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Conference Paper
A Comparative Study on Multi-object Tracking Methods for Sports Events
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- Authors
- Sungwon MOON, Jiwon LEE, Dowon NAM, Howon KIM, Wonjun KIM
- Issue Date
- 2017-02
- Citation
- International Conference on Advanced Communication Technology (ICACT) 2017, pp.883-885
- Publisher
- IEEE
- Language
- English
- Type
- Conference Paper
- Abstract
- Due to the rapid growth of machine learning technology, there is a need for research to automatically recognize objects and analyze their behavior in various fields, as is the case with sports. Currently, a system for detecting and tracking multiple objects in a sporting event is not accurate enough. Since most of the services depend on the manual operation of an experienced operator, it is necessary to develop a real time tracking technique for detecting the position of an object. In this paper, we propose an algorithm for multi-object tracking in a sporting event by presenting the results of comparing the performance of existing algorithms for multi-object tracking.
- KSP Keywords
- Learning Technology, Manual operation, Multiple objects, Rapid growth, Real-Time Tracking, Sports events, Tracking technique, comparative study, machine Learning, multi-object tracking, need for