Digital Bayon Project
This talk introduces Digital Bayon Project, conducted by The University of Tokyo team, with the cooperation of the Japanese Government team for Safeguarding Angkor, to scan the Bayon temple and obtain 3D digital data of the temple.
Der Arbeitsbereich Bildverarbeitung und Mustererkennung (PRIP) am Institut für Rechnergestützte Automation (E183) lädt ein:
This talk introduces Digital Bayon Project, conducted by The University of Tokyo team, with the cooperation of the Japanese Government team for Safeguarding Angkor, to scan the Bayon temple and obtain 3D digital data of the temple. We have conducted over 1500 person-day scanning missions. During these missions, we obtained range data from more than 14,600 different directions using commercially available sensors, such as Cyrax and Z+F, as well as newly developed sensors for this scanning mission, such as the UTokyo Balloon and UTokyo climbing sensors. The total amount of the data approximates a quarter of a terabyte.
We have developed parallel alignment processing with merging software that run on a PC cluster a hundred times faster than previously available software. This cluster processes our massive range data into unified 3D digital data of the Bayon temple.
As a result of this effort, we have obtained the following 3D data:
The entire Bayon 3D structure
By using Cyrax, Z+F, balloon and climbing sensors, we have obtained a 3D model of the entire Bayon temple. From this model, we have created floor plans of the temple, and have confirmed that the Bayon temple is rotated 0.94 degrees counter-clockwise from the exact east-west lines.
173 Deity Faces
We have scanned all the 173 faces of the deities on the exterior of the temple using Cyrax and Balloon sensors, analyzed these data, and verified that we can classify these faces into three categories: Dava, Davatar, and Asherah. It was also confirmed that there is sufficient resemblance among groups of faces to support the assumption that more than one worker group conducted the construction project in a parallel manner.
16 Hidden Pediments
By using a newly created mirror range sensor, we obtained pictures of 16 hidden pediments, whose existence had not been previously known.
8 Wall Reliefs
We obtained 3D digital data of all eight wall reliefs along the inner and outer corridors using a VIVID sensor. We plan to continue our efforts to create finer models of the structure, to fill the holes still missing in parts of the structure, and to complete our models by adding texture to the 3D digital data.
Dr. Katsushi Ikeuchi is a Professor at the University of Tokyo. He received a Ph.D. degree in Information Engineering from the University of Tokyo in 1978. After working at the Massachusetts Institute of Technology's AI Lab for two years, Electrotechnical Lab, Japan for five years, and Carnegie Mellon University for ten years, he joined the university in 1996. His research interest spans computer vision, robotics, and computer graphics. He has received several awards, including the IEEE R&A K-S Fu Memorial Best Transaction Paper award for the paper "Toward Automatic Robot Instruction from Perception." He is a distinguished speaker of the IEEE CS society this year. He has been elected as a fellow of IEEE since 1998.
Di, 9. September 2008
Prof. Katsushi Ikeuchi
University of Tokyo
1040 Wien, Favoritenstraße 9-11, Stiege 1, 4. Stock, Gelber Bereich
Research, Teaching