Analyzing Cricket Biomechanical Parameters Through Keypoint Detection and Tracking

Author:

Pandey PranayORCID,Dhruv Shindhe S.,Omkar S. N.ORCID

Publisher

Springer Nature Switzerland

Reference7 articles.

1. Noorbhai, H.: Biomechanical Implications of the Batting Backlift Technique in Cricket: a Collation of Current Evidence. University of Johannesburg, Johannesburg, South Africa (2016)

2. Ghasemzadeh, S.A., Van Zandycke, G., De Vleeschouwer, C.: DeepSportLab: a Unified Framework for Ball Detection, Player Instance Segmentation and Pose Estimation in Team Sports Scenes (2021)

3. Khan, M.Z., Hassan, M.A., Farooq, A., Khan, M.U.G.: Deep CNN based data-driven recognition of cricket batting shots. In: 2018 International Conference on Applied and Engineering Mathematics (ICAEM), pp. 67–71. IEEE (2018)

4. Foysal, M.A., Islam, M.S., Karim, A., Neehal, N.: Shot-Net: a convolutional neural network for classifying different cricket shots. In: International Conference on Recent Trends in Image Processing and Pattern Recognition, pp. 111–120. Springer, Singapore (2018). https://doi.org/10.1007/978-981-13-9181-1_10

5. Thomas, G., Gade, R., Moeslund, T.B., Carr, P., Hilton, A.: Computer vision for sports: current applications and research topics. Computer Vision and Image Understanding 159 (2017)

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