The accuracy and efficiency of human body pose estimation depend on the quality of the data to be processed and of the particularities of these data. To demonstrate how dance videos can challenge pose estimation techniques, we proposed a new 3D human body pose estimation pipeline which combined up-to-date techniques and methods that had not been yet used in dance analysis. Second, we performed tests and extensive experimentations from dance video archives, and used visual analytic tools to evaluate the impact of several data parameters on human body pose. Our results are publicly available for research atthis https URL
View on arXiv@article{colantoni2025_2505.07249,
title={ When Dance Video Archives Challenge Computer Vision },
author={ Philippe Colantoni and Rafique Ahmed and Prashant Ghimire and Damien Muselet and Alain Trémeau },
journal={arXiv preprint arXiv:2505.07249},
year={ 2025 }
}