Human pose estimation of ski jumpers based on video

Wenxia Bao; Tao Niu; Nian Wang; Xianjun Yang

doi:10.1117/12.2639724

19 October 2022 Human pose estimation of ski jumpers based on video

Wenxia Bao, Tao Niu, Nian Wang, Xianjun Yang

Proceedings Volume 12294, 7th International Symposium on Advances in Electrical, Electronics, and Computer Engineering; 122942Y (2022) https://doi.org/10.1117/12.2639724
Event: 7th International Symposium on Advances in Electrical, Electronics and Computer Engineering (ISAEECE 2022), 2022, Xishuangbanna, China

Abstract

Ski jumping is a fast and wide-range motion. Although wearable devices are available to analyze the motion, it is cumbersome and difficult to implement. Since video data is relatively simple to obtain, this paper proposes a video-based method for estimating the pose of ski jumpers. In this method, we use a high-speed camera as a video data collector, and use Simi Motion software to convert the video into frames and manually annotate keypoints. The video data of three athletes is used to build the training set, and another is used to build the test set. In addition, we use High-Resolution Net (HRNet) to transfer the learning of feature knowledge from the public dataset COCO2017 to the task of ski jumpers pose estimation. The experiments show that under the real labeled bounding box, an average precision of 84.6% is obtained, which is higher than other mainstream human pose estimate methods.

Citation Download Citation

Wenxia Bao, Tao Niu, Nian Wang, and Xianjun Yang "Human pose estimation of ski jumpers based on video", Proc. SPIE 12294, 7th International Symposium on Advances in Electrical, Electronics, and Computer Engineering, 122942Y (19 October 2022); https://doi.org/10.1117/12.2639724

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