@inproceedings{c8dbee9240624353beec02c5d8589d34,
title = "Freedom: online activity recognition via dictionary-based sparse representation of RFID sensing data",
abstract = "Understanding and recognizing the activities performed by people is a fundamental research topic for a wide range of important applications such as fall detection of elderly people. In this paper, we present the technical details behind Freedom, a low-cost, unobtrusive system that supports independent living of the older people. The Freedom system interprets what a person is doing by leveraging machine learning algorithms and radio-frequency identification (RFID) technology. To deal with noisy, streaming, unstable RFID signals, we particularly develop a dictionary-based approach that can learn dictionaries for activities using an unsupervised sparse coding algorithm. Our approach achieves efficient and robust activity recognition via a more compact representation of the activities. Extensive experiments conducted in a real-life residential environment demonstrate that our proposed system offers a good overall performance (e.g., achieving over 96% accuracy in recognizing 23 activities) and has the potential to be further developed to support the independent living of elderly people.",
keywords = "Activity recognition, Dictionary, Feature selection, RFID, Sensing data, Sparse coding",
author = "Lina Yao and Sheng, {Quan Z.} and Xue Li and Sen Wang and Tao Gu and Wenjie Ruan and Wan Zou",
year = "2015",
doi = "10.1109/ICDM.2015.102",
language = "English",
series = "IEEE International Conference on Data Mining",
publisher = "Institute of Electrical and Electronics Engineers (IEEE)",
pages = "1087--1092",
editor = "Charu Aggarwal and Zhi-Hua Zhou and Alexander Tuzhilin and Hui Xiong and Xindong Wu",
booktitle = "Proceedings - 15th IEEE International Conference on Data Mining",
address = "United States",
note = "15th IEEE International Conference on Data Mining, ICDM 2015 ; Conference date: 14-11-2015 Through 17-11-2015",
}