A Pose Awareness Solution for Estimating Pedestrian Walking Speed

被引:26
作者
Guo, Guangyi [1 ]
Chen, Ruizhi [1 ,2 ]
Ye, Feng [1 ]
Chen, Liang [1 ]
Pan, Yuanjin [1 ]
Liu, Mengyun [1 ]
Cao, Zhipeng [1 ]
机构
[1] Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & R, Wuhan 430079, Hubei, Peoples R China
[2] Wuhan Univ, Collaborat Innovat Ctr Geospatial Technol, Wuhan 430079, Hubei, Peoples R China
关键词
smartphone; multi-sensors; posture context; walking speed estimation; RECOGNITION; TRACKING; AMBIENT; SYSTEM;
D O I
10.3390/rs11010055
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Pedestrian walking speeds (PWS) can be used as a body speedometer to reveal health status information of pedestrians and positioning indoors with other locating methods. This paper proposes a pose awareness solution for estimating pedestrian walking speeds using the sensors built in smartphones. The smartphone usage pose is identified by using a machine learning approach based on data from multiple sensors. The data are then coupled tightly with an adaptive step detection solution to estimate the pedestrian walking speed. Field tests were carried out to verify the advantages of the proposed algorithms compared to existing solutions. The test results demonstrated that the features extracted from the data of the smartphone built-in sensors clearly reveal the characteristics of the pose pattern, with overall accuracy of 98.85% and a kappa statistic of 98.46%. The proposed walking speed estimation solution, running in real-time on a commercial smartphone, performed well, with a mean absolute error of 0.061 m/s, under a challenging walking process combining various usage poses including texting, calling, swinging, and in-pocket modes.
引用
收藏
页数:18
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