TY - GEN
T1 - Position estimation of pedestrians in surveillance video using face detection and simple camera calibration
AU - Sato, Toshio
AU - Qi, Xin
AU - Yu, Keping
AU - Wen, Zheng
AU - Katsuyama, Yutaka
AU - Sato, Takuro
N1 - Funding Information:
This work was supported by a research grant for expanding radio wave resources (JPJ000254) of the Ministry of Internal Affairs and Communications under the contract for “Research and development of radar fundamental technology for advanced recognition of moving objects for security enhancement”.
Publisher Copyright:
© 2021 MVA Organization.
PY - 2021/7/25
Y1 - 2021/7/25
N2 - Pedestrian position estimation in videos is an important technique for enhancing surveillance system applications. Although many studies estimate pedestrian positions by using human body detection, its usage is limited when the entire body expands outside of the field of view. Camera calibration is also important for realizing accurate position estimation. Most surveillance cameras are not adjusted, and it is necessary to establish a method for easy camera calibration after installation. In this paper, we propose an estimation method for pedestrian positions using face detection and anthropometric properties such as statistical face lengths. We also investigate a simple method for camera calibration that is suitable for actual uses. We evaluate the position estimation accuracy by using indoor surveillance videos.
AB - Pedestrian position estimation in videos is an important technique for enhancing surveillance system applications. Although many studies estimate pedestrian positions by using human body detection, its usage is limited when the entire body expands outside of the field of view. Camera calibration is also important for realizing accurate position estimation. Most surveillance cameras are not adjusted, and it is necessary to establish a method for easy camera calibration after installation. In this paper, we propose an estimation method for pedestrian positions using face detection and anthropometric properties such as statistical face lengths. We also investigate a simple method for camera calibration that is suitable for actual uses. We evaluate the position estimation accuracy by using indoor surveillance videos.
UR - http://www.scopus.com/inward/record.url?scp=85113961398&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85113961398&partnerID=8YFLogxK
U2 - 10.23919/MVA51890.2021.9511348
DO - 10.23919/MVA51890.2021.9511348
M3 - Conference contribution
AN - SCOPUS:85113961398
T3 - Proceedings of MVA 2021 - 17th International Conference on Machine Vision Applications
BT - Proceedings of MVA 2021 - 17th International Conference on Machine Vision Applications
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 17th International Conference on Machine Vision Applications, MVA 2021
Y2 - 25 July 2021 through 27 July 2021
ER -