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arXiv · 1410.5605

Attentive monitoring of multiple video streams driven by a Bayesian foraging strategy

Paolo Napoletano·Giuseppe Boccignone·Francesco Tisato
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Abstract

In this paper we shall consider the problem of deploying attention to subsets of the video streams for collating the most relevant data and information of interest related to a given task. We formalize this monitoring problem as a foraging problem. We propose a probabilistic framework to model observer's attentive behavior as the behavior of a forager. The forager, moment to moment, focuses its attention on the most informative stream/camera, detects interesting objects or activities, or switches to a more profitable stream. The approach proposed here is suitable to be exploited for multi-stream video summarization. Meanwhile, it can serve as a preliminary step for more sophisticated video surveillance, e.g. activity and behavior analysis. Experimental results achieved on the UCR Videoweb Activities Dataset, a publicly available dataset, are presented to illustrate the utility of the proposed technique.

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Paolo Napoletano, Giuseppe Boccignone, Francesco Tisato. 2014-10-21. Attentive monitoring of multiple video streams driven by a Bayesian foraging strategy. https://doi.org/10.1109/tip.2015.2431438

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