@inproceedings{10fff313e3e649b0ae2c927daab57562,
title = "Unsupervised Anomaly Detection of the First Person in Gait from an Egocentric Camera",
abstract = "Assistive technology is increasingly important as the senior population grows. The purpose of this study is to develop a means of preventing fatal injury by monitoring the movements of the elderly and sounding an alarm if an accident occurs. We present a method of detecting an anomaly in a first-person{\textquoteright}s gait from an egocentric video. Followed by the conventional anomaly detection methods, we train the model in an unsupervised manner. We use optical flow images to capture ego-motion information in the first person. To verify the effectiveness of our model, we introduced and conducted experiments with a novel first-person video anomaly detection dataset and showed that our model outperformed the baseline method.",
keywords = "Adversarial training, Assistive technology, Egocentric video, Optical flow, Unsupervised learning",
author = "Mana Masuda and Ryo Hachiuma and Ryo Fujii and Hideo Saito",
note = "Publisher Copyright: {\textcopyright} 2020, Springer Nature Switzerland AG.; 15th International Symposium on Visual Computing, ISVC 2020 ; Conference date: 05-10-2020 Through 07-10-2020",
year = "2020",
doi = "10.1007/978-3-030-64559-5_48",
language = "English",
isbn = "9783030645588",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "604--617",
editor = "George Bebis and Zhaozheng Yin and Edward Kim and Jan Bender and Kartic Subr and Kwon, {Bum Chul} and Jian Zhao and Denis Kalkofen and George Baciu",
booktitle = "Advances in Visual Computing - 15th International Symposium, ISVC 2020, Proceedings",
}