Predicting the Perceptual Quality of Point Cloud: A 3D-to-2D Projection-Based Exploration

• Published in: IEEE transactions on multimedia Vol. 23; pp. 3877 - 3891
• Main Authors: Yang, Qi, Chen, Hao, Ma, Zhan, Xu, Yiling, Tang, Rongjun, Sun, Jun
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: 3D-to-2D projection; Color texture; Datasets; Distortion; Distortion measurement; Forecasting; Image color analysis; Image edge detection; image features; Image quality; Indexes; Noise; Optimization; Performance prediction; Planes; point cloud; quality assessment; Signal to noise ratio; Similarity; Subjective assessment; Teleportation; Three dimensional models; Three-dimensional displays; Virtual reality
• ISSN: 1520-9210; 1941-0077
• DOI: 10.1109/TMM.2020.3033117

Point cloud is emerged as a promising media format to represent realistic 3D objects or scenes in applications, such as virtual reality, teleportation, etc. How to accurately quantify the subjective point cloud quality for application-driven optimization, however, is still a challenging and open pro...