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Conference Paper
Golf Swing Analyzing System based on Human Skeleton Data
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- Authors
- Jae-Ho Lee, Ju Yong Chang, Soonchan Park, Hyuk Jung, Ji-Young Park
- Issue Date
- 2016-02
- Citation
- Korea-Japan Joint Workshop on Frontiers of Computer Vision (FCV) 2016, pp.1-4
- Language
- English
- Type
- Conference Paper
- Abstract
- This paper presents a developed automatic golf swing analyzing system as an example application using 3D gestural interface. The developed system automatically detects golf swing motion, estimates 7 golf key poses, and shows the analyzed information of golf swing gesture. The system can be installed in narrow spaces compared with required minimum distance by rotating the depth sensor vertically. Additionally, the system can estimate skeleton points even in self-occluded body parts while the golf swing is in motion. Heuristic based golf swing detection and analyzing method is implied in the segmentation stage while skeleton estimation is based on a machine learning method. The heuristic approach is a more reasonable method in development, maintenance, and debugging for specific applications such as our golf swing detection and analyzing system, that have to show the results simultaneously in real-time. The system is currently being adapted in golf coaching lessons by providing real-time intuitive analyzed information of golf swing.
- KSP Keywords
- Body parts, Depth sensor, Gestural interfaces, Golf swing motion, Human Skeleton, Machine Learning Methods, Minimum distance, Narrow spaces, Real-time, Skeleton data, Specific applications