文章基本信息

标题：Vehicle recognition in acoustic sensor networks using multiple kernel sparse representation over learned dictionaries
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作者：Rui Wang ; Wenming Cao ; Zhihai He 等
期刊名称：International Journal of Distributed Sensor Networks
印刷版ISSN：1550-1329
电子版ISSN：1550-1477
出版年度：2017
卷号：13
期号：4
页码：1
DOI：10.1177/1550147717701435
出版社：Hindawi Publishing Corporation
摘要：Sparse representation–based classification and kernel methods have emerged as important methods for pattern recognition. In this work, we study the problem of vehicle recognition using acoustic sensor networks in real-world applications. To improve the recognition accuracy with noise sensor data collected from challenging sensing environments, we develop a new method, called multiple kernel sparse representation–based classification, for vehicle recognition. In the proposed multiple kernel sparse representation–based classification method, acoustic features of vehicles are extracted and mapped into a high-dimensional feature space using a kernel function, which combines multiple kernels to obtain linearly separable samples. To improve the recognition accuracy, we incorporate dictionary learning method K-singular value decomposition into the multiple kernel sparse representation–based classification framework. The vehicle recognition from acoustic sensor network is then formulated into an optimization problem. Our extensive experimental results demonstrate that the proposed multiple kernel sparse representation–based classification method with learned dictionaries outperforms other existing methods in the literature on vehicle recognition from complex acoustic sensor network datasets.
关键词：Multiple kernel sparse representation–based classification; K-singular value decomposition; vehicle recognition; sensor networks