References
- Addison, A. P., Addison, P. S., Smit, P., Jacquel, D., & Borg, U. R. (2021). Noncontact Respiratory Monitoring Using Depth Sensing Cameras: A Review of Current Literature. Sensors, 21(4), 1135.
https://doi.org/10.3390/s21041135 - Alexiadis, D. S., Zarpalas, D., & Daras, P. (2013). Real-Time, Full 3-D Reconstruction of Moving Foreground Objects From Multiple Consumer Depth Cameras. IEEE Transactions on Multimedia, 15(2), 339–358.
https://doi.org/10.1109/TMM.2012.2229264 - Al-Nuaimi, M., Wibowo, S., Qu, H., Aitken, J., & Veres, S. (2021). Hybrid Verification Technique for Decision-Making of Self-Driving Vehicles. Journal of Sensor and Actuator Networks, 10(3), 42.
https://doi.org/10.3390/jsan10030042 - Amir-Behghadami, M., & Janati, A. (2020). Population, Intervention, Comparison, Outcomes and Study (PICOS) design as a framework to formulate eligibility criteria in systematic reviews. Emergency Medicine Journal, 37(6), 387–387.
https://doi.org/10.1136/emermed-2020-209567 - An, W. C., Ngali, M. Z., Kaharuddin, Z., & Khairu Razak, S. B. (2017). Performance of Dual Depth Camera Motion Capture System for Athletes’ Biomechanics Analysis. MATEC Web of Conferences, 135, 00059.
https://doi.org/10.1051/matecconf/201713500059 - Andújar, D., Ribeiro, A., Fernández-Quintanilla, C., & Dorado, J. (2016). Using depth cameras to extract structural parameters to assess the growth state and yield of cauliflower crops. Computers and Electronics in Agriculture, 122, 67–73.
https://doi.org/10.1016/j.compag.2016.01.018 - Babayan, J., Hommaid, M., Hage-Diab, A., & Abdulnabi, S. (2015). Low-cost dry swimming machine using Kinect biomotion capture. Proceedings of the 2015 International Conference on Advances in Biomedical Engineering (ICABME), 282–284.
https://doi.org/10.1109/ICABME.2015.7323307 - Belić, M., Bobić, V., Badža, M., Šolaja, N., Đurić‐Jovičić, M., & Kostić, V. S. (2019). Artificial intelligence for assisting diagnostics and assessment of Parkinson’s disease—A review. Clinical Neurology and Neurosurgery, 184, 105442.
https://doi.org/10.1016/j.clineuro.2019.105442 - Bernardina, G. R. D., Monnet, T., Pinto, H. T., de Barros, R. M. L., Cerveri, P., & Silvatti, A. P. (2019). Are Action Sport Cameras Accurate Enough for 3D Motion Analysis? A Comparison With a Commercial Motion Capture System. Journal of Applied Biomechanics, 35(1), 80–86.
https://doi.org/10.1123/jab.2017-0101 - Bilesan, A., Komizunai, S., Tsujita, T., & Konno, A. (2021). Improved 3D Human Motion Capture Using Kinect Skeleton and Depth Sensor. Journal of Robotics and Mechatronics, 33(6), 1408–1422.
https://doi.org/10.20965/jrm.2021.p1408 - Bittar, É., Desprez, P.-É., Grisonnet, B., Nocent, O., & Soilih, A. (2017). LeBonGeste: basketball training by entertaining. Procedia Computer Science, 112, 1281–1287.
https://doi.org/10.1016/j.procs.2017.08.084 - Bo, L., Ren, X., & Fox, D. (2011). Depth kernel descriptors for object recognition. 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 821–826.
https://doi.org/10.1109/IROS.2011.6095119 - Chang, Z., & Zhao, Y. (2022). Algorithm for Swimmers’ Starting Posture Correction Based on Kinect. Mathematical Problems in Engineering, 2022(1), 1–8.
