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Proceedings Paper

Task-oriented quality assessment and adaptation in real-time mission critical video streaming applications
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Paper Abstract

In recent years video traffic has become the dominant application on the Internet with global year-on-year increases in video-oriented consumer services. Driven by improved bandwidth in both mobile and fixed networks, steadily reducing hardware costs and the development of new technologies, many existing and new classes of commercial and industrial video applications are now being upgraded or emerging. Some of the use cases for these applications include areas such as public and private security monitoring for loss prevention or intruder detection, industrial process monitoring and critical infrastructure monitoring. The use of video is becoming commonplace in defence, security, commercial, industrial, educational and health contexts. Towards optimal performances, the design or optimisation in each of these applications should be context aware and task oriented with the characteristics of the video stream (frame rate, spatial resolution, bandwidth etc.) chosen to match the use case requirements. For example, in the security domain, a task-oriented consideration may be that higher resolution video would be required to identify an intruder than to simply detect his presence. Whilst in the same case, contextual factors such as the requirement to transmit over a resource-limited wireless link, may impose constraints on the selection of optimum task-oriented parameters. This paper presents a novel, conceptually simple and easily implemented method of assessing video quality relative to its suitability for a particular task and dynamically adapting videos streams during transmission to ensure that the task can be successfully completed. Firstly we defined two principle classes of tasks: recognition tasks and event detection tasks. These task classes are further subdivided into a set of task-related profiles, each of which is associated with a set of taskoriented attributes (minimum spatial resolution, minimum frame rate etc.). For example, in the detection class, profiles for intruder detection will require different temporal characteristics (frame rate) from those used for detection of high motion objects such as vehicles or aircrafts. We also define a set of contextual attributes that are associated with each instance of a running application that include resource constraints imposed by the transmission system employed and the hardware platforms used as source and destination of the video stream. Empirical results are presented and analysed to demonstrate the advantages of the proposed schemes.

Paper Details

Date Published: 27 February 2015
PDF: 9 pages
Proc. SPIE 9400, Real-Time Image and Video Processing 2015, 94000M (27 February 2015); doi: 10.1117/12.2078741
Show Author Affiliations
James Nightingale, Univ. of the West of Scotland (United Kingdom)
Qi Wang, Univ. of the West of Scotland (United Kingdom)
Christos Grecos, Univ. of the West of Scotland (United Kingdom)

Published in SPIE Proceedings Vol. 9400:
Real-Time Image and Video Processing 2015
Nasser Kehtarnavaz; Matthias F. Carlsohn, Editor(s)

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