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In rate-distortion optimization, the encoder settings are determined bymaximizing a reconstruction quality measure subject to a constraint on the bitrate. One of the main challenges of this approach is to define a qualitymeasure that can be computed with low computational cost and which correlateswell with perceptual quality. While several quality measures that fulfil thesetwo criteria have been developed for images and video, no such one exists for3D point clouds. We address this limitation for the video-based point cloudcompression (V-PCC) standard by proposing a linear perceptual quality modelwhose variables are the V-PCC geometry and color quantization parameters andwhose coefficients can easily be computed from two features extracted from theoriginal 3D point cloud. Subjective quality tests with 400 compressed 3D pointclouds show that the proposed model correlates well with the mean opinionscore, outperforming state-of-the-art full reference objective measures interms of Spearman rank-order and Pearsons linear correlation coefficient.Moreover, we show that for the same target bit rate, ratedistortionoptimization based on the proposed model offers higher perceptual quality thanrate-distortion optimization based on exhaustive search with a point-to-pointobjective quality metric.

Reduced Reference Perceptual Quality Model With Application to Rate Control for Video-Based Point Cloud Compression