https://doi.org/10.1155/2022/1101002 - Chatzitofis, A., Zarpalas, D., Kollias, S., & Daras, P. (2019). DeepMoCap: Deep Optical Motion Capture Using Multiple Depth Sensors and Retro-Reflectors. Sensors, 19(2), 282.
https://doi.org/10.3390/s19020282 - Choppin, S., & Wheat, J. (2013). The potential of the Microsoft Kinect in sports analysis and biomechanics. Sports Technology, 6(2), 78–85.
https://doi.org/10.1080/19346182.2013.819008 - Corazza, S., Mündermann, L., Gambaretto, E., Ferrigno, G., & Andriacchi, T. P. (2010). Markerless Motion Capture through Visual Hull, Articulated ICP and Subject Specific Model Generation. International Journal of Computer Vision, 87(1–2), 156–169.
https://doi.org/10.1007/s11263-009-0284-3 - Cunha, P., Barbosa, P., Ferreira, F., Fitas, C., Carvalho, V. H., & Soares, F. O. (2021). Real-time evaluation system for top Taekwondo athletes: Project overview. In A. Fred, H. Gamboa, & D. Elias (Eds.), Proceedings of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies (BIODEVICES 2021) (pp. 209–216). SCITEPRESS.
https://www.scitpress.org/Papers/2021/104142/104142.pdf - Cunha, P., Barbosa, P., Ferreira, F., Silva, T., Martins, N., Soares, F., & Carvalho, V. (2023). Cyber-Physical System for Evaluation of Taekwondo Athletes: An Initial Project Description. Machines, 11(2), 234.
https://doi.org/10.3390/machines11020234 - Dufner, A.-L., Schütz, L.-M., & Hill, Y. (2023). The introduction of the Video Assistant Referee supports the fairness of the game – An analysis of the home advantage in the German Bundesliga. Psychology of Sport and Exercise, 66, 102386.
https://doi.org/10.1016/j.psychsport.2023.102386 - Dutta, T. (2012). Evaluation of the KinectTM sensor for 3-D kinematic measurement in the workplace. Applied Ergonomics, 43(4), 645–649.
https://doi.org/10.1016/j.apergo.2011.09.011 - Emad, B., Atef, O., Shams, Y., El-Kerdany, A., Shorim, N., Nabil, A., & Atia, A. (2020). iKarate: Karate Kata Guidance System. Procedia Computer Science, 175, 149–156.
https://doi.org/10.1016/j.procs.2020.07.024 - Gai, J., Xiang, L., & Tang, L. (2021). Using a depth camera for crop row detection and mapping for under-canopy navigation of agricultural robotic vehicle. Computers and Electronics in Agriculture, 188, 106301.
https://doi.org/10.1016/j.compag.2021.106301 - Garcia, G. J., Gil, P., Llácer, D., & Torres, F. (2013). Guidance of Robot Arms using Depth Data from RGB-D Camera. Proceedings of the 10th International Conference on Informatics in Control, Automation and Robotics, 315–321.
- Helten, T., Muller, M., Seidel, H.-P., & Theobalt, C. (2013). Real-Time Body Tracking with One Depth Camera and Inertial Sensors. 2013 IEEE International Conference on Computer Vision, 1105–1112.
https://doi.org/10.1109/ICCV.2013.141 - Hwang, S., Ko, K., & Pan, S. B. (2021). Motion data acquisition method for motion analysis in golf. Concurrency and Computation: Practice and Experience, 33(2), e5215.
https://doi.org/10.1002/cpe.5215 - Iacono, M., & Sgorbissa, A. (2018). Path following and obstacle avoidance for an autonomous UAV using a depth camera. Robotics and Autonomous Systems, 106, 38–46.
https://doi.org/10.1016/j.robot.2018.04.005 - Jacobsson, M., Willén, J., & Swarén, M. (2023). A Drone-mounted Depth Camera-based Motion Capture System for Sports Performance Analysis. In International Conference on Human-Computer Interaction (pp. 489–503). Springer Nature Switzerland.
