A Probabilistic Model of Activity Recognition with Loose Clothing

This file contains source code and dataset of paper "A Probabilistic Model of Activity Recognition with Loose Clothing". This paper proposes a probabilistic model and verifies it in a physical realisation and a real human activity recognition task. The experiment result shows that this model can be used to predict the performance of activity reignition in different situations. This study is also the first to suggest that fabric movement can be beneficial to activity recognition in a real human task. With this finding, textile-based sensors could be used for activity recognition in real-world applications. It also has many advantages, such as being able to ensure the wearer’s comfort by unobtrusive sensing and allowing the capture of natural behaviour.
For the description of code and data, please see the readme file in the dataset.

本文件包含论文《基于宽松服装的活动识别概率模型》的源代码和数据集。该论文提出了一种概率模型，并在实物实现及真实人类活动识别任务中对其进行了验证。实验结果表明，该模型可用于预测不同情境下活动复燃的性能。本研究亦首次提出，织物运动对于真实人类任务中的活动识别具有积极作用。据此发现，基于纺织品的传感器可应用于现实世界的活动识别。此外，该技术还具有诸多优势，例如通过隐蔽式感知确保穿着者的舒适性，并能够捕捉自然行为。有关代码和数据的描述，请参阅数据集中提供的readme文件。