BUDA.ART: A Multimodal Content-Based Analysis and Retrieval System for Buddha Statues
Abstract
We introduce BUDA.ART, a system designed to assist researchers in Art History, to explore and analyze an archive of pictures of Buddha statues. The system combines different CBIR and classical retrieval techniques to assemble 2D pictures, 3D statue scans and meta-data, that is focused on the Buddha facial characteristics. We build the system from an archive of 50,000 Buddhism pictures, identify unique Buddha statues, extract contextual information, and provide specific facial embedding to first index the archive. The system allows for mobile, on-site search, and to explore similarities of statues in the archive. In addition, we provide search visualization and 3D analysis of the statues
Cite
@article{arxiv.1909.12932,
title = {BUDA.ART: A Multimodal Content-Based Analysis and Retrieval System for Buddha Statues},
author = {Benjamin Renoust and Matheus Oliveira Franca and Jacob Chan and Van Le and Ayaka Uesaka and Yuta Nakashima and Hajime Nagahara and Jueren Wang and Yutaka Fujioka},
journal= {arXiv preprint arXiv:1909.12932},
year = {2019}
}
Comments
Demo video at: https://www.youtube.com/watch?v=3XJvLjSWieY