Research Article
An Action Recognition Method Based on Wearable Sensors
@INPROCEEDINGS{10.1007/978-3-030-05888-3_19, author={Fuliang Ma and Jing Tan and Xiubing Liu and Huiqiang Wang and Guangsheng Feng and Bingyang Li and Hongwu Lv and Junyu Lin and Mao Tang}, title={An Action Recognition Method Based on Wearable Sensors}, proceedings={Ad Hoc Networks. 10th EAI International Conference, ADHOCNETS 2018, Cairns, Australia, September 20-23, 2018, Proceedings}, proceedings_a={ADHOCNETS}, year={2018}, month={12}, keywords={Action recognition Wearable sensors Wearing scheme}, doi={10.1007/978-3-030-05888-3_19} }- Fuliang Ma
Jing Tan
Xiubing Liu
Huiqiang Wang
Guangsheng Feng
Bingyang Li
Hongwu Lv
Junyu Lin
Mao Tang
Year: 2018
An Action Recognition Method Based on Wearable Sensors
ADHOCNETS
Springer
DOI: 10.1007/978-3-030-05888-3_19
Abstract
In the field of human action recognition, some existing works are mainly focused on macro actions, e.g., the requirements for action recognition is walking or jumping, while others are concentrated on micro actions, e.g., hand waving or leg raising. However, existing works rarely consider the recognition effect of different sensor wearing schemes with various requirements. In this work, the influences of the wearing scheme on action recognition effect are taken into account, a universal action recognition method to adapt different recognition requirements is developed. First, we present an action layered verification model which includes static action layer, dynamic action layer and joint presentation layer, which is used to provide an optional wearing scheme for each layer and to prevent wrong classification problems. Second, we verify the recognition effect of various wearing schemes under different layers. Finally, an action recognition method based on decision tree is introduced to adapt different requirements. The experiments show that the proposed method achieves a desirable recognition effect in comparison to existing ones.
