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Low Level Representation of Data for Visual Sensor Network

Low Level Representation of Data for Visual Sensor Network
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Author(s): Ruth Aguilar-Ponce (Universidad Autonoma de San Luis Potosi, Mexico), J. Luis Tecpanecatl-Xihuitl (Universidad Autonoma de San Luis Potosi, Mexico)and Alfonso Alba-Cadena (Universidad Autonoma de San Luis Potosi, Mexico)
Copyright: 2012
Pages: 22
Source title: Visual Information Processing in Wireless Sensor Networks: Technology, Trends and Applications
Source Author(s)/Editor(s): Li-Minn Ang (University of Nottingham Malaysia Campus, Malaysia)and Kah Phooi Seng (University of Nottingham Malaysia Campus, Malaysia)
DOI: 10.4018/978-1-61350-153-5.ch005

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Abstract

Wireless Sensor Network future direction is going towards more complex sensor such as camera sensor. Therefore, a very active research field is Visual Sensor Network. This type of network brings new challenges such as processing and transmitting a massive amount of data generated by the camera sensor. The efforts into decreasing the amount of data to be transmitted are going towards two directions: data encoding and data filtering. This chapter introduces an algorithm for each direction. Visual data encoding is performed by means of Predictive Video Encoding using Phase-Only Correlation function to achieve motion estimation. Visual data filtering is done at the lowest level of abstraction and is performed in three phases: pixel classification, background update and detection. The algorithms involved in each phase are light in terms of complexity and memory resources.

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