A 3D-Customized Subjective Experiment Software
A software and dataset for 3D graphics qulity assessment. Please contact slfan@pku.edu.cn if having any questions.
Figure 1: Working windows of the proposed 3D subjective experiment software.
🔥 NEWS
- [2023/06/10] 💥Create the project of software V1.0.0
Catalog
Abstract
Recently, widespread 3D graphics (e.g., point clouds and meshes) have drawn considerable efforts from academia and industry to assess their perceptual quality by conducting subjective experiments. However, lacking a handy software for 3D subjective experiments complicates the construction of 3D graphics quality assessment datasets, thus hindering the prosperity of relevant fields. In this paper, we develop a customized platform with which users can flexibly design their 3D subjective methodologies and build high-quality datasets, easing a broad spectrum of 3D graphics subjective quality study. To accurately illustrate the perceptual quality differences of 3D stimuli, our software can simultaneously render the source stimulus and impaired stimulus and allows both stimuli to respond synchronously to viewer interactions. Compared with amateur 3D visualization tool-based or image/video rendering-based schemes, our approach embodies typical 3D applications while minimizing cognitive overload during subjective experiments. We organized a subjective experiment involving 40 participants to verify the validity of the proposed software. Experimental analyses demonstrate that subjective tests on our software can produce reasonable subjective quality scores of 3D models.
Software
Figure 2: Usage procedures of our software.
Please refer to the manual to perform your subjective experiments based on our software, we also provide handy video tutorials here.
3DQA
├── example.zip ------------ An example of the compiled software
│
├── source codes.zip ------------ The source codes of our software
│
├── tutorials.mp4 ------------ The video tutorials
│
├── manual.pdf ------------ The manual file
└──...
Dataset
Figure 3: Our collected source models including (a) Rose, (b) Girl, (c) Statue, (d) Sneaker, and (d) Man.
To illustrate the validity of our scheme, we generate 40 impaired models with varying compression distortions from five high-quality point clouds (see Figure 3). Then, a subjective experiment involving 40 subjects is performed. The resulting dataset can be found here.
Citation
Please cite our paper if you find our work is helpful.
@article{fan2023screen,
title={Screen-based 3D Subjective Experiment Software},
author={Fan, Songlin and Gao, Wei},
journal={arXiv preprint arXiv:2308.03698},
year={2023}
}