Novel automated detection of sports activities using shadow videos
Article
Barua, Prabal Datta, Tuncer, Turker, Dogan, Sengul, Ooi, Chui Ping and Acharya, Rajendra U.. 2024. "Novel automated detection of sports activities using shadow videos." Multimedia Tools and Applications. 83 (15), pp. 44933-44954. https://doi.org/10.1007/s11042-023-17407-1
| Article Title | Novel automated detection of sports activities using shadow videos |
|---|---|
| ERA Journal ID | 18083 |
| Article Category | Article |
| Authors | Barua, Prabal Datta, Tuncer, Turker, Dogan, Sengul, Ooi, Chui Ping and Acharya, Rajendra U. |
| Journal Title | Multimedia Tools and Applications |
| Journal Citation | 83 (15), pp. 44933-44954 |
| Number of Pages | 22 |
| Year | 2024 |
| Publisher | Springer |
| Place of Publication | United States |
| ISSN | 1380-7501 |
| 1573-7721 | |
| Digital Object Identifier (DOI) | https://doi.org/10.1007/s11042-023-17407-1 |
| Web Address (URL) | https://link.springer.com/article/10.1007/s11042-023-17407-1 |
| Abstract | The aim of this work is to investigate the use of shadow videos for daily sports activity detection and to contribute to the emerging field of shadow-based classification in machine learning. A novel deep feature engineering model is proposed, and a new shadow video dataset is collected to validate the proposed model. Furthermore, the use of shadow videos ensures privacy protection for individuals. To evaluate the proposed system, a dataset comprising five sports activities (i.e., squat, steady run, standing butterfly, overhead side bend, and knee lift) recorded from 33 participants is used. The proposed model works in the following way: (i) videos are divided into frames and aggregated into non-overlapping blocks of six frames to create images, (ii) deep features are extracted from three fully connected layers of the pre-trained AlexNet, resulting in 4096, 4096, and 1000 features from fc6, fc7, and fc8 layers, respectively. These three feature vectors are then merged to generate a final feature vector with a length of 9192 (= 4096 + 4096 + 1000). (iii) The Chi2 selector is employed to select the most distinctive 1000 features in the feature selection phase, and (iv) the support vector machine (SVM) with leave-one-subject-out (LOSO) validation is used to classify the five sports activities. The proposed deep features coupled with Chi2 based model achieved a classification accuracy of 88.49% using the SVM classifier with LOSO cross-validation (CV) on our collected dataset. |
| Keywords | Chi2 feature selection; Sports activities detection using shadow; Video processing; Transfer learning; LOSO validation |
| Contains Sensitive Content | Does not contain sensitive content |
| ANZSRC Field of Research 2020 | 400306. Computational physiology |
| Public Notes | Files associated with this item cannot be displayed due to copyright restrictions. |
| Byline Affiliations | School of Business |
| Firat University, Turkey | |
| Singapore University of Social Sciences (SUSS), Singapore | |
| School of Mathematics, Physics and Computing |
Permalink -
https://research.usq.edu.au/item/z2553/novel-automated-detection-of-sports-activities-using-shadow-videos
71
total views1
total downloads1
views this month0
downloads this month
Export as
Related outputs
Automated hip dysplasia detection using novel FlexiLBPHOG model with ultrasound images
Key, Sefa, Kurum, Huseyin, Esmez, Omer, Hafeez-Baig, Abdul, Hajiyeva, Rena, Dogan, Sengul and Tuncer, Turker. 2025. "Automated hip dysplasia detection using novel FlexiLBPHOG model with ultrasound images." Ain Shams Engineering Journal. 16 (1). https://doi.org/10.1016/j.asej.2024.103235Artificial Intelligence-Based Suicide Prevention and Prediction: A Systematic Review (2019-2023)
Atmakuru, Anirudh, Shahini, Alen, Chakraborty, Subrata, Seoni, Silvia, Salvi, Massimo, Hafeez-Baig, Abdul, Rashid, Sadaf, Tan, Ru San, Barua, Prabal Datta, Molinari, Filippo and Acharya, U Rajendra. 2025. "Artificial Intelligence-Based Suicide Prevention and Prediction: A Systematic Review (2019-2023)." Information Fusion. 114. https://doi.org/10.1016/j.inffus.2024.102673Explainable deeply-fused nets electricity demand prediction model: Factoring climate predictors for accuracy and deeper insights with probabilistic confidence interval and point-based forecasts
Ghimire, Sujan, AL-Musaylh, Mohanad S., Nguyen-Huy, Thong, Deo, Ravinesh C., Acharya, Rajendra, Casillas-Perez, David, Yaseen, Zaher Mundher and Salcedo-sanz, Sancho. 2025. "Explainable deeply-fused nets electricity demand prediction model: Factoring climate predictors for accuracy and deeper insights with probabilistic confidence interval and point-based forecasts." Applied Energy. 378 (Part A). https://doi.org/10.1016/j.apenergy.2024.124763AttentionPoolMobileNeXt: An automated construction damage detection model based on a new convolutional neural network and deep feature engineering models
