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An Architecture for Automated Scene Understanding

Authors: Ruth Aguilar-Ponce; Ashok Kumar 0001; Jose Luis Tecpanecatl-Xihuitl; Magdy A. Bayoumi;

An Architecture for Automated Scene Understanding

Abstract

This paper presents distributed, automated, scene surveillance architecture. Object detection and tracking is performed by a set of region and object agents. The area under surveillance is divided in several sub-areas. One camera is assigned to each sub-area. A region agent is responsible for monitoring a given sub-area. Background subtraction is first performed on the scene taken by the camera. Based on the foreground mask, the region agent segments the incoming frame and creates object agents dedicated to tracking detected objects. Tracking information and segments are sent to a scene processing unit that analyzed this information and determined if a threat pattern is present at the scene and performed appropriate action.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
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