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Edge Assisted Efficient Data Annotation for Realtime Video Big Data | IEEE Conference Publication | IEEE Xplore

Edge Assisted Efficient Data Annotation for Realtime Video Big Data


Abstract:

There is a lack of efficient video data labeling mechanism for real-time applications. Most of the labeling solutions are designed for big data offline video analytics, h...Show More

Abstract:

There is a lack of efficient video data labeling mechanism for real-time applications. Most of the labeling solutions are designed for big data offline video analytics, however emerging real-time applications with video analytics and the data-centric global trend require real-time video analytics with real-time labeling/annotation. In this paper, we present a solution that provides a per frame custom metadata that can be easily encoded and decoded and overlaid with the video frame for labeling the relevant objects/scenes. The presented solution is implemented and tested in a pilot and is leveraging edge computing capabilities to minimize the cost of using the cloud (in terms of latency and additional network resources).
Date of Conference: 21-23 October 2018
Date Added to IEEE Xplore: 30 December 2018
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Conference Location: Washington, DC, USA

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