A novel method, to our knowledge, for monitoring weightlifting exercises based on infrared imaging is proposed in this work. For the infrared workout weightlifting recorded scenes, radiometry and artificial intelligence were employed for in-scene temperature and biomechanical athletes' body parts position mapping. Our method was effective in monitoring muscle exertion during high-performance athletic exercises, as evidenced by the results obtained from real athletic datasets. The method generates a color-labeled sequence of thermal images and reports on body part positions, which can be used by judges and trainers to guide athletes toward safer and more efficient practices. (c) 2024 Optica Publishing Group. All rights, including for text and data mining (TDM), Artificial Intelligence (AI) training, and similar technologies, are reserved. C1 [Viafora, Laura A.; Torres, Sergio N.; Soto, Ricardo F.] Univ Concepcion, Dept Ingn Elect, Casilla 160-C, Concepcion, Chile. [Machuca, Guillermo] Univ Atacama, Dept Ingn Informat & Ciencias Comp, Copiapo, Chile. [Gutierrez, Pablo] Univ Tecn Federico Santa Maria, Fac Fis, Santiago, Chile. [Jara, Anselmo; Coelho, Pablo] Univ San Sebastian, Fac Ingn Arquitectura & Diseno, Lientur 1457, Concepcion 4080871, Chile. C3 Universidad de Concepcion; Universidad de Atacama; Universidad Tecnica Federico Santa Maria; Universidad San Sebastian