Player identification by motion features in sport videos using wearable sensors

Hamatani, Takashi; Sakaguchi, Yudai; Uchiyama, Akira; Higashino, Teruo

doi:10.1109/icmu.2016.7742086

Cited by 3 publications

(1 citation statement)

References 14 publications

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“…In this study, seven male players were tested on an outdoor court in daylight conditions. A method to identify sports players in videos has been proposed by (Hamatani et al, 2016), where the identification was achieved by motion feature matching between (unknown) players in videos (the features were obtained from estimated postures in the videos) and wearable sensors whose IDs were already known. The experimental results showed that the proposed method successfully identified 10 players with 72% accuracy.…”

Section: Introductionmentioning

confidence: 99%

Multiview Human Body Tracking of Hurdle Clearance: A Case Study

Krzeszowski¹,

Przednówek²,

Wiktorowicz³

et al. 2017

Proceedings of the 5th International Congress on Sport Sciences Research and Technology Support

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This initial research is a case study that uses a multiview human body tracking method as a tool to measure hurdle clearance kinematic parameters. This study is conducted on a hurdler representing a high sport level, who is a participant in the European and World Championships and the Olympic Games. The video recordings were made under simulated starting conditions of a 110 m hurdle race. Kinematic parameters are estimated based on the analysis of images from a multicamera system. The images were recorded with a resolution of 1920x1080 and with a frequency of 100 Hz. The proposed method does not use any special clothes, markers or other estimation support techniques. The parameters of the hurdle clearance were compared with the parameters obtained from ground truth poses. Mean Absolute Error and Mean Relative Error were used as the quality criteria.

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Section: Introductionmentioning

confidence: 99%