3D Shape Compression and Simplification
Supervisor: Dr Yonghuai Liu (email@example.com)
Nowadays, it is easy to capture millions of points of the object of interest using the latest scanning systems . While such a huge amount of points is useful for the description of the details of the object of interest, it presents a challenge for its pre-processing, visualization, and storage. This project intends to develop novel techniques [1, 2, 3] for the evaluation of the importance of the points for the representation of the overall geometry and local details, so that the levels of detail can be generated and transmitted for different applications.
 R. Song, Y. Liu, R.R. Martin, P.L. Rosin. Saliency-Guided Integration of Multiple Scans, Proc. of IEEE CS Conference on Computer Vision and Pattern Recognition (CVPR'12), pp. 1474-1481, 2012
 Y. Zhao, Y. Liu, R. Song, M. Zhang. A saliency detection based method for 3D surface simplification. Proceedings of the 36th IEEE International Conference on Acoustics, Speech and Signal Processing, pp. 889-892, 2012.
 Michael Garland and Paul S. Heckbert. Surface Simplification Using Quadric Error Metrics. SIGGRAPH 97.