https://doi.org/10.1007/978-3-031-35894-4_36 - Kaharuddin, M. Z., Khairu Razak, S. B., Kushairi, M. I., Abd. Rahman, M. S., An, W. C., Ngali, Z., Siswanto, W. A., Salleh, S. M., & Yusup, E. M. (2017). Biomechanics Analysis of Combat Sport (Silat) By Using Motion Capture System. IOP Conference Series: Materials Science and Engineering, 165, 012028.
https://doi.org/10.1088/1757-899X/165/1/012028 - Kytö, M., Nuutinen, M., & Oittinen, P. (2011). Method for measuring stereo camera depth accuracy based on stereoscopic vision. In J. A. Beraldin et al. (Eds.), Three-Dimensional Imaging, Interaction, and Measurement (Vol. 7864, p. 78640I). SPIE.
https://doi.org/10.1117/12.872015 - Laaraibi, A. R. A. (2024). Development of an autonomous system based on piezoresistive sensors for quantitative sports movement [Doctoral dissertation, Université de Rennes]. HAL.
https://theses.hal.science/tel-04673560 - Langmann, B., Hartmann, K., & Loffeld, O. (2012). Depth camera technology comparison and performance evaluation. In Proceedings of the 1st International Conference on Pattern Recognition Applications and Methods (ICPRAM 2012) (pp. 438–444). SCITEPRESS.
https://www.scitpress.org/papers/2012/37783/37783.pdf - Link, D., & Lames, M. (2014). An introduction to sport informatics. In D. Link & M. Lames (Eds.), Computer science in sport (pp. 1–17). Routledge.
- Ma, Z., & Wu, E. (2014). Real-time and robust hand tracking with a single depth camera. The Visual Computer, 30(10), 1133–1144.
https://doi.org/10.1007/s00371-013-0894-1 - Macadam, P., Cronin, J., Neville, J., & Diewald, S. (2019). Quantification of the validity and reliability of sprint performance metrics computed using inertial sensors: A systematic review. Gait & Posture, 73, 26–38.
https://doi.org/10.1016/j.gaitpost.2019.07.123 - Malawski, F. (2021). Depth Versus Inertial Sensors in Real-Time Sports Analysis: A Case Study on Fencing. IEEE Sensors Journal, 21(4), 5133–5142.
https://doi.org/10.1109/JSEN.2020.3036436 - Monteiro, A., Santos, S., & Gonçalves, P. (2021). Precision Agriculture for Crop and Livestock Farming—Brief Review. Animals, 11(8), 2345.
https://doi.org/10.3390/ani11082345 - Nam, C. N. K., Kang, H. J., & Suh, Y. S. (2014). Golf Swing Motion Tracking Using Inertial Sensors and a Stereo Camera. IEEE Transactions on Instrumentation and Measurement, 63(4), 943–952.
https://doi.org/10.1109/TIM.2013.2283548 - Neupane, C., Koirala, A., Wang, Z., & Walsh, K. B. (2021). Evaluation of Depth Cameras for Use in Fruit Localization and Sizing: Finding a Successor to Kinect v2. Agronomy, 11(9), 1780.
https://doi.org/10.3390/agronomy11091780 - Omelina, L., Jansen, B., Bonnechère, B., Oravec, M., Jarmila, P., & Jan, S. V. S. (2016). Interaction Detection with Depth Sensing and Body Tracking Cameras in Physical Rehabilitation. Methods of Information in Medicine, 55(01), 70–78.
https://doi.org/10.3414/ME14-01-0120 - Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., Chou, R., Glanville, J., Grimshaw, J. M., Hróbjartsson, A., Lalu, M. M., Li, T., Loder, E. W., Mayo-Wilson, E., McDonald, S., … Moher, D. (2021). The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. Systematic Reviews, 10(1), 89.
