SDAS: Semantic Data Acquisition System for Minimizing Redundancy and Maximizing Diversity
Abstract
In this paper, we propose SDAS, a new motion data assessment and storage system designed to acquire new motion data with reduced redundancy and maximizing diversity. SDAS collects data in the field, retrieves the most similar data from the database in real-time, and provides visualization tools that allow for the comparison of differences between the capture data and the stored data. Through this system, researchers can efficiently build and manage a database. The demonstration video is available at https://youtu.be/vqW0uMDnZTw.
Cite
Text
Park et al. "SDAS: Semantic Data Acquisition System for Minimizing Redundancy and Maximizing Diversity." AAAI Conference on Artificial Intelligence, 2025. doi:10.1609/AAAI.V39I28.35365Markdown
[Park et al. "SDAS: Semantic Data Acquisition System for Minimizing Redundancy and Maximizing Diversity." AAAI Conference on Artificial Intelligence, 2025.](https://mlanthology.org/aaai/2025/park2025aaai-sdas/) doi:10.1609/AAAI.V39I28.35365BibTeX
@inproceedings{park2025aaai-sdas,
title = {{SDAS: Semantic Data Acquisition System for Minimizing Redundancy and Maximizing Diversity}},
author = {Park, Yeseung and Yoon, Hyunse and Huh, Jungwoo and Kim, Jungsu and Choi, Jeongwook and Lee, Sanghoon},
booktitle = {AAAI Conference on Artificial Intelligence},
year = {2025},
pages = {29679-29681},
doi = {10.1609/AAAI.V39I28.35365},
url = {https://mlanthology.org/aaai/2025/park2025aaai-sdas/}
}