Fast Compressive Target Detection for Wireless Video Sensor Nodes
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In order to prolong the lifetime of visual target detection and tracking system based on wireless video sensor networks, many efficient methods have been proposed to reduce the energy consumption of the battery-powered video sensor nodes. Focused on reducing the amount of image data for computing, this paper presents a fast compressive method of target detection for video sensor nodes using structured compressive sensing. The major contributions are as follows: Firstly, we construct a novel structured measurement matrix for sampling the image. Secondly, we use an efficient adaptive Gaussian mixture model for real-time background subtraction. Experimental results show that our method can achieve good performance and over two times faster than traditional Gaussian mixture model.
KeywordsTarget detection Video sensor nodes Compressive sensing Structured measurement matrix
This work was supported by the National Natural Science Foundation of China under Grant 61271274, Natural Science Foundation of Hubei province, China, under Grants 2012FFA108 and 2013BHE009. Wuhan Youth Chenguang Program of Science and Technology (2014070404010209).
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Conflict of interest
The authors declare that there is no conflict of interests regarding the publication of this article.
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