Target Container: A Target-Centric Parallel Programming Abstraction for Video-based Surveillance
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Abstract
Surveillance systems are some of the most computationally
intensive applications. Despite technological advances, lowcost
of sensors, and continuous improvement of computer
vision algorithms for analyzing video data, large-scale reliable
surveillance systems are yet to become common. We
argue that building effective smart surveillance systems requires
a new approach, with a focus on programmability and
scalability. We define programmability as the productivity
of building concurrent and parallel systems. While considerable
progress has been made in the area of computer vision
algorithms, such advances cannot translate to deployment
in the large until adequate system abstractions and resource
management techniques are in place to ensure their
performance. In this paper we propose a novel abstraction, the target
container (TC). A TC is a programming and execution abstraction
that allows programmers to focus on targets, simplifying
the programming effort while allowing better resource
utilization under overloaded scenarios. A TC provides
a single interface for video surveillance application
programmers to operate on all video camera image streams
for a particular target. Each TC is mapped to a single target
and aggregates the system resources dedicated to that target.
By mapping all of the individual sensor streams presently
containing data for a particular target, the TC system is able
to more efficiently manage per-target resources and provide
an execution model that is target-aware, and improves the
overall scalability of a surveillance system in terms of the
number of targets the system can track in real time. The
TC model enables a variety of target tracking policies, including
target prioritization. Under this policy, the TC system
automatically allocates system resources based upon
programmer-specified target priority, enabling a TC-based
surveillance system to guarantee that high-priority targets
are tracked, even under conditions of system overload (i.e.,
when many targets are being tracked).We have implemented
an experimental prototype of the TC model, and measurements
confirm its performance benefits.
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Date
2010
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Technical Report