Titlebook: Distributed Video Sensor Networks; Bir Bhanu,Chinya V. Ravishankar,Demetri Terzopoulo Book 2011 Springer-Verlag London Limited 2011 Camera

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Africa: Central Independent Statestions such as visual surveillance to track and identify objects of interest, and overcome visual nuisances such as occlusion and pose variations between multiple camera views. To accommodate limited bandwidth between the cameras and the base-station computer, the method utilizes the available comput

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Africa: Central Independent Statesvarious tasks. One of the most basic tasks is the tracking of objects, which requires mechanisms to select a camera for a certain object and hand-off this object from one camera to another so as to accomplish seamless tracking. In this chapter, we provide a comprehensive comparison of current and em

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https://doi.org/10.1057/9780230253223hes for which objects are identified, classified, and tracked to locate objects with suspicious behavior, we proceed directly with event characterization and behavior modeling using low-level features. Our approach consists of two-phases. In the first phase, co-occurrence of activity between tempora

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Africa: Central Independent Statesfferent sources. In this chapter, we discuss two broad categories of contextual sources: environmental context and user-centric context. Environmental context refers to information derived from domain knowledge or from concurrently sensed effects in the area of operation. User-centric context refers

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The Statesman‘s Year-Book 1965-66r in order to prevent further malicious wireless broadcasts (i.e., escorting an intruder off the premises based on physical evidence). Embedded Sensor Networks (SNs) can be used to bridge the gap between digital and physical security planes, and thus can provide reciprocal benefit to security tasks