Pitching form evaluation based on elbow position by a monocular camera

Naoto Nohara; Hidehiko Shishido; Itaru Kitahara; Yoshinari Kameda

doi:10.1117/12.2567003

1 June 2020 Pitching form evaluation based on elbow position by a monocular camera

Naoto Nohara, Hidehiko Shishido, Itaru Kitahara, Yoshinari Kameda

Author Affiliations +

Proceedings Volume 11515, International Workshop on Advanced Imaging Technology (IWAIT) 2020; 1151519 (2020) https://doi.org/10.1117/12.2567003
Event: International Workshop on Advanced Imaging Technologies 2020 (IWAIT 2020), 2020, Yogyakarta, Indonesia

Abstract

Pitching in the correct form is essential for preventing injury and improving skills. It is not easy for athletes and instructors to check whether a pitcher is throwing in the correct form. In this study, we record a pitcher from the direction of the catcher by a monocular camera and estimate the skeleton pose of the pitcher by using OpenPose. We propose a new method to evaluate whether the pitcher can pitch in the correct form by examining the estimated pose. We use SSE(Shoulder, Shoulder, Elbow)-line as an evaluation index. When the upper body of the pitcher faces a batter, the SSE-line should be straight. To find the right frame at which the pitcher body turns squarely to the batter, the distance of the shoulders in a video frame is used. When it becomes the largest, the shape of SSE-line should be measured. Since the motion of the pitcher was fast, we use a 240 fps camera to investigate the relationship between the shape of SSE-line and the shoulder distance. The relationship between the shape of the SSE-line and the shoulder distance with the 240 fps camera was evaluated, and we discussed their pitching properties based on the evaluation.

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Naoto Nohara, Hidehiko Shishido, Itaru Kitahara, and Yoshinari Kameda "Pitching form evaluation based on elbow position by a monocular camera", Proc. SPIE 11515, International Workshop on Advanced Imaging Technology (IWAIT) 2020, 1151519 (1 June 2020); https://doi.org/10.1117/12.2567003

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KEYWORDS

Cameras

Video

Photography

Injuries

Sensors

Computing systems

High speed cameras

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