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Using Line Cameras for Monitoring and Surveillance Sensor Networks
Abstract
The innovative combination of wireless sensor network (WSN) technology with visual monitoring and surveillance technology in computer vision has been emerging as an important new paradigm. This emerging technology will play a crucial role in visual monitoring and surveillance for automatic object detection and tracking in applications such as real-time traffic monitoring and control, vehicle parking control, intrusion detection, security surveillance, military battlefield monitoring, and so on. Compared to traditional WSNs with scalar sensing data, the development of WVSNs presents much greater challenges in terms of node’s computation power, storage, wireless bandwidth capacity and energy conservation due to the processing and transmission of the huge amount of two-dimensional (2D) image data. We introduce the use of linear CCD sensors for wireless sensor network here. It reads temporal data from a CCD array continuously and stores them to form a 2D image profile. Compared to most of the sensors in the current sensor networks that output temporal signals, it delivers more information such as color, shape, and event of a flowing scene. On the other hand, it abstracts passing objects in the profile without heavy computation and transmits much less data than a video from normal cameras. This paper focus on several unsolved issues of line sensors in capturing targets in the 3D space such as sensor setting, shape analysis, robust object extraction, and real time background adapting to ensure long-term sensing and visual data collection via networks. All the developed algorithms are executed in constant complexity for reducing the sensor and network burden. A sustainable visual sensor network can thus be established in a large area to monitor passing objects and people for surveillance, traffic assessment, invasion alarming, etc.
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