Preserving the Khmer smile: classifying and restoring the faces of Bayon

Authors:
Min Lu;Bo Zheng;Jun Takamatsu;Ko Nishino;Katsushi Ikeuchi
Affiliations:
Institute of Industrial Science, The University of Tokyo, Japan;Institute of Industrial Science, The University of Tokyo, Japan;Graduate School of Information Science, Nara Institute of Science and Technology, Japan;Department of Computer Science, Drexel University;Institute of Industrial Science, The University of Tokyo, Japan
Venue:
VAST'11 Proceedings of the 12th International conference on Virtual Reality, Archaeology and Cultural Heritage
Year:
2011

Citing 11
Cited 0

Simplification and Repair of Polygonal Models Using Volumetric Techniques

IEEE Transactions on Visualization and Computer Graphics
Filling holes in meshes

Proceedings of the 2003 Eurographics/ACM SIGGRAPH symposium on Geometry processing
Pattern Classification (2nd Edition)

Pattern Classification (2nd Edition)
Context-based surface completion

ACM SIGGRAPH 2004 Papers
Robust repair of polygonal models

ACM SIGGRAPH 2004 Papers
Pattern Recognition and Machine Learning (Information Science and Statistics)

Pattern Recognition and Machine Learning (Information Science and Statistics)
Template-based mesh completion

SGP '05 Proceedings of the third Eurographics symposium on Geometry processing
Example-based 3D scan completion

SGP '05 Proceedings of the third Eurographics symposium on Geometry processing
Digitally Archiving Cultural Objects

Digitally Archiving Cultural Objects
Three-Dimensional Surface Relief Completion Via Nonparametric Techniques

IEEE Transactions on Pattern Analysis and Machine Intelligence
3D shape restoration via matrix recovery

ACCV'10 Proceedings of the 2010 international conference on Computer vision - Volume part II

Quantified Score

Hi-index	0.00

Visualization

Abstract

The Bayon temple is known for its numerous massive stone faces with serene smiles, often referred to as the 'Khmer Smile.' Many of these sculptures are, however, only partially preserved, making it difficult to see the original appearance of these faces. To restore the Bayon faces, we propose a novel method that builds upon the matrix recovery theory. The method achieves accurate restoration by adopting a two-step shape recovery strategy. Rough restoration and clustering processes are first carried out using the entire database to group similar samples together. Then refined restoration using high resolution data is executed in each cluster to restore higher details while retaining the characteristics of each face. Experimental results demonstrate the effectiveness of our proposed method.