Position estimation of pedestrians in surveillance video using face detection and simple camera calibration

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

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.

Original languageEnglish
Title of host publicationProceedings of MVA 2021 - 17th International Conference on Machine Vision Applications
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9784901122207
DOIs
Publication statusPublished - 2021 Jul 25
Event17th International Conference on Machine Vision Applications, MVA 2021 - Aichi, Japan
Duration: 2021 Jul 252021 Jul 27

Publication series

NameProceedings of MVA 2021 - 17th International Conference on Machine Vision Applications

Conference

Conference17th International Conference on Machine Vision Applications, MVA 2021
Country/TerritoryJapan
CityAichi
Period21/7/2521/7/27

ASJC Scopus subject areas

  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Signal Processing

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