https://doi.org/10.1186/s13643-021-01626-4 - Pandurevic, D., Sutor, A., & Hochradel, K. (2019). Methods for quantitative evaluation of force and technique in competitive sport climbing. Journal of Physics: Conference Series, 1379(1), 012014.
https://doi.org/10.1088/1742-6596/1379/1/012014 - Patton, D. A., Huber, C. M., Jain, D., Myers, R. K., McDonald, C. C., Margulies, S. S., Master, C. L., & Arbogast, K. B. (2020). Head Impact Sensor Studies In Sports: A Systematic Review Of Exposure Confirmation Methods. Annals of Biomedical Engineering, 48(11), 2497–2507.
https://doi.org/10.1007/s10439-020-02642-6 - Piche, E., Guilbot, M., Chorin, F., Guerin, O., Zory, R., & Gerus, P. (2022). Validity and repeatability of a new inertial measurement unit system for gait analysis on kinematic parameters: Comparison with an optoelectronic system. Measurement, 198, 111442.
https://doi.org/10.1016/j.measurement.2022.111442 - Pueo, B. (2016). High speed cameras for motion analysis in sports science. Journal of Human Sport and Exercise, 11(1), 53–73.
https://doi.org/10.14198/jhse.2016.111.05 - Pueo, B., & Jimenez-Olmedo, J. M. (2017). Application of motion capture technology for sport performance analysis (El uso de la tecnología de captura de movimiento para el análisis del rendimiento deportivo). Retos, 32, 241–247.
https://doi.org/10.47197/retos.v0i32.56072 - Ráthonyi, G., Bácsné Bába, É., Müller, A., & Ráthonyi-Ódor, K. (2018). How Digital Technologies Are Changing Sport? Applied Studies in Agribusiness and Commerce, 12(3–4), 89–96.
https://doi.org/10.19041/APSTRACT/2018/3-4/10 - Regazzoni, D., de Vecchi, G., & Rizzi, C. (2014). RGB cams vs RGB-D sensors: Low cost motion capture technologies performances and limitations. Journal of Manufacturing Systems, 33(4), 719–728.
https://doi.org/10.1016/j.jmsy.2014.07.011 - Reily, B., Zhang, H., & Hoff, W. (2017). Real-time gymnast detection and performance analysis with a portable 3D camera. Computer Vision and Image Understanding, 159, 154–163.
https://doi.org/10.1016/j.cviu.2016.11.006 - Retinger, M., Michalski, J., Kozierski, P., & Giernacki, W. (2023). Toward improving tracking precision in motion capture systems. 2023 International Conference on Unmanned Aircraft Systems (ICUAS), 919–925.
https://doi.org/10.1109/ICUAS57906.2023.10156538 - Rybnikár, F., Kačerová, I., Hořejší, P., & Šimon, M. (2022). Ergonomics Evaluation Using Motion Capture Technology—Literature Review. Applied Sciences, 13(1), 162.
https://doi.org/10.3390/app13010162 - Scataglini, S., Abts, E., Van Bocxlaer, C., Van den Bussche, M., Meletani, S., & Truijen, S. (2024). Accuracy, Validity, and Reliability of Markerless Camera-Based 3D Motion Capture Systems versus Marker-Based 3D Motion Capture Systems in Gait Analysis: A Systematic Review and Meta-Analysis. Sensors, 24(11), 3686.
https://doi.org/10.3390/s24113686 - Siddiqi, M. H., Almashfi, N., Ali, A., Alruwaili, M., Alhwaiti, Y., Alanazi, S., & Kamruzzaman, M. M. (2021). A Unified Approach for Patient Activity Recognition in Healthcare Using Depth Camera. IEEE Access, 9, 92300–92317.
https://doi.org/10.1109/ACCESS.2021.3092403 - Siddiqui, M. S., Syed, T. A., Nadeem, A., Nawaz, W., & Alkhodre, A. (2022). Virtual Tourism and Digital Heritage: An Analysis of VR/AR Technologies and Applications. International Journal of Advanced Computer Science and Applications, 13(7).
