In this paper, we shall consider the problem of deploying attention to the 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 multistream 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 Data Set, a publicly available data set, are presented to illustrate the utility of the proposed technique.

Napoletano, P., Boccignone, G., Tisato, F. (2015). Attentive Monitoring of Multiple Video Streams Driven by a Bayesian Foraging Strategy. IEEE TRANSACTIONS ON IMAGE PROCESSING, 24(11), 3266-3281 [10.1109/TIP.2015.2431438].

Attentive Monitoring of Multiple Video Streams Driven by a Bayesian Foraging Strategy

NAPOLETANO, PAOLO
Primo
;
TISATO, FRANCESCO
Ultimo
2015

Abstract

In this paper, we shall consider the problem of deploying attention to the 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 multistream 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 Data Set, a publicly available data set, are presented to illustrate the utility of the proposed technique.
Articolo in rivista - Articolo scientifico
Activity detection; Attentive vision; Cognitive Dynamic Surveillance; Foraging theory; Intelligent sensors; Multi-camera video surveillance; Multi-stream summarisation;
Activity detection; Attentive vision; Cognitive Dynamic Surveillance; Foraging theory; Intelligent sensors; Multi-camera video surveillance; Multi-stream summarisation; Computer Graphics and Computer-Aided Design; Software
English
3266
3281
16
Napoletano, P., Boccignone, G., Tisato, F. (2015). Attentive Monitoring of Multiple Video Streams Driven by a Bayesian Foraging Strategy. IEEE TRANSACTIONS ON IMAGE PROCESSING, 24(11), 3266-3281 [10.1109/TIP.2015.2431438].
Napoletano, P; Boccignone, G; Tisato, F
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/107305
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