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An informatics-based approach to object tracking for distributed live video computing

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Abstract

Omnipresent camera networks have been a popular research topic in recent years. They are applicable to a range of monitoring tasks, from bridges to gas stations to the inside of industrial chemical tanks. Though a large body of existing work focuses on image and video processing techniques, very few address the usability of such systems or the implications of real-time video dissemination. In this article, we present our work on extending the LVDBMS prototype with a multifaceted object model to characterize objects in live video streams. This forms the basis for a cross-camera tracking framework which permits objects to be tracked from one video stream to another. With this infrastructure, real-time queries may be posed to monitor complex events that occur in multiple video streams simultaneously. This live video database environment provides a general-purpose platform for distributed live video computing with the goal of enabling rapid application development for camera networks.

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Authors and Affiliations

  1. University of Central Florida, Orlando, FL, USA

    Alexander J. Aved & Kien A. Hua

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  1. Alexander J. Aved
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  2. Kien A. Hua
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Correspondence to Alexander J. Aved.

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Aved, A.J., Hua, K.A. An informatics-based approach to object tracking for distributed live video computing. Multimed Tools Appl 68, 111–133 (2014). https://doi.org/10.1007/s11042-012-1204-z

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