Computer Science ›› 2016, Vol. 43 ›› Issue (12): 297-301.doi: 10.11896/j.issn.1002-137X.2016.12.055

Previous Articles     Next Articles

Human Motion Activity Recognition Model Based on Multi-classifier Fusion

WANG Zhong-min, WANG Ke and HE Yan   

  • Online:2018-12-01 Published:2018-12-01

Abstract: To improve the accuracy of human activity recognition based on the triaxial acceleration data from mobile sensors,an activity recognition model based on multiple classifier fusion (MCF) was proposed.The features which are high correlated with each daily activity (staying,walking,running,going upstairs and going downstairs) are extracted from the original acceleration data to generate the five feature data sets to train the five base classifiers.The input of the five base classifiers are these feature data sets,and their output are processed using multi-classifier fusion algorithm to produce the final activity recognition result.The experimental results show that the average activity recognition accuracy and the reliability by using MCF are respectively 96.84% and 97.41%,and it can effectively identify human activities.

Key words: Activity recognition,Triaxial acceleration,Base classifier,Multi-classifier fusion

[1] Wang Zhong-min,Cao Dong.A Feature Selection Method for Be-havior Recognition Based onAnt Colony Algorithm[J].Journal of Xi’an University of Posts & Telecommunications,2014,9(1):73-77(in Chinese) 王忠民,曹栋.基于蚁群算法的行为识别特征优选方法[J].西安邮电大学学报,2014,9(1):73-77
[2] Wang Tai-qing,Wang Sheng-jin,Ding Xiao-qing.Human Action Detection Based on Tracking Region of Maximum Mutual Information[J].Acta Automatica Sinica,2012,8(12):2023-2031(in Chinese) 王泰青,王生进,丁晓青.基于最大互信息区域跟踪的人体行为检测算法[J].自动化学报,2012,8(12):2023-2031
[3] Huang Wan-wen,Zhang Yao,Li Bao-jun.Ultracompact Wave-length and Polarization Splitters in Periodic Dielectric Waveguides [J].Optics Express,2008,6(3):1600-1609
[4] Wang Zhong-min,Wang Bin.Feature Selection Method for Mobile User Behavior Recognition Basedon Multiband Time Domain Decomposition[J].Application Research of Computers,2015,2(7):1956-1958(in Chinese) 王忠民,王斌.多频段时域分解的行为为识别特征优选方法[J].计算机应用研究,2015,2(7):1956-1958
[5] Zhao Hai-yong,Jia Bao-xian.Human Action Recognition Using Image Contour[J].Computer Science,2013,0(2):312-315(in Chinese) 赵海勇,贾保先.基于轮廓特征的人体行为识别[J].计算机科学,2013,0(2):312-315
[6] Young-Seol L,Sung-Bae C.Activity Recognition with AndroidPhone Using Mixture-of-experts Co-trained with Labeled and Unlabeled Data[J].Neurocomputing,2014,6(3):106-115
[7] Fan Lin,Wang Zhong-min.Human Activity Recognition Model Based on Location-independent Accelerometer[J].Application Research of Computers,2015,2(1):63-66(in Chinese) 范琳,王忠民.穿戴位置无关的手机用户行为识别模型[J].计算机应用研究,2015,2(1):63-66
[8] Surapa T.A Device-Orientation Independent Method for Activity Recognition[C]∥Proceedings of the 2010 IEEE International Conference on Body Sensor Networks (BSN).Singapore,2010:19-23
[9] Witten I H,Frank E.Data Mining:Practical Machine Learning Tools and Techniques[M].[S.l.]:Elsevier Inc,2006
[10] Yunus E U,Ozlem D I,Cem E.User,Device and Orientation Independent Human Activity Recognition on Mobile Phones:Challenges and A Proposal[C]∥Proceedings of the 2013 ACM International Joint Conference on Pervasive and Ubiquitous Computing.Zurich,Switzerland,2013:1427-1435
[11] Vo Q V,Hoang M T,Deokjai C.Adaptive Energy-saving Strategy for Activity Recognition on Mobile Phone[C]∥2012 IEEE Internation Symposium on Signal Processing and Information Technology.Chi NinhCity,Vietnam,2012:95-100
[12] Yan Zhi-xian,Subbaraju V,Chakraborty D,et al.Energy-Effi-cient Continuous Activity Recognition on Mobile Phones:An Activity-Adaptive Approach[C]∥Proceedings of the 2012 IEEE 16th International Symposium on Wearable Computers (ISWC).Newcastle,United Kingdom,2012:17-24
[13] Li Yue-xiang,Liu Yan,Yuan Tao,et al.Multiple ClassifierBased Walking Pattern Recognizing Algorithm Using Acceleration Signals[J].Acta Electronica Sinica,2009,7(8):1794-1798(in Chinese) 李月香,刘燕,袁涛,等.基于加速度信号的走路模式多级分类算法[J].电子学报,2009,7(8):1794-1798
[14] Tin K H,Hull J J,Srihari S N.Decision Combination in Multiple Classifier Systems[J].IEEE Transactions Pattern Analysis and Machine Intelligence,1994,6(1):66-75

No related articles found!
Full text



No Suggested Reading articles found!