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Penalty Kick Trajectory Prediction in Soccer Videos Using Digital Image Processing and a Deep Neural Network Model

Vin-Nnajiofor, Chifu
http://orcid.org/0000-0002-0416-792X
http://rave.ohiolink.edu/etdc/view?acc_num=ucin1649763212291042

Abstract Details

2022, MS, University of Cincinnati, Engineering and Applied Science: Electrical Engineering.
The ever-changing and rapid advances in computer vision, machine learning has paved way to unparalleled likelihoods in the broad world of sports, most especially in soccer. In current times, many professional sports teams use artificial intelligence and machine learning to improve the training and develop better strategies for competition. Great emphasis has been placed on collecting data, implementing models and techniques that help simplify set tasks by the teams. In this thesis, we developed an effective way of applying image and video processing techniques, deep learning, and machine learning models to predict penalty kicks in a soccer game. Specifically, the deep neural networks are used to analyze soccer videos and to predict penalty kicks’ trajectories. The image and video enhancement techniques are used to adjust the pixel values in the videos and improve the performance of the model which reduces the average and final displacement errors associated with predicting the trajectories of the player run up and the final kick. We conclude by extracting the visual and semantic features of the videos and testing with a multi-task prediction model in order to achieve a better result of trajectory prediction.
Wen-Ben Jone, Ph.D. (Committee Member)
Xuefu Zhou, Ph.D. (Committee Member)
92 p.
Engineering
Penalty Kick; Soccer; Image Processing; Trajectory; Neural Network Model; Prediction

Recommended Citations

Citations

  • Vin-Nnajiofor, C. (2022). Penalty Kick Trajectory Prediction in Soccer Videos Using Digital Image Processing and a Deep Neural Network Model [Master's thesis, University of Cincinnati]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1649763212291042

    APA Style (7th edition)

  • Vin-Nnajiofor, Chifu. Penalty Kick Trajectory Prediction in Soccer Videos Using Digital Image Processing and a Deep Neural Network Model. 2022. University of Cincinnati, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=ucin1649763212291042.

    MLA Style (8th edition)

  • Vin-Nnajiofor, Chifu. "Penalty Kick Trajectory Prediction in Soccer Videos Using Digital Image Processing and a Deep Neural Network Model." Master's thesis, University of Cincinnati, 2022. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1649763212291042

    Chicago Manual of Style (17th edition)

ucin1649763212291042
730
© 2022, some rights reserved.Creative Commons License Penalty Kick Trajectory Prediction in Soccer Videos Using Digital Image Processing and a Deep Neural Network Model by Chifu Vin-Nnajiofor is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License. Based on a work at etd.ohiolink.edu.
This open access ETD is published by University of Cincinnati and OhioLINK.