文档介绍：哈尔滨工业大学学报
Journal of Harbin Institute of Technology
ISSN 0367-6234,CN 23-1235/T
3 种步态运动状态下的数据库；最后,选择支持向
量机中的多分类方法完成步态识别，在识别过程中通过 K-CV 法对分类器参数进行了寻优。实验结果表明：足底压力分区方
式增加了特征识别点，提高了模型识别率；在正常步态运动条件下的平均识别率为 %，在背包和穿大衣的情况下模型
识别性能下降比较少。融合视觉和触觉特征建立包含上肢摆动的全身步态模型可以有效提高模型在复杂步态运动条件下的鲁
棒性和步态识别准确率。
关键词：步态识别; 全身步态运动模型; 视触融合; 特征提取; 支持向量机
中图分类号：TP273 文献标志码：A
Visual-tactile fusion gait recognition based on full-body gait model
LI Yu1,2，JI Wenbin1,2,DAI Shijie1,2
(1. State Key Laboratory of Reliability and Intelligence of Electrical Equipment(Hebei University of Technology)，Tianjin 300130，
China；2. School of Mechanical Engineering，Hebei University of Technology，Tianjin 300000，China)
Abstract：To reduce the influence of factors such as backpack load, clothing and environment on gait recognition rate, a full-body
gait model fusing visual and tactile features was proposed. The model first took the support foot as the starting point, established the
kinetic relationship between the mass of each body part and the ground support force according to