Yoga Pose

Research on yoga pose recognition focuses on developing accurate and efficient computer vision systems to automatically identify and assess yoga postures from images or videos. Current efforts leverage deep convolutional neural networks (CNNs), often incorporating attention mechanisms and efficient architectures like EfficientNets, to achieve high accuracy even on challenging datasets with significant intra- and inter-class variations. These advancements are driven by the growing popularity of yoga and the need for tools to improve practice accuracy and accessibility, impacting both the development of smart healthcare applications and the advancement of computer vision techniques for human pose estimation. The creation and use of large, publicly available datasets are crucial for benchmarking and driving further progress in this field.