Development and performance evaluation of efficient methods for coding, transmission, and quality assessment of 3D visual content require rich datasets of a suitable test material. The use of these databases allows a fair comparison of systems under test. Moreover, publicly available and widely used datasets are crucial for experimentation leading to reproducible research. This chapter presents an overview of 3D visual content datasets relevant to research in the field of coding, transmission, and quality assessment. Description of regular stereoscopic or multiview image and video datasets is presented. Databases created using emerging technologies, including light-field imaging, are also addressed. Moreover, there are databases of multimedia content annotated with ratings from the subjective experiment, which are a necessary resource for understanding the complex problem of quality of experience while consuming the 3D visual content.
Fliegel, K., Battisti, F., Carli, M., Gelautz, M., Krasula, L., Le Callet, P., et al. (2019). 3D Visual Content Datasets. In Signals and Communication Technology (pp. 299-325). Springer [10.1007/978-3-319-77842-6_11].
3D Visual Content Datasets
Battisti F.;Carli M.;Le Callet P.;
2019-01-01
Abstract
Development and performance evaluation of efficient methods for coding, transmission, and quality assessment of 3D visual content require rich datasets of a suitable test material. The use of these databases allows a fair comparison of systems under test. Moreover, publicly available and widely used datasets are crucial for experimentation leading to reproducible research. This chapter presents an overview of