A linear CCD sensor reads temporal data from a CCD array continuously and forms 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. This work revisits the capabilities of the sensors in data processing, compression, and streaming in the framework of wireless sensor network. We focus on several unsolved issues 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.

My Publications:

• S. Bagheri, J. Y. Zheng, S. Sinha, Temporal mapping of surveillance video from indexing and summarization, Computer Vision and Image Understanding (CVIU), 144, 237-257, 2016.
• S. Bagheri, J. Y. Zheng, Temporal mapping of surveillance video, 22th International Conference on Pattern Recognition (ICPR), 4128-4133, 2014.

• J. Y. Zheng, S. Sinha, Line cameras for monitoring and surveillance sensor networks, ACM Conf. Multimedia 07, 433-442, Augsburg, Germany, 2007 (pdf).

• Jiang Yu Zheng, Line cameras in wireless visual sensor networks, Book Chapter in Visual Information Processing in Wireless Sensor Networks: Technology, Trends and Applications Li-Minn Ang and Kah Phooi Seng Ed., IGI Global 2011

   

   

Last modified: 10/01/11