传感技术学报2016，Vol.29Issue(5)：659-664,6.DOI:10.3969/j.issn.1004-1699.2016.05.006
基于加速度传感器的可扩展手势识别
Accelerometer-Based Extensible Hand Gesture Recognition
摘要
Abstract
This paper presents an algorithm combining machine learning model and template matching to improve the performance of accelerometer-based dynamic hand gesture recognition and enhance the extensibility of the system. Gestures are divided into two types,i.e.,the basic gesture and the complex gesture which can be decomposed into a basic gesture sequence. According to the characteristics of hand movements,effective features are extracted. A ran-dom forest model is constructed with the basic gesture samples,and then used to classify the basic gesture sequences. The predicted results are subsequently encoded with Johnson codes,and then matched with the standard template sequences by comparing the similarity. Experiment achieves 99.75% basic gesture recognition rate and 100%complex gesture recognition rate. The algorithm improves the performance as well as enhances the extensibility.关键词
手势识别/加速度传感器/手势分割/随机森林/相似度匹配Key words
gesture recognition/accelerometer/gesture segmentation/random forest/similarity matching分类
信息技术与安全科学引用本文复制引用
谢仁强,曹俊诚..基于加速度传感器的可扩展手势识别[J].传感技术学报,2016,29(5):659-664,6.基金项目
国家重点基础研究发展计划项目(2014CB339803) （2014CB339803）
国家高技术研究发展计划(863)主题项目(2011AA010205) （863）
国家自然科学基金项目(61131006) （61131006）
国家重大科学仪器设备开发专项项目(2011YQ150021) （2011YQ150021）
