Arnab Dey1,*, Samit Biswas1, Dac-Nhuong Le2
CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 3067-3087, 2024, DOI:10.32604/cmc.2024.049512
Abstract Regular exercise is a crucial aspect of daily life, as it enables individuals to stay physically active, lowers the likelihood of developing illnesses, and enhances life expectancy. The recognition of workout actions in video streams holds significant importance in computer vision research, as it aims to enhance exercise adherence, enable instant recognition, advance fitness tracking technologies, and optimize fitness routines. However, existing action datasets often lack diversity and specificity for workout actions, hindering the development of accurate recognition models. To address this gap, the Workout Action Video dataset (WAVd) has been introduced as a significant… More >
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