Aircraft Pose Recognition Using Locally Linear Embedding

摘要：

Locally linear embedding (LLE) is a prevalent manifold learning method in pattern recognition and machine learning. It preserves the intrinsic structure information of data set and has been widely applied to feature extraction and dimensionality reduction. This paper introduces LLE to aircraft pose recognition. The representative motion poses of an aircraft in the air are analyzed. Unfolding results of aircraft images in different poses show LLE has a natural connection to clustering. Moreover, we employ back propagation neural networks and nearest neighbor algorithms to classify the input samples after dimensionality reduction. Computer simulation testifies the efficiency and accuracy of LLE in aircraft pose recognition.

关键词： LLE machine learning classify pose recognition

作者: Wenting Yuan Peng Jia Luping Wang Lin Sha

作者单位: School of Electronic Science and Engineering,National University of Defense Technology,Changsha, Hun Department of Automatic Control, College of Mechatronics and Automation,National University of Defen Unit 96115 of the Chinese PLA National University of Defense Technology,Changsha, Hunan 410073, Chin

会议类型: 国际会议

会议名称: 2009 International Conference on Measuring Technology and Mechatronics Automation(ICMTMA 2009)(2009年检测技术与机电自动化国际会议)

会议地点: 张家界

会议语种:英文

页码: 454-457

在线出版日期: 2009-04-11（万方平台首次上网日期，不代表论文的发表时间）