@inproceedings{f5cd3348a2ba4245b6cb1924599fba37,
title = "Automatic Seizure Detection in Face Videos Based on CWT",
abstract = "Magnifying micro movements of natural videos that are undetectable by human eye have recently received considerable interests. This is due to its impact on numerous applications. Seizure has been classified as a dangerous symptom of a victim's behavior. It is an indication of abnormality in the brain neuro activity which can lead to a damage of brain cells and victims gets worse rapidly. In this paper, we introduce a novel Radon Transform based technique on Dual Tree Complex Wavelet DT-CWT coefficients that can give an indication of early seizure signs from videos by magnifying micro movements in a complete automatic manner, without any human interaction. We modify the phases of the CWT wavelet coefficients of successive video frames, in order to detect any minor change in the object's spatial position. We limited our experiments to baby video due to data availability and privacy conformity. We were able to detect all cases of true seizure in our limited database as will be illustrated in our simulation results. Our results show that our proposed system can be utilized for automatic seizure detection and analysis.",
keywords = "Complex Wavelet Transform, Dual-Tree Complex Wavelet Transform, Face Video, Radon Transform, Seizure Detection",
author = "Gamal Fahmy and Illiyasu, \{Abdul M.\} and Ayman Tawfik",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 2018 IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2018 ; Conference date: 06-12-2018 Through 08-12-2018",
year = "2018",
month = jul,
day = "2",
doi = "10.1109/ISSPIT.2018.8642670",
language = "English",
series = "2018 IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2018",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "58--62",
booktitle = "2018 IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2018",
address = "United States",
}