Real-time multi pose trajectory tracking based on OpenPose keypoints
Authors:
- Adam Surówka
Abstract
Currently, there exist several open-source computer vision libraries designed for human pose estimation from photos and videos. They are mainly focused on the possibility of detecting individuals in the image and returning their skeleton determinants. An often overlooked or underdeveloped functionality is tracking the trajectory of the detected people, which presents a serious problem in the process of design automated video surveillance systems. In this work, the author attempts to develop an algorithm for tracking multiple human poses in real-time, based on simple decision filters. The developed solution is designed to work with keypoints obtained from a selected open-source human poses recognition library. The author reveals details related to the method of processing and analysing obtained keypoints, describes the concept of decision filters and presents the results of the software implementation.
- Record ID
- CUT88e308654d9b498abb03eef59d4ab872
- Publication categories
- ; ;
- Author
- Pages
- 813-817
- Other elements of collation
- fot.; schem.; tab.; wykr.; Bibliografia (na s.) - 817; Bibliografia (liczba pozycji) - 15; Oznaczenie streszczenia - Abstr.
- Substantive notes
- Data wyd. wg cop.
- Book
- IDAACS'2021 : proceedings of the 11th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS), September 22-25, 2021, Cracow, Poland : virtual conference. Vol. 2, Proceedings of the IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems, 2021, [Piscataway], Institute of Electrical and Electronics Engineers, IEEE, ISBN 978-1-6654-2605-3 (electronic)
- Keywords in English
- automated surveillance system, human pose recognition, human pose tracking, body posture analysis, computer vision, data analysis
- DOI
- DOI:10.1109/IDAACS53288.2021.9660867 Opening in a new tab
- URL
- https://ieeexplore.ieee.org/document/9660867 Opening in a new tab
- Language
- eng (en) English
- Score (nominal)
- 20
- Additional fields
- Indeksowana w: Web of Science, Scopus
- Uniform Resource Identifier
- https://cris.pk.edu.pl/info/article/CUT88e308654d9b498abb03eef59d4ab872/
- URN
urn:pkr-prod:CUT88e308654d9b498abb03eef59d4ab872
* presented citation count is obtained through Internet information analysis, and it is close to the number calculated by the Publish or PerishOpening in a new tab system.