Comparison of a point cloud compression methods and benchmark of objective quality metrics

18th October 2018

Proposed by Emin Zerman –¬†zermane at

Point clouds (PC) are a popular representation method both for static 3D models and for free-viewpoint videos (FVV). Compression is necessary to store and transmit the PCs, as the file sizes of these PCs are very high. Quality evaluation is crucial for the development of these compression algorithms.

In this project, the goal is to create a PC quality database using several point cloud compression (PCC) methods and to evaluate the performances of the objective quality metrics. For this purpose, subjective quality scores need to be collected. Possible benefits to the MSc student include learning the cutting-edge point cloud compression technologies, understanding data representation format of PCs, and develop a sense for the quality evaluation research.

Useful references:
[1] R. Mekuria, Z. Li, C. Tulvan, and P. Chou, “Evaluation Criteria for Point Cloud Compression,” ISO/IEC JTC1/SC29/WG11 MPEG n16332, Geneva, Switzerland, Feb. 2016.
[2] E. Alexiou and T. Ebrahimi, “On Subjective and Objective Quality Evaluation of Point Cloud Geometry,” in 9th International Conference on Quality of Multimedia Experience (QoMEX), 2017.
[3] A. Javaheri, C. Brites, F. Pereira and J. Ascenso, “Subjective and objective quality evaluation of compressed point clouds,” 2017 IEEE 19th International Workshop on Multimedia Signal Processing (MMSP), Luton, 2017.