A survey of depth and inertial sensor fusion for human action recognition

被引:259
作者
Chen, Chen [1 ]
Jafari, Roozbeh [2 ,3 ,4 ]
Kehtarnavaz, Nasser [1 ]
机构
[1] Univ Texas Dallas, Dept Elect Engn, Richardson, TX 75080 USA
[2] Texas A&M Univ, Dept Biomed Engn, College Stn, TX 77843 USA
[3] Texas A&M Univ, Comp Sci & Engn Dept, College Stn, TX 77843 USA
[4] Texas A&M Univ, Elect & Comp Engn Dept, College Stn, TX 77843 USA
基金
美国国家科学基金会;
关键词
Human action recognition; Activity recognition; 3Daction data; Depth sensor; Inertial sensor; Sensor fusion; Multimodal dataset; FALL DETECTION; MAPS;
D O I
10.1007/s11042-015-3177-1
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
A number of review or survey articles have previously appeared on human action recognition where either vision sensors or inertial sensors are used individually. Considering that each sensor modality has its own limitations, in a number of previously published papers, it has been shown that the fusion of vision and inertial sensor data improves the accuracy of recognition. This survey article provides an overview of the recent investigations where both vision and inertial sensors are used together and simultaneously to perform human action recognition more effectively. The thrust of this survey is on the utilization of depth cameras and inertial sensors as these two types of sensors are cost-effective, commercially available, and more significantly they both provide 3D human action data. An overview of the components necessary to achieve fusion of data from depth and inertial sensors is provided. In addition, a review of the publicly available datasets that include depth and inertial data which are simultaneously captured via depth and inertial sensors is presented.
引用
收藏
页码:4405 / 4425
页数:21
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