https://doi.org/10.14569/IJACSA.2022.0130739 - Southgate, D. F. L., Prinold, J. A. I., & Weinert-Aplin, R. A. (2016). Motion Analysis in Sport. In Sports Innovation, Technology and Research (pp. 3–30). WORLD SCIENTIFIC (EUROPE).
https://doi.org/10.1142/9781786340429_0001 - Spitz, J., Wagemans, J., Memmert, D., Williams, A. M., & Helsen, W. F. (2021). Video assistant referees (VAR): The impact of technology on decision making in association football referees. Journal of Sports Sciences, 39(2), 147–153.
https://doi.org/10.1080/02640414.2020.1809163 - Spörri, J., Schiefermüller, C., & Müller, E. (2016). Collecting Kinematic Data on a Ski Track with Optoelectronic Stereophotogrammetry: A Methodological Study Assessing the Feasibility of Bringing the Biomechanics Lab to the Field. PLOS ONE, 11(8), e0161757.
https://doi.org/10.1371/journal.pone.0161757 - Sri-Iesaranusorn, P., Garcia, F. C., Tiausas, F., Wattanakriengkrai, S., Ikeda, K., & Yoshimoto, J. (2021). Toward the Perfect Stroke: A Multimodal Approach for Table Tennis Stroke Evaluation. 2021 Thirteenth International Conference on Mobile Computing and Ubiquitous Network (ICMU), 1–5.
https://doi.org/10.23919/ICMU50196.2021.9638855 - Stancic, I., Grujic Supuk, T., & Panjkota, A. (2013). Design, development and evaluation of optical motion‐tracking system based on active white light markers. IET Science, Measurement & Technology, 7(4), 206–214.
https://doi.org/10.1049/iet-smt.2012.0157 - Syed, T. A., Siddiqui, M. S., Abdullah, H. B., Jan, S., Namoun, A., Alzahrani, A., Nadeem, A., & Alkhodre, A. B. (2022). In-Depth Review of Augmented Reality: Tracking Technologies, Development Tools, AR Displays, Collaborative AR, and Security Concerns. Sensors, 23(1), 146.
https://doi.org/10.3390/s23010146 - Terwee, C. B., Prinsen, C. A. C., Chiarotto, A., Westerman, M. J., Patrick, D. L., Alonso, J., Bouter, L. M., de Vet, H. C. W., & Mokkink, L. B. (2018). COSMIN methodology for evaluating the content validity of patient-reported outcome measures: a Delphi study. Quality of Life Research, 27(5), 1159–1170.
https://doi.org/10.1007/s11136-018-1829-0 - van der Kruk, E., & Reijne, M. M. (2018). Accuracy of human motion capture systems for sport applications; state-of-the-art review. European Journal of Sport Science, 18(6), 806–819.
https://doi.org/10.1080/17461391.2018.1463397 - Xu, Y., Tong, M., Ming, W.-K., Lin, Y., Mai, W., Huang, W., & Chen, Z. (2021). A Depth Camera–Based, Task-Specific Virtual Reality Rehabilitation Game for Patients With Stroke: Pilot Usability Study. JMIR Serious Games, 9(1), e20916.
https://doi.org/10.2196/20916 - Yahav, G., Iddan, G. J., & Mandelboum, D. (2007). 3D Imaging Camera for Gaming Application. 2007 Digest of Technical Papers International Conference on Consumer Electronics, 1–2.
https://doi.org/10.1109/ICCE.2007.341537 - Yoshimura, K., Yamauchi, Y., & Takahashi, H. (2023). Managing Variability of Logistics Robot System. Proceedings of the 27th ACM International Systems and Software Product Line Conference - Volume A, 234–241.
https://doi.org/10.1145/3579027.3608995