| 基于智能手机传感器和SC\|HMM算法的行为识别 |
| |
| 引用本文： | 孙冰怡,吕 巍,李文洋.基于智能手机传感器和SC\|HMM算法的行为识别[J].吉林大学学报(理学版),2013,51(6):1128-1132. |
| |
| 作者姓名： | 孙冰怡 吕 巍 李文洋 |
| |
| 作者单位： | 吉林大学 计算机科学与技术学院, 长春 130012 |
| |
| 摘 要： | 在获取智能手机传感器信号的基础上, 提出一种基于谱聚类和隐Markov模型的日常行为识别算法. 该方法利用智能手机获取的加速度、 地理位置和接受信号强度等数据, 结合谱聚类分析和隐Markov模型学习, 能有效地对用户日常行为进行自动识别. 实验结果表明, 在真实的手机数据集中, 该方法具有较高的准确度.
|
| 关 键 词： | 智能手机 传感器 行为识别 隐Markov模型 谱聚类 |
| 收稿时间： | 2013-07-11 |
Activity Recognition Based on Smart Phone Sensors and SC-HMM Algorithm |
| |
| SUN Bing yi,LV Wei,LI Wen yang.Activity Recognition Based on Smart Phone Sensors and SC-HMM Algorithm[J].Journal of Jilin University: Sci Ed,2013,51(6):1128-1132. |
| |
| Authors: | SUN Bing yi LV Wei LI Wen yang |
| |
| Institution: | College of Computer Science and Technology, Jilin University, Changchun 130012, China |
| |
| Abstract: | A daily behavior recognition algorithm based on spectral clustering algorithm and hidden Markov model was proposed by utilizing sensor data of smart phones. After the acceleration, GPS and RSSI data were obtained, our method combined spectral clustering algorithm with hidden Markov model can automatically and effectively identify user behavior. Experimental results show that the proposed method achieved higher recognition accuracy from the reality data. |
| |
| Keywords: | smart phone sensor activity recognition hidden Markov model spectral clustering |
|
| 点击此处可从《吉林大学学报(理学版)》浏览原始摘要信息 |
| 点击此处可从《吉林大学学报(理学版)》下载免费的PDF全文 |