Aydin, Mehmet, Barua, Prabal Datta, Chadalavada, Sreenivasulu, Dogan, Sengul, Tuncer, Turker, Chakraborty, Subrata and Acharya, Rajendra U.. 2025. "AttentionPoolMobileNeXt: An automated construction damage detection model based on a new convolutional neural network and deep feature engineering models." Multimedia Tools and Applications. 84 (4), pp. 1821-1843. https://doi.org/10.1007/s11042-024-19163-2Directed Lobish-based explainable feature engineering model with TTPat and CWINCA for EEG artifact classification
Tuncer, Turker, Dogan, Sengul, Baygin, Mehmet, Tasci, Irem, Mungen, Bulent, Tasci, Burak, Barua, Prabal Datta and Acharya, U.R.. 2024. "Directed Lobish-based explainable feature engineering model with TTPat and CWINCA for EEG artifact classification." Knowledge-Based Systems. 305. https://doi.org/10.1016/j.knosys.2024.112555Retinal Health Screening Using Artificial Intelligence with Digital Fundus Images: A Review of the Last Decade (2012-2023)
Islam, Saad, Deo, Ravinesh C., Barua, Prabal Datta, Soar, Jeffrey, Yu, Ping and Acharya, U. Rajendra. 2024. "Retinal Health Screening Using Artificial Intelligence with Digital Fundus Images: A Review of the Last Decade (2012-2023)." IEEE Access. 12, pp. 176630-176685. https://doi.org/10.1109/ACCESS.2024.3477420Automated EEG-based language detection using directed quantum pattern technique
Dogan, Sengul, Tuncer, Turker, Barua, Prabal Datta and Acharya, U.R.. 2024. "Automated EEG-based language detection using directed quantum pattern technique." Applied Soft Computing. 167 (Part A). https://doi.org/10.1016/j.asoc.2024.112301A Novel Hybrid Model for Automatic Non-Small Cell Lung Cancer Classification Using Histopathological Images
Katar, Oguzhan, Yildirim, Ozal, Tan, Ru-San and Acharya, U Rajendra. 2024. "A Novel Hybrid Model for Automatic Non-Small Cell Lung Cancer Classification Using Histopathological Images." Diagnostics. 14 (22). https://doi.org/10.3390/diagnostics14222497Synthetic Data Generation via Generative Adversarial Networks in Healthcare: A Systematic Review of Image- and Signal-Based Studies
Akpinar, Muhammed Halil, Sengur, Abdulkadir, Salvi, Massimo, Seoni, Silvia, Faust, Oliver, Mir, Hasan, Molinari,Filippo and Acharya, U. Rajendra. 2024. "Synthetic Data Generation via Generative Adversarial Networks in Healthcare: A Systematic Review of Image- and Signal-Based Studies." IEEE Open Journal of Engineering in Medicine and Biology. 6, pp. 183-192. https://doi.org/10.1109/OJEMB.2024.3508472RECOMED: A comprehensive pharmaceutical recommendation system
Zomorodi, Mariam, Ghodsollahee, Ismail, Martin, Jennifer H, Talley, Nicholas J, Salari, Vahid, Pławiak, Paweł, Rahimi, Kazem and Acharya, U.R.. 2024. "RECOMED: A comprehensive pharmaceutical recommendation system." Artificial Intelligence in Medicine. 157. https://doi.org/10.1016/j.artmed.2024.102981Artificial intelligence in assessing cardiovascular diseases and risk factors via retinal fundus images: A review of the last decade
Abdollahi, Mirsaeed, Jafarizadeh, Ali, Ghafouri-Asbagh, Amirhosein, Sobhi, Navid, Pourmoghtader, Keysan, Pedrammehr, Siamak, Asadi, Houshyar, Tan, Ru-San, Alizadehsani, Roohallah and Acharya, U. Rajendra. 2024. "Artificial intelligence in assessing cardiovascular diseases and risk factors via retinal fundus images: A review of the last decade." WIREs Data Mining and Knowledge Discovery. 14 (6). https://doi.org/10.1002/widm.1560Early prediction of sudden cardiac death using multimodal fusion of ECG Features extracted from Hilbert–Huang and wavelet transforms with explainable vision transformer and CNN models
Telangore, Hardik, Azad, Victor, Sharma, Manish, Bhurane, Ankit, Tan, Ru San and Acharya, U. Rajendra. 2024. "Early prediction of sudden cardiac death using multimodal fusion of ECG Features extracted from Hilbert–Huang and wavelet transforms with explainable vision transformer and CNN models." Computer Methods and Programs in Biomedicine. 257. https://doi.org/10.1016/j.cmpb.2024.108455A Pragmatic Approach to Fetal Monitoring via Cardiotocography Using Feature Elimination and Hyperparameter Optimization
Hardalac, Firat, Akmal, Haad, Ayturan, Kubilay, Acharya, U. Rajendra and Tan, Ru-San. 2024. "A Pragmatic Approach to Fetal Monitoring via Cardiotocography Using Feature Elimination and Hyperparameter Optimization." Interdisciplinary Sciences: Computational Life Sciences. 16 (4), pp. 882-906. https://doi.org/10.1007/s12539-024-00647-6Automated System for the Detection of Heart Anomalies Using Phonocardiograms: A Systematic Review
Gudigar, Anjan, Raghavendra, U., Maithri, M., Samanth, Jyothi, Inamdar, Mahesh Anil, Vidhya, V., Vicnesh, Jahmunah, Prabhu, Mukund A., Tan, Ru-San, Yeong, Chai Hong, Molinari, Filippo and Acharya, U. R.. 2024. "Automated System for the Detection of Heart Anomalies Using Phonocardiograms: A Systematic Review." IEEE Access. 12, pp. 138399-138428. https://doi.org/10.1109/ACCESS.2024.3465511