Work

BUDA.ART: A Multimodal Content-Based Analysis and Retrieval System for Buddha Statues

Year: 2019

Type: preprint

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

Source: arXiv (Cornell University)

DOI: 10.48550/arxiv.1909.12932

Authors: Renoust, Benjamin, Franca, Matheus Oliveira, Chan, Jacob, Le, Van, Uesaka, Ayaka, Nakashima, Yuta, Nagahara, Hajime, Wang, Jueren, Fujioka, Yutaka

Institutions: The University of Osaka, Osaka University of Economics

Language: English

Topic: Image Retrieval and Classification Techniques

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

Funder: Japan Society for the Promotion of Science

Award: Stylistic analysis of Buddhist sculptures by using Artificial Intelligence and 3D measurement data with a special focus on facial expressions

OpenAlex ID: W2977006678

Cites: 14

Cited by:

Related to: 10