BASICS DATASET: Broad Quality Assessment of Static Point Clouds in a Compression Scenario

Point clouds have become increasingly prevalent in representing 3D scenes within virtual environments, alongside 3D meshes. Their ease of capture has facilitated a wide array of applications on mobile devices, including smartphones and other microcontrollers. Notably, point cloud compression has reached an advanced stage and being standardized. However, the availability of quality assessment datasets, which are essential for the development of improved objective quality metrics, remains limited. We introduce BASICS, a large-scale quality assessment dataset tailored for static point clouds. The BASICS dataset comprises 75 unique point clouds, each compressed with four different algorithms, resulting in the evaluation of nearly 1500 point clouds by 3500 unique participants. For a detailed explanation of the dataset and the analysis done, please refer to the related publication: @ARTICLE{10403987, author={Ak, Ali and Zerman, Emin and Quach, Maurice and Chetouani, Aladine and Smolic, Aljosa and Valenzise, Giuseppe and Le Callet, Patrick}, journal={IEEE Transactions on Multimedia}, title={BASICS: Broad Quality Assessment of Static Point Clouds in a Compression Scenario}, year={2024}, pages={1-13}, doi={10.1109/TMM.2024.3355642}} BASICS paper is accepted to be published in IEEE TMM. The above article will be updated later on with the correct DOI. The BASICS dataset was previously used for the ICIP 2023 ICIP PCQVA Grand Challenge. Since the challenge is over, we are making it public for the community to build upon! Check the link below for the ICIP 2023 PCQVA Challenge Page: https://sites.google.com/view/icip2023-pcvqa-grand-challenge/