Skip to main content

Advertisement

SpringerLink
Log in

A novel approach for automatic detection and identification of inappropriate postures and movements of table tennis players

  • Optimization
  • Published:
Soft Computing Aims and scope Submit manuscript

Abstract

In recent years, developments in the fields of computer vision and artificial intelligence have created new opportunities for studying sports performance. With advancements in computer vision and artificial intelligence, it is now possible to use massive volumes of video data to get deeper insights into sports dynamics, especially in precision-based video sports like table tennis. To develop skills, a thorough examination of player movements is required. With the development of vision-based human posture recognition, computers can function like humans and derive intelligent judgments from outside data. This paper presents a novel method that uses graph convolutional neural networks (GCNNs) to detect and identify improper postures and movements in table tennis players. In addition to conventional methods, the proposed method dissects the human skeleton into finely detailed head, trunk, and leg features. Deep-level features that offer a more comprehensive understanding of athlete movements are extracted after feeding these features into the network. The softmax classifier combines these features to produce the final recognition result. The effectiveness of this approach has been evaluated through extensive experimentation. The GCN model performs remarkably well, with accuracy rates of 86.4% on the NTU-RGB + D dataset and 79.1% on the COCO dataset. This accomplishment is significant because the model consistently yields accurate detection results, even in complex and occlusion-filled scenes. In comparison tests, the proposed model performs better than GraphSAGE, GAT, ChebNet, GIN, and GC-LSTM in identifying relevant body part movements in table tennis players while ignoring irrelevant ones. According to proposed experiments, this enhances the recognition of improper postures in most table tennis actions.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17
Fig. 18
Fig. 19
Fig. 20
Fig. 21
Fig. 22
Fig. 23
Fig. 24
Fig. 25
Fig. 26
Fig. 27
Fig. 28
Fig. 29
Fig. 30
Fig. 31
Fig. 32

Similar content being viewed by others

Data availability

Contacting the corresponding author will provide access to the data supporting the research’s findings.

References

  • Ali M, Yin B, Bilal H et al (2023) Advanced efficient strategy for detection of dark objects based on spiking network with multi-box detection. Multimed Tools Appl. https://doi.org/10.1007/s11042-023-16852-2

    Article  Google Scholar 

  • Aslam MS, Chen Z (2019) Observer-based dissipative output feedback control for network T-S fuzzy systems under time delays with mismatch premise. Nonlinear Dyn 95:2923–2941

    Article  Google Scholar 

  • Aslam MS, Dai X, Hou J, Li Q, Ullah R, Ni Z, Liu Y (2020) Reliable control design for composite-driven scheme based on delay networked T-S fuzzy system. Int J Robust Nonlinear Control 30(4):1622–1642

    Article  MathSciNet  Google Scholar 

  • Aslam MS, Shamrooz M, Li Q, Hou J (2021) Fault detection for asynchronous T-S fuzzy networked Markov jump systems with new event-triggered scheme. IET Control Theory Appl 15(11):1461–1473

    Article  MathSciNet  Google Scholar 

  • Aslam MS, Qaisar I, Majid A, Shamrooz S (2023) Adaptive event-triggered robust H∞ control for Takagi–Sugeno fuzzy networked Markov jump systems with time-varying delay. Asian J Control 25(1):213–228

    Article  MathSciNet  Google Scholar 

  • Bao N, Zhang T, Huang R, Biswal S, Su J, Wang Y (2023) A deep transfer learning network for structural condition identification with limited real-world training data. Struct Control Health Monit 2023:1–18. https://doi.org/10.48550/arXiv.2307.15249

    Article  Google Scholar 

  • Behrens R, Foutz NZ, Franklin M, Funk J, Gutierrez-Navratil F, Hofmann J, Leibfried U (2021) Leveraging analytics to produce compelling and profitable film content. J Cult Econ 45:171–211

    Article  Google Scholar 

  • Chen YY, Lin YH, Hu YC, Hsia CH, Lian YA, Jhong SY (2022) Distributed real-time object detection based on edge-cloud collaboration for smart video surveillance applications. IEEE Access 10:93745–93759

    Article  Google Scholar 

  • Cong P, Xiao Y, Wan X, Deng M, Li J, Zhang X (2023) DACR-AMTP: adaptive multi-modal vehicle trajectory prediction for dynamic drivable areas based on collision risk. IEEE Trans Intell Veh

  • Cui Y, Shao C, Luo L, Wang L, Gao S, Chen L (2023) Center weighted convolution and GraphSAGE cooperative network for hyperspectral image classification. IEEE Trans Geosci Remote Sens 61

