Driver Fatigue Recognition Based on Supervised LPP and MKSVM

摘要：

Driver fatigue is a significant factor in many traffic accidents. In this paper, a novel approach is proposed to recognize driver fatigue. First of all, in order to extract effective feature of fatigue expression from face images, supervised locality preserving projections (SLPP) is adopted, which can solve the problem that LPP ignores the within-class local structure by adopting prior class label information. And then multiple kernels support vector machines (MKSVM) is employed to recognizing fatigue expression, Compared to SVM, which can improve the interpretability of decision function and performance of fatigue recognition. Experimental results are shown to demonstrate the effectiveness of the proposed method.

关键词： Fatigue Expression SLPP MKSVM

作者: Huang wei Zhang wei

作者单位: Department of Computer and Information Engineering , Changsha Aeronautical Vocational and Technical College of Information Science and Engineering , Central South University , Changsha , China

会议类型: 国际会议

会议名称: Third International Conference on Digital Image Processing(ICDIP 2011)(第三届数字图像处理国际会议)

会议地点: 成都

会议语种:英文

页码: 320-325

在线出版日期: 2011-04-15（万方平台首次上网日期，不代表论文的发表时间）