TY - GEN
T1 - Respiratory rate estimation using nostril detection in thermal video streams
AU - Mocanu, Bogdan
AU - Ţarǎlungǎ, Dragos
AU - Ţapu, Ruxandra
AU - Ţapu, Ermina
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/7/28
Y1 - 2017/7/28
N2 - In this paper we propose a complete method for breath rate estimation using thermal video streams and computer vision algorithms. The system performs subject nose detection, interest point extraction and tracking, geometric transformation and minimum thermal region estimation. All algorithms are carefully designed in order to ensure real-time capability on a regular desktop computer. The experimental evaluation validates the proposed methodology, when compared with traditional breath rate extraction methods, returning high accuracy scores.
AB - In this paper we propose a complete method for breath rate estimation using thermal video streams and computer vision algorithms. The system performs subject nose detection, interest point extraction and tracking, geometric transformation and minimum thermal region estimation. All algorithms are carefully designed in order to ensure real-time capability on a regular desktop computer. The experimental evaluation validates the proposed methodology, when compared with traditional breath rate extraction methods, returning high accuracy scores.
KW - breath rate estimation
KW - nostril tracking and detection
KW - thermal video stream
U2 - 10.1109/EHB.2017.7995396
DO - 10.1109/EHB.2017.7995396
M3 - Conference contribution
AN - SCOPUS:85028526115
T3 - 2017 E-Health and Bioengineering Conference, EHB 2017
SP - 201
EP - 204
BT - 2017 E-Health and Bioengineering Conference, EHB 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 6th IEEE International Conference on E-Health and Bioengineering, EHB 2017
Y2 - 22 June 2017 through 24 June 2017
ER -