  • Dou H, Liu Y, Chen S et al (2023) A hybrid CEEMD-GMM scheme for enhancing the detection of traffic flow on highways. Soft Comput 27:16373–16388. https://doi.org/10.1007/s00500-023-09164-y

    Article  Google Scholar 

  • Fu C, Yuan H, Xu H, Zhang H, Shen L (2023) TMSO-Net: texture adaptive multi-scale observation for light field image depth estimation. J vis Commun Image Represent 90:103731

    Article  Google Scholar 

  • Hu Z, Ren L, Wei G, Qian Z, Liang W, Chen W, Lu X, Ren L, Wang K (2022) Energy flow and functional behavior of individual muscles at different speeds during human walking. IEEE Trans Neural Syst Rehabil Eng 31:294–303

    Article  Google Scholar 

  • Khan S, Khan M, Iqbal N, Li M, Khan DM (2020) Spark-based parallel deep neural network model for classification of large scale RNAs into piRNAs and non-piRNAs. IEEE Access 8:136978–136991

    Article  Google Scholar 

  • Lin Z, Wang H, Li S (2022) Pavement anomaly detection based on transformer and self-supervised learning. Autom Constr 143:104544

    Article  Google Scholar 

  • Liu H, Tan KH, Kumar A, Singh SK, Chung L (2022) Value co-creation in sports live streaming platforms: a microfoundations perspective. IEEE Trans Eng Manag 1–12. https://doi.org/10.1109/TEM.2022.3204451

    Article  Google Scholar 

  • Liu H, Xu Y, Chen F (2023a) Sketch2Photo: synthesizing photo-realistic images from sketches via global contexts. Eng Appl Artif Intell 117:105608

    Article  Google Scholar 

  • Liu Y, Li G, Lin L (2023b) Cross-modal causal relational reasoning for event-level visual question answering. IEEE Trans Pattern Anal Mach Intell 45:11624–11641. https://doi.org/10.48550/arXiv.2207.12647

    Article  Google Scholar 

  • Liu Z, Wen C, Su Z, Liu S, Sun J, Kong W, Yang Z (2023c) Emotion-semantic-aware dual contrastive learning for epistemic emotion identification of learner-generated reviews in MOOCs. IEEE Trans Neural Netw Learn Syst 1–14. https://doi.org/10.1109/TNNLS.2023.3294636

  • Lu S, Ban Y, Zhang X, Yang B, Liu S, Yin L, Zheng W (2022) Adaptive control of time delay teleoperation system with uncertain dynamics. Front Neurorobot 16:928863

    Article  Google Scholar 

  • Lu S, Ding Y, Liu M, Yin Z, Yin L, Zheng W (2023) Multiscale feature extraction and fusion of image and text in VQA. Int J Comput Intell Syst 16(1):54

    Article  Google Scholar 

  • Mi C, Huang S, Zhang Y, Zhang Z, Postolache O (2022) Design and implementation of 3-D measurement method for container handling target. J Mar Sci Eng 10(12):1961

    Article  Google Scholar 

  • Mi C, Liu Y, Zhang Y, Wang J, Feng Y, Zhang Z (2023) A vision-based displacement measurement system for foundation pit. IEEE Trans Instrum Meas

  • Miao Y, Wang X, Wang S, Li R (2022) Adaptive switching control based on dynamic zero moment point for versatile hip exoskeleton under hybrid locomotion. IEEE Trans Ind Electron 70(11):11443–11452. https://doi.org/10.1109/TIE.2022.3229343

    Article  Google Scholar 

  • Rani GJ, Hashmi MF, Gupta A (2023) Surface electromyography and artificial intelligence for human activity recognition—a systematic review on methods, emerging trends applications, challenges, and future implementation. IEEE Access 11:105140–105169. https://doi.org/10.1109/ACCESS.2023.3316509

    Article  Google Scholar 

  • She Q, Hu R, Xu J, Liu M, Xu K, Huang H (2022) Learning high-DOF reaching-and-grasping via dynamic representation of gripper-object interaction. ACM Trans Graph 41(4):1–14

    Article  Google Scholar 

  • Sun Z, Ke Q, Rahmani H, Bennamoun M, Wang G, Liu J (2022) Human action recognition from various data modalities: a review. IEEE Trans Pattern Anal Mach Intell

  • Tan X, Lin J, Xu K, Chen P, Ma L, Lau RW (2022) Mirror detection with the visual chirality cue. IEEE Trans Pattern Anal Mach Intell 45(3):3492–3504

    Google Scholar 

  • Ullah R, Dai X, Sheng A (2020) Event-triggered scheme for fault detection and isolation of non-linear system with time-varying delay. IET Control Theory Appl 14(16):2429–2438

    Article  MathSciNet  Google Scholar 

  • Ullah FUM, Muhammad K, Haq IU, Khan N, Heidari AA, Baik SW, de Albuquerque VHC (2021) AI-assisted edge vision for violence detection in IoT-based industrial surveillance networks. IEEE Trans Ind Inf 18(8):5359–5370

    Article  Google Scholar 

  • Wang Y, Xu N, Liu AA, Li W, Zhang Y (2021) High-order interaction learning for image captioning. IEEE Trans Circuits Syst Video Technol 32(7):4417–4430

    Article  Google Scholar 

  • Wang J, Ma J, Hu K, Zhou Z, Zhang H, Xie X, Wu Y (2022) Tac-trainer: a visual analytics system for IoT-based racket sports training. IEEE Trans Visual Comput Graphics 29(1):951–961

    Google Scholar 

  • Wang Y, Su Y, Li W, Xiao J, Li X, Liu AA (2023) Dual-path rare content enhancement network for image and text matching. IEEE Trans Circuits Syst Video Technol 33:6144–6158

    Article  Google Scholar 

  • Wu F, Wang Q, Bian J, Ding N, Lu F, Cheng J, Dou D, Xiong H (2022) A survey on video action recognition in sports: datasets, methods and applications. IEEE Trans Multimed 25:7943–7966. https://doi.org/10.1109/TMM.2022.3232034

    Article  Google Scholar 

  • Wu Q, Li X, Wang K et al (2023) Regional feature fusion for on-road detection of objects using camera and 3D-LiDAR in high-speed autonomous vehicles. Soft Comput 27:18195–18213. https://doi.org/10.1007/s00500-023-09278-3

    Article  Google Scholar 

  • Xiao Y, Feng K, Li Z, Gu F, Jiang Z (2022) Gas turbine blade passing frequency reconstruction and its application for blade fracturing fault diagnosis. In International conference on the Efficiency and Performance Engineering Network. Springer Nature Switzerland, Cham, pp 1006–1017

  • Xu J, Park SH, Zhang X, Hu J (2021) The improvement of road driving safety guided by visual inattentional blindness. IEEE Trans Intell Transp Syst 23(6):4972–4981

    Article  Google Scholar 

  • Xu J, Zhang X, Park SH, Guo K (2022) The alleviation of perceptual blindness during driving in urban areas guided by saccades recommendation. IEEE Trans Intell Transp Syst 23(9):16386–16396

    Article  Google Scholar 

  • Yang S, Li Q, Li W, Li X, Liu AA (2022) Dual-level representation enhancement on characteristic and context for image-text retrieval. IEEE Trans Circuits Syst Video Technol 32(11):8037–8050

    Article  Google Scholar 

  • Zhang J, Zhu C, Zheng L, Xu K (2021a) ROSEFusion: random optimization for online dense reconstruction under fast camera motion. ACM Trans Graph 40(4):1–17

    Google Scholar 

  • Zhang H, Luo G, Li J, Wang FY (2021b) C2FDA: coarse-to-fine domain adaptation for traffic object detection. IEEE Trans Intell Transp Syst 23(8):12633–12647

    Article  Google Scholar 

  • Zhang J, Tang Y, Wang H, Xu K (2022) ASRO-DIO: Active subspace random optimization based depth inertial odometry. IEEE Trans Rob 39(2):1496–1508

    Article  Google Scholar 

  • Zhang S, Li C, Jia Z, Liu L, Zhang Z, Wang L (2023) Diag-IoU loss for object detection. IEEE Trans Circuits Syst Video Technol 33:7671–7683

    Article  Google Scholar 

  • Zheng W, Yin L (2022) Characterization inference based on joint-optimization of multi-layer semantics and deep fusion matching network. PeerJ Comput Sci 8:e908

    Article  Google Scholar 

  • Zheng Y, Lv X, Qian L, Liu X (2022) An optimal Bp neural network track prediction method based on a GA–ACO Hybrid algorithm. J Mar Sci Eng 10(10):1399

    Article  Google Scholar 

  • Zhou X, Zhang L (2022) SA-FPN: an effective feature pyramid network for crowded human detection. Appl Intell 52(11):12556–12568

    Article  Google Scholar 

Download references

Funding

No funding was provided for the completion of this study.

Author information

Authors and Affiliations

  1. Physical Education Institute, Liaocheng University, Liaocheng, 252000, Shandong, China

    Weihao Ren

Authors
  1. Weihao Ren
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Weihao Ren.

Ethics declarations

Conflict of interest

The author asserts the absence of any competing interests.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ren, W. A novel approach for automatic detection and identification of inappropriate postures and movements of table tennis players. Soft Comput 28, 2245–2269 (2024). https://doi.org/10.1007/s00500-023-09587-7

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00500-023-09587-7

Keywords

Search

Navigation