Rajakumar, VigneshVigneshRajakumarRethinam, PragathiPragathiRethinamManoharan, SaravananSaravananManoharanKirupakaran, Anish MonsleyAnish MonsleyKirupakaranSadananda Hegde, RaviRaviSadananda HegdeSrinivasan, BabjiBabjiSrinivasan2025-08-312025-08-312024-01-01[9798350351453]10.1109/STAR62027.2024.106359682-s2.0-85203108777https://d8.irins.org/handle/IITG2025/29160Velocity-based training (VBT) is gaining popularity among strength and conditioning coaches over traditional methods due to its ability to quantify training intensity using movement velocity (m/s) as a standard, which is useful for prescribing other training variables. Existing VBT systems vary in functionalities, setups, accuracy, and costs. This research aims to develop and validate a markerless computer vision algorithm that uses Pose Estimation Models and RGB-D images to accurately estimate movement velocity during weight training irrespective of image orientations. Initial results show that the developed algorithm has a Mean Absolute Percentage Error (MAPE) of 4.82% in estimating movement velocity non-intrusively, compared to standard systems. This suggests that the developed algorithm can be used to build complete VBT systems for athlete load management with real-Time feedback and effective progress tracking in daily and long-Term periodization, aiding in reducing training stress, predicting fatigue, and injuries of the athletes.false3D Markerless Detection | Computer Vision | Fatigue detection | Pose Estimation | Velocity-based trainingConference Paper228-23320240cpConference Proceeding0