captured images (sharpness, definition, resolution) to the characteristics of the networks such as employed hardware, power consumption, and networking efficiency. In order to better support quality analysis and performance comparisons among different wireless visual sensor networks, which could be valuable in many monitoring scenarios, this article surveys this area with special concern on assessment mechanisms and quality metrics. In this context, a novel classification approach is proposed to better categorize the diverse applicable metrics for quality assessment of visual monitoring procedures. Hence, this article yields a practical guide for analyzing different visual sensor network implementations, allowing fairer evaluations and comparisons among a variety of research works. Critical analysis are also performed regarding the relevance and usage of the proposed categories and identified quality metrics. Finally, promising open issues and research directions are discussed in order to guide new developments in this research field.

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Section: Miscellaneousmentioning

confidence: 99%

A Survey on Monitoring Quality Assessment for Wireless Visual Sensor Networks

et al. 2022

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“…For test purposes, the vision sensor has been embedded into a system based on the commercial FPGA-based DE0-Nano board from terasIC. The operation of the chip is fully controlled through 85 digital signals and 21 analog signals, thus enabling its integration with high-level power management schemes [ 35 , 36 ] in order to set low-power operation and idle states. The test system, together with some microphotographs of the chip, can be seen in Figure 4 .…”

Section: A Qvga Focal-plane Sensor-processor Chip With Multi-functionmentioning

confidence: 99%

Focal-Plane Sensing-Processing: A Power-Efficient Approach for the Implementation of Privacy-Aware Networked Visual Sensors

Fernández-Berni

Carmona-Galán

Rı́o

et al. 2014

Sensors

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The capture, processing and distribution of visual information is one of the major challenges for the paradigm of the Internet of Things. Privacy emerges as a fundamental barrier to overcome. The idea of networked image sensors pervasively collecting data generates social rejection in the face of sensitive information being tampered by hackers or misused by legitimate users. Power consumption also constitutes a crucial aspect. Images contain a massive amount of data to be processed under strict timing requirements, demanding high-performance vision systems. In this paper, we describe a hardware-based strategy to concurrently address these two key issues. By conveying processing capabilities to the focal plane in addition to sensing, we can implement privacy protection measures just at the point where sensitive data are generated. Furthermore, such measures can be tailored for efficiently reducing the computational load of subsequent processing stages. As a proof of concept, a full-custom QVGA vision sensor chip is presented. It incorporates a mixed-signal focal-plane sensing-processing array providing programmable pixelation of multiple image regions in parallel. In addition to this functionality, the sensor exploits reconfigurability to implement other processing primitives, namely block-wise dynamic range adaptation, integral image computation and multi-resolution filtering. The proposed circuitry is also suitable to build a granular space, becoming the raw material for subsequent feature extraction and recognition of categorized objects.

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“…Due to this simple protocol, we can quickly react to changed environmental circumstances and detected events in the monitored area. The distributed algorithm is fast and has good scalability and is therefore feasible for online reconfiguration in dynamic environments [5].…”

Section: Distributed Configurationmentioning

confidence: 99%

“…The goal is to select the best camera for track- Table 1. Comparison of the centralized and distributed configuration algorithm using 4 different scenarios [5]. Average, minimum and maximum deviation in predicted solution quality after the initial assignment (second column) and number of messages of the initial assignment (third column) as well as the ratio of optimal solutions found initially and after re-evaluation (fourth column) are shown.…”

Section: Proprioceptive Configurationmentioning

confidence: 99%

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Resource-aware configuration in smart camera networks

Rinner

Dieber

Esterle

et al. 2012

2012 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops

Self Cite

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A recent trend in smart camera networks is that they are able to modify the functionality during runtime to better reflect changes in the observed scenes and in the specified monitoring tasks. In this paper we focus on different configuration methods for such networks. A configuration is given by three components: (i) a description of the camera nodes, (ii) a specification of the area of interest by means of observation points and the associated monitoring activities, and (iii) a description of the analysis tasks. We introduce centralized, distributed and proprioceptive configuration methods and compare their properties and performance.

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Distributed online visual sensor network reconfiguration for resource-aware coverage and task assignment

Cited by 3 publications

References 17 publications

A Survey on Monitoring Quality Assessment for Wireless Visual Sensor Networks

A Survey on Monitoring Quality Assessment for Wireless Visual Sensor Networks

Focal-Plane Sensing-Processing: A Power-Efficient Approach for the Implementation of Privacy-Aware Networked Visual Sensors

Resource-aware configuration in smart camera networks

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