Recognizing Human Activities Based on Multi-sensors Fusion

摘要：

Usually the recognition of daily human activity need to collect multi-sensor data, this paper applies an information fusion algorithm based Na?ve Bayes so as to obtain higher-level contexts from a small number of sensor. The sensor data from accelerometer node are firstly classified by C4.5 Decision Tree algorithm, once the confusion matrix of each sensor node have be gotten, the sensor fusion can be performed at the classifier level by calculating the corresponding posterior probability. The Experimental results of daily human activity recognition indicate that the classifier fusion strategy based on Na?ve Bayes technique has achieved a higher correct classification by effectively fusion the classification result of hip and wrist classifiers.

作者: Liu Rong Liu Ming

作者单位: College of Physical Science and Technology Central China Normal University Wuhan, China

会议类型: 国际会议

会议名称: The 4th International Conference on Bioinformatics and Biomedical Engineering(第四届IEEE生物信息与生物医学工程国际会议 iCBBE 2010)

会议地点: 成都

会议语种:英文

页码: 1-4

在线出版日期: 2010-06-18（万方平台首次上网日期，不代表论文的发表时间）