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Research Articles

Efficient key frame extraction and hybrid wavelet convolutional manta ray foraging for sports video classification

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Pages 691-714 | Received 12 Dec 2022, Accepted 11 Mar 2023, Published online: 27 Mar 2023

References

  • Achanta SDM, Karthikeyan T, Vinothkanna R. A novel hidden Markov model-basedadaptive dynamic time warping (HMDTW) gait analysis for identifying physically challenged persons. Soft Comput. 2019;23:8359–8366.
  • Jian M, Zhang S, Wu L, et al. Deep key frame extraction for sport training. Neurocomputing. 2019;328:147–156.
  • Rachmadi FR, Uchimura K, Koutaki G. Video classification using compacted dataset based on selected keyframe. In 2016 IEEE Region 10 Conference (TENCON), IEEE, 2016; 873-878.
  • Minhas RA, Javed A, Irtaza A, et al. Shot classification of field sports videos using AlexNet Convolutional Neural Network. Appl Sci. 2019;9(3):483.
  • Zhang J, Mei K, Zheng Y, et al. Exploiting mid-level semantics for large-scale complex video classification. IEEE Trans Multimed. 2019;21(10):2518–2530.
  • Xie D, Deng C, Wang H, et al. Semantic adversarial network with multi-scale pyramid attention for video classification. Proc AAAI Conf Artif Intell. 2019;33:9030–9037.
  • Ullah H, Khan SD, Ullah M, et al. Two stream model for crowd video classification. In 2019 8th European Workshop on Visual Information Processing (EUVIP), IEEE 2019; 93-98.
  • Xing J, Li X. Feature extraction algorithm of audio and video based on clustering in sports video analysis. J Vis Commun Image Represent. 2019: 102694.
  • Russo AM, Kurnianggoro L, Jo K-H. Classification of sports videos with combination of deep learning models and transfer learning. In 2019 international conference on electrical, computer and communication engineering (ECCE), IEEE, 2019; 1-5.
  • Gao J, Zhang T, Xu C. Learning to model relationships for zero-shot video classification. IEEE Trans Pattern Anal Mach Intell. 2020;43(10):3476–3491.
  • Zhi-Chao C, Zhang L. Key pose recognition toward sports scene using deeply-learned model. J Vis Commun Image Represent. 2019;63:102571.
  • Wang C, Liu H. Comprehensive Soccer Video Understanding: towards Human-comparable Video Understanding System in Constrained Environment, 2019. arXiv preprint arXiv:1912.04465.
  • Cao K, Ji J, Cao Z, et al. Few-shot video classification via temporal alignment. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020; 10618-10627.
  • Wei S, Hagras H. A hybrid fuzzy football scenes classification system for Big video data. In: Multimodal analytics for next-generation Big data technologies and applications. Cham: Springer; 2019. p. 299–318.
  • Diba A, Fayyaz M, Sharma V, et al. Temporal 3d convnets: new architecture and transfer learning for video classification, 2017.arXiv preprint arXiv:1711.08200.
  • Abu-El-Haija S, Kothari N, Lee J, et al. Youtube-8m: a large-scale video classification benchmark, 2016. arXiv preprint arXiv:1609.08675.
  • Walia A, Badran B. Sports Video Classification using Objects as Attributes, 2018.
  • Miech A, Laptev I, Sivic J. Learnable pooling with context gating for video classification, 2017. arXiv preprint arXiv:1706.06905.
  • Fernando B, Gould S. Learning end-to-end video classification with rank-pooling. In International Conference on Machine Learning, 2016; 1187-1196.
  • Girdhar R, Ramanan D, Gupta A, et al. Actionvlad: learning spatio-temporal aggregation for action classification. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2017; 971-980.
  • Wu Z, Jiang Y-G, Wang X, et al. Multi-stream multi-class fusion of deep networks for video classification. In Proceedings of the 24th ACM International Conference on Multimedia, 2016; 791-800.
  • Joshi S, Karhadkar A, Thatte N, et al. A Novice Approach of Hybrid Transfer Learning for Video Classification.
  • Shen H, Han S, Philipose M, et al. Fast video classification via adaptive cascading of deep models. Proc IEEE Conf Comput Vision Pattern Recognit. 2017: 3646–3654.
  • Rafiq M, Rafiq G, Agyeman R, et al. Scene classification for sports video summarization using transfer learning. Sensors. 2020;20(6):1702.
  • Javed A, Malik KM, Irtaza A, et al. A decision tree framework for shot classification of field sports videos. J Supercomput. 2020: 1–26.
  • Joshi K, Tripathi V, Bose C, et al. Robust sports image classification using InceptionV3 and neural networks. Procedia Comput Sci. 2020;167:2374–2381.
  • Kang S-K, Lee J-H. An E-sports video highlight generator using win-loss probability model. In Proceedings of the 35th Annual ACM Symposium on Applied Computing, 2020; 915-922.
  • Rangasamy K, As’ari MA, Rahmad NA, et al. Hockey activity recognition using pre-trained deep learning model. ICT Express. 2020;6(3):170–174.
  • Lv C, Li J, Tian J. Key frame extraction for sports training based on improved deep learning. Sci Program. 2021 Sep 2;2021.
  • Yuan Y, Lu Z, Yang Z, et al. Key frame extraction based on global motion statistics for team-sport videos. Multimedia Syst. 2022 Apr;28(2):387–401.
  • Sarma MS, Deb K, Dhar PK, et al. Traditional Bangladeshi sports video classification using deep learning method. Appl Sci. 2021 Feb 28;11(5):2149.
  • Afza F, Khan MA, Sharif M, et al. A framework of human action recognition using length control features fusion and weighted entropy-variances based feature selection. Image Vis Comput. 2021 Feb 1;106:104090.
  • Fu M, Zhong Q, Dong J. Sports action recognition based on deep learning and clustering extraction algorithm. Comput Intell Neurosci. 2022 Mar 19;2022.
  • Meng XH, Shi HY, Shang WH. Analysis of basketball technical movements based on human-computer interaction with deep learning. Comput Intell Neurosci. 2022 Apr 14;2022.
  • Guo J, Xu N, Li LJ, et al. Attention based CLDNNs for short-duration acoustic scene classification. In Interspeech 2017; 469-473.
  • Khater S, Hadhoud M, Fayek MB. A novel human activity recognition architecture: using residual inception ConvLSTM layer. J Eng Appl Sci . 2022 Dec;69(1):1–6.
  • Podgorelec V, Pečnik Š, Vrbančič G. Classification of similar sports images using convolutional neural network with hyper-parameter optimization. App Sci. 2020 Nov 27;10(23):8494.
  • Guo X. Intelligent sports video classification based on deep neural network (DNN) algorithm and transfer learning. Comput Intell Neurosci. 2021 Nov 24;2021.
  • Abd Elaziz M, Nabil N, Moghdani R, et al. Multilevel thresholding image segmentation based on improved volleyball premier league algorithm using whale optimization algorithm. Multimed Tools Appl. 2021 Mar;80:12435–68.
  • Wu K. Deconstruction and realization of sports entity simulation based on fish swarm algorithm. Comput Intell Neurosci. 2022 Jul 22;2022.
  • Zhu H, Liu L. Basketball object extraction method based on image segmentation algorithm. Secu Commun Netw. 2022 Aug 29;2022.
  • Chen BQ, Cui JG, Xu Q, et al. Coupling denoising algorithm based on discrete wavelet transform and modified median filter for medical image. J Cent South Univ. 2019 Jan;26(1):120–31.
  • Joel T, Sivakumar R. Non-subsampled contourlet transform with cross-guided bilateral filter for despeckling of medical ultrasound images. Int J Imaging Syst Technol. 2020;31(2):763–777.
  • Faramarzi A, Heidarinejad M, Stephens B, et al. Equilibrium optimizer: a novel optimization algorithm. Knowl Based Syst. 2020;191:105190.
  • Anthwal S, Ganotra D. Optical flow estimation in synthetic image sequences using farneback algorithm. In: Advances in signal processing and communication. Singapore: Springer; 2019. p. 363–371.
  • Zhao W, Zhang Z, Wang L. Manta ray foraging optimization: an effective bio-inspired optimizer for engineering applications. Eng Appl Artif Intell. 2020;87:103300.
  • Safdarnejad MS, Liu X, Udpa L, et al. Sports videos in the wild (SVW): a video dataset for sports analysis. In 2015 11th IEEE international conference and workshops on automatic face and gesture recognition (FG), IEEE, 2015; 1: 1-7.
  • SVW. [dataset] available at http://cvlab.cse.msu.edu/project-svw.html.
  • Li X, Chuah MC. Rehar: robust and efficient human activity recognition. In 2018 IEEE Winter Conference on Applications of Computer Vision (WACV) 2018 Mar 12; 362-371.
  • Zha D, Bhat ZP, Chen YW, et al. Autovideo: an automated video action recognition system. arXiv preprint arXiv:2108.04212. 2021 Aug 9.
  • Shrichandran GV, Sathiyamoorthy S, Malarchelvi PD. A hybrid glow-worm swarm optimization with bat algorithm based retinal blood vessel segmentation. J Comput Theor Nanosci. 2017 Jun 1;14(6):2601–11.
  • Gotoh JY, Kim MJ, Lim AE. Robust empirical optimization is almost the same as mean–variance optimization. Oper Res Lett. 2018 Jul 1;46(4):448–52.
  • Abualigah L, Diabat A, Mirjalili S, et al. The arithmetic optimization algorithm. Comput Methods Appl Mech Eng. 2021 Apr 1;376:113609.
  • Heidari AA, Mirjalili S, Faris H, et al. Harris hawks optimization: algorithm and applications. Future Gener Comput Syst. 2019 Aug 1;97:849–72.
  • Ahmadianfar I, Bozorg-Haddad O, Chu X. Gradient-based optimizer: a new metaheuristic optimization algorithm. Inf Sci (Ny). 2020 Nov 1;540:131–59.
  • Rachmadi FR, Uchimura K, Koutaki G. Combined convolutional neural network for event recognition. In Proceedings of the Korea-Japan Joint Workshop on Frontiers of Computer Vision, 2016; 85-90.
  • Malekmohamadi H, Pattanjak N, Bom R. Human activity identification in smart daily environments. In: Smart assisted living. Cham: Springer; 2020. p. 91–118.
  • Liu Y. Classification of videos based on deep learning. J Sens. 2022 Sep 6;2022.

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