arXiv Open Access 2025

When Dance Video Archives Challenge Computer Vision

Philippe Colantoni Rafique Ahmed Prashant Ghimire Damien Muselet Alain Trémeau

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Abstrak

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 at https://www.couleur.org/articles/arXiv-1-2025/

Topik & Kata Kunci

cs.CV

Penulis (5)

Philippe Colantoni

Rafique Ahmed

Prashant Ghimire

Damien Muselet

Alain Trémeau

Format Sitasi

APA MLA BibTeX

Colantoni, P., Ahmed, R., Ghimire, P., Muselet, D., Trémeau, A. (2025). When Dance Video Archives Challenge Computer Vision. https://arxiv.org/abs/2505.07249

Akses Cepat

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Informasi Jurnal

Tahun Terbit: 2025
Bahasa: en
Sumber Database: arXiv
Akses: Open Access ✓