基于视觉压缩感知的传感网络行人目标辨识方法.pdfVIP

35 11 Vol. 35 No. 11 2014 11 Chinese Journal of Scientific Instrument Nov. 2014 * 基于视觉压缩感知的传感网络行人目标辨识方法 谈宇奇, 王 雪, 林奎成 (清华大学精密仪器系 精密测试技术及仪器国家重点实验室 北京 100084) 摘 要: 行人目标辨识是指在视觉传感网络中识别检测到的目标, 对智能安防具有重要意义。对行人目标辨识所需数据进 行压缩可提高视觉传感网络行人目标辨识的实时性。提出了一种基于视觉压缩感知的传感网络行人目标辨识方法。无线视 觉节点获取行人目标图像后, 首先提取图像中行人脸部的尺度不变特征, 并采用特征字典对目标进行稀疏表示, 得到目标 特征直方图。然后视觉节点应用压缩感知方法对特征直方图进行数据压缩, 并传输至中心节点。最后, 中心节点应用非负 正交匹配追踪算法重构特征直方图, 并采用支持向量机对特征直方图进行分类辨识。实验表明, 该方法能够在不影响行人 目标辨识准确率的前提下, 有效减少在视觉传感网络中进行行人目标辨识时所需传输的数据量。 关键词: 行人目标辨识; 压缩感知; 数据关联; 视觉传感网络 中图分类号: TP391.4 文献标识码: A 国家标准学科分类代码: 520.60 Visual compressive sensing-based pedestrian identification in sensor networks Tan Yuqi, Wang Xue, Lin Kuicheng (Department of Precision Instrument , State Key Laboratory of Precision Measurement Technology and Instruments, Tsinghua University, Beijing 100084, China) Abstract: Pedestrian identification is to identify a detected target emerged in visual sensor networks, which is important for the applications of intelligence security. Data compression for the pedestrian identification can enhance the instantaneity. This paper proposes a visual compressive sensing based pedestrian identification scheme in sensor networks. In this scheme, scale-invariant features are extracted and represented by a sparse feature histogram via feature dictionary. After that, the histo- gram is compressed according to compressive sensing theory and sent by the node to the s