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Search Results - Image and Vision Computing

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  1. 1

    TT3D: table tennis 3D reconstruction

    Gossard, T., Ziegler, A., Zell, A.
    Published in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops (2025)
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  2. 2

    Towards ball spin and trajectory analysis in table tennis broadcast videos via physically grounded synthetic-to-real transfer

    Kienzle, D., Schön, R., Lienhart, R., Satoh, S.
    Published in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops (2025)
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  3. 3

    Temporal pattern attention for multivariate time series of tennis strokes classification

    Skublewska-Paszkowska, M., Powroznik, P.
    Published in Sensors (2023)
    “…It interacts with many aspects of Computer Vision, Machine Learning, Deep Learning and Image Processing in order to understand human behaviours as well as identify them. …”
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  4. 4

    Prediction of shuttle trajectory in badminton using player's position

    Nokihara, Y., Hori, R., Hachiuma, R., Saito, H.
    Published in Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (2023)
    “…Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications…”
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  5. 5

    Application of computer vision and vector space model for tactical movement classification in badminton

    Weeratunga, K., Dharmaratne, A., How, K. B.
    Published in IEEE/CVF Conference on Computer Vision and Pattern Recognition (2017)
    “…The proposed approach uses computer vision techniques to automate data gathering from video footage. …”
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  6. 6

    Evaluation of open-source and pre-trained deep convolutional neural networks suitable for player detection and motion analysis in squash

    Brumann, C., Kukuk, M., Reinsberger, C.
    Published in Sensors (2021)
    “…At present, contact-free, camera-based, multi-athlete detection and tracking have become a reality, mainly due to the advances in machine learning regarding computer vision and, specifically, advances in artificial convolutional neural networks (CNN), used for human pose estimation (HPE-CNN) in image sequences. …”
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  7. 7

    Development of an image processing-based ball tracking program for table tennis

    Moon, J.-H., Lee, S.-H., Lee, J.-S., Manish, P., Ruiz Sanchez, G. A., Panday, S. B.
    Published in Korean Journal of Sport Science (2020)
    “…Methods: The algorithms used in the field of computer vision were applied on two matches played by novice and two matches during international competitions by elite athletes. …”
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  8. 8

    Vision based automated badminton action recognition using the new local convolutional neural network extractor

    Azmina Rahmad, N., Amir As`ari, M., Fauzi Ibrahim, M., Jasmin Sufri, N. A., Rangasamy, K.
    Published in MoHE 2019: Enhancing Health and Sports Performance by Design (2019)
    “…In this study, we developed a model for automated badminton action recognition from the computer vision data inputs using the deep learning pre-trained AlexNet Convolutional Neural Network (CNN) for features extraction and classify the features using supervised machine learning method which is linear Support-Vector Machine (SVM). …”
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  9. 9

    Validation of a video-based system for automatic tracking of tennis players

    Petróvna Resende Lara, J., Roveri Vieira, C. L., Shoiti Misuta, M., Arruda Moura, F., Machado Leite de Barros, R.
    Published in International Journal of Performance Analysis in Sport (2018)
    “…The method is based on algorithms for camera calibration, image pre-processing, segmentation, filtering, tracking and computer vision tools. …”
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  10. 10

    Video analysis technology and its application in badminton sports training

    Li, Y., Jiang, S.
    Published in IOP Conf. Series: Journal of Physics: Conf. Series 1213 (2019)
    “…Based on the continuous development of computer vision and graphics technology, pattern recognition and image processing technology, intelligent video analysis technology combines these related technologies to establish a mapping relationship between image description and surveillance image. …”
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  11. 11

    Attributed graphs for tracking multiple objects in structured sports videos

    Morimitsu, H., Cesar-Jr., R. M., Bloch, I.
    Published in IEEE/CVF International Conference on Computer Vision (2015)
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  12. 12

    Automatic evaluation of sports motion: A generic computation of spatial and temporal errors

    Morel, M., Achard, C., Kulpa, R., Dubuisson, S.
    Published in Image and Vision Computing (2017)
    “…Image and Vision Computing…”
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  13. 13

    Predicting shot locations in tennis using spatiotemporal data

    Wei, X., Lucey, P., Morgan, S., Sridharan, S.
    Published in International Conference on Digital Image Computing: Techniques and Applications (DICTA) (2013)
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  14. 14

    Table tennis and computer vision: A monocular event classifier

    Oldham, K. M., Chung, P. W. H., Edirisinghe, E. A., Halkon, B. J.
    Published in Proceedings of the 10th International Symposium on Computer Science in Sports (ISCSS) (2016)
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  15. 15

    A statistical method for analysis of technical data of a badminton match based on 2-D seriate images

    Chen, B., Wang, Z.
    Published in Tsinghua Science and Technology (2007)
    “…The use of computer vision technology to collect and analyze statistics during badminton matches or training sessions can be expected to provide valuable information to help coaches to determine which tactics should be used by a player in a given game or to improve the player's tactical training. …”
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  16. 16

    Tracking people in sports using video analysis

    Rasmussen, A. T., Rasmussen, H. M.
    Published 2008
    “…In this project, we wish to utilize the video information for the movement analysis, which leads us to the following main question: How can computer vision be used to analyze movement in sport events? …”
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  17. 17

    Measurement error associated with the SAGIT/Squash computer tracking software

    Vuckovic, G., Pers, J., James, N., Hughes, M.
    Published in European Journal of Sport Science (2010)
    “…The techniques used to calculate these movement parameters have ranged from human judgements to technological solutions such as GPS and computer vision. This paper evaluates the accuracy of a computerized motion tracking system (SAGIT/Squash) that uses computer vision methods on video captured via a fixed single camera located centrally above the court. …”
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