3DYoga90: A Hierarchical Video Dataset for Yoga Pose Understanding
This dataset addresses the need for professional exercise video datasets in AI, specifically for yoga action recognition and pose assessment, but it is incremental as it builds on an existing dataset.
The authors introduced 3DYoga90, a hierarchical video dataset for yoga pose understanding, expanding an existing dataset from 82 to 90 poses and including RGB videos and 3D skeleton sequences, with experiments showing its practicality through benchmarking with three model variants.
The increasing popularity of exercises including yoga and Pilates has created a greater demand for professional exercise video datasets in the realm of artificial intelligence. In this study, we developed 3DYoga901, which is organized within a three-level label hierarchy. We have expanded the number of poses from an existing state-of-the-art dataset, increasing it from 82 to 90 poses. Our dataset includes meticulously curated RGB yoga pose videos and 3D skeleton sequences. This dataset was created by a dedicated team of six individuals, including yoga instructors. It stands out as one of the most comprehensive open datasets, featuring the largest collection of RGB videos and 3D skeleton sequences among publicly available resources. This contribution has the potential to significantly advance the field of yoga action recognition and pose assessment. Additionally, we conducted experiments to evaluate the practicality of our proposed dataset. We employed three different model variants for benchmarking purposes.