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The motion measurement of point targets constitutes a fundamental problem in photogrammetry, with extensive applications across various engineering domains. Reconstructing a point's 3D motion just from the images captured by only a…

Computer Vision and Pattern Recognition · Computer Science 2025-02-28 Huayu Huang , Banglei Guan , Yang Shang , Qifeng Yu

Tactical understanding in badminton involves interpreting not only individual actions but also how tactics are dynamically executed over time. In this paper, we propose \textbf{Shot2Tactic-Caption}, a novel framework for semantic and…

Computer Vision and Pattern Recognition · Computer Science 2025-10-17 Ning Ding , Keisuke Fujii , Toru Tamaki

This article introduces a novel approach to shuttlecock hitting event detection. Instead of depending on generic methods, we capture the hitting action of players by reasoning over a sequence of images. To learn the features of hitting…

Computer Vision and Pattern Recognition · Computer Science 2023-06-21 Yu-Hsi Chen

The application of visual tracking to the performance analysis of sports players in dynamic competitions is vital for effective coaching. In doubles matches, coordinated positioning is crucial for maintaining control of the court and…

Computer Vision and Pattern Recognition · Computer Science 2023-10-27 Ning Ding , Kazuya Takeda , Wenhui Jin , Yingjiu Bei , Keisuke Fujii

This paper reports on the decay in shuttlecock velocity after smash and slice shots performed by elite and international players, based on the analysis of videos captured on a badminton court with high-speed cameras. The trajectories of…

Fluid Dynamics · Physics 2026-01-06 Eric Collet

In this paper, we present a neural network-based approach for tracking and reconstructing the trajectories of baseball pitches from 2D video footage to 3D coordinates. We utilize OpenCV's CSRT algorithm to accurately track the baseball and…

Computer Vision and Pattern Recognition · Computer Science 2024-05-28 Jhen Hsieh

We present a method to reconstruct the three-dimensional trajectory of a moving instance of a known object category in monocular video data. We track the two-dimensional shape of objects on pixel level exploiting instance-aware semantic…

Computer Vision and Pattern Recognition · Computer Science 2017-11-17 Sebastian Bullinger , Christoph Bodensteiner , Michael Arens , Rainer Stiefelhagen

Computer vision based object tracking has been used to annotate and augment sports video. For sports learning and training, video replay is often used in post-match review and training review for tactical analysis and movement analysis. For…

Computer Vision and Pattern Recognition · Computer Science 2019-07-31 Tzu-Han Hsu , Ching-Hsuan Chen , Nyan Ping Ju , Tsì-Uí İk , Wen-Chih Peng , Chih-Chuan Wang , Yu-Shuen Wang , Yuan-Hsiang Lin , Yu-Chee Tseng , Jiun-Long Huang , Yu-Tai Ching

The filming of sporting events projects and flattens the movement of athletes in the world onto a 2D broadcast image. The pixel locations of joints in these images can be detected with high validity. Recovering the actual 3D movement of the…

Computer Vision and Pattern Recognition · Computer Science 2023-04-11 Tobias Baumgartner , Stefanie Klatt

We focus on the task of estimating a physically plausible articulated human motion from monocular video. Existing approaches that do not consider physics often produce temporally inconsistent output with motion artifacts, while…

Computer Vision and Pattern Recognition · Computer Science 2022-05-26 Erik Gärtner , Mykhaylo Andriluka , Hongyi Xu , Cristian Sminchisescu

Despite significant progress made in the past few years, challenges remain for depth estimation using a single monocular image. First, it is nontrivial to train a metric-depth prediction model that can generalize well to diverse scenes…

Computer Vision and Pattern Recognition · Computer Science 2022-09-07 Wei Yin , Jianming Zhang , Oliver Wang , Simon Niklaus , Simon Chen , Yifan Liu , Chunhua Shen

3D object detection based on monocular camera data is a key enabler for autonomous driving. The task however, is ill-posed due to lack of depth information in 2D images. Recent deep learning methods show promising results to recover depth…

Computer Vision and Pattern Recognition · Computer Science 2020-05-18 Felix Nobis , Fabian Brunhuber , Simon Janssen , Johannes Betz , Markus Lienkamp

Multi-object tracking, player identification, and pose estimation are fundamental components of sports analytics, essential for analyzing player movements, performance, and tactical strategies. However, existing datasets and methodologies…

Computer Vision and Pattern Recognition · Computer Science 2026-01-21 Kazuhiro Yamada , Li Yin , Qingrui Hu , Ning Ding , Shunsuke Iwashita , Jun Ichikawa , Kiwamu Kotani , Calvin Yeung , Keisuke Fujii

Real-time 3D trajectory player tracking in sports plays a crucial role in tactical analysis, performance evaluation, and enhancing spectator experience. Traditional systems rely on multi-camera setups, but are constrained by the inherently…

Computer Vision and Pattern Recognition · Computer Science 2025-08-22 Ryunosuke Hayashi , Kohei Torimi , Rokuto Nagata , Kazuma Ikeda , Ozora Sako , Taichi Nakamura , Masaki Tani , Yoshimitsu Aoki , Kentaro Yoshioka

Trajectories are fundamental to winning in alpine skiing. Tools enabling the analysis of such curves can enhance the training activity and enrich broadcasting content. In this paper, we propose SkiTraVis, an algorithm to visualize the…

Computer Vision and Pattern Recognition · Computer Science 2023-12-18 Matteo Dunnhofer , Luca Sordi , Christian Micheloni

We present SpatialTrackerV2, a feed-forward 3D point tracking method for monocular videos. Going beyond modular pipelines built on off-the-shelf components for 3D tracking, our approach unifies the intrinsic connections between point…

Computer Vision and Pattern Recognition · Computer Science 2025-07-22 Yuxi Xiao , Jianyuan Wang , Nan Xue , Nikita Karaev , Yuri Makarov , Bingyi Kang , Xing Zhu , Hujun Bao , Yujun Shen , Xiaowei Zhou

We introduce RacketVision, a novel dataset and benchmark for advancing computer vision in sports analytics, covering table tennis, tennis, and badminton. The dataset is the first to provide large-scale, fine-grained annotations for racket…

Computer Vision and Pattern Recognition · Computer Science 2026-01-29 Linfeng Dong , Yuchen Yang , Hao Wu , Wei Wang , Yuenan Hou , Zhihang Zhong , Xiao Sun

Recent techniques for analyzing sports precisely has stimulated various approaches to improve player performance and fan engagement. However, existing approaches are only able to evaluate offline performance since testing in real-time…

Machine Learning · Computer Science 2022-11-23 Li-Chun Huang , Nai-Zen Hseuh , Yen-Che Chien , Wei-Yao Wang , Kuang-Da Wang , Wen-Chih Peng

The increasing use of artificial intelligence (AI) technology in turn-based sports, such as badminton, has sparked significant interest in evaluating strategies through the analysis of match video data. Predicting future shots based on past…

Artificial Intelligence · Computer Science 2024-04-09 Minwoo Seong , Jeongseok Oh , SeungJun Kim

Trajectories are fundamental in different skiing disciplines. Tools enabling the analysis of such curves can enhance the training activity and enrich the broadcasting contents. However, the solutions currently available are based on…

Computer Vision and Pattern Recognition · Computer Science 2021-12-20 Matteo Dunnhofer , Alberto Zurini , Maurizio Dunnhofer , Christian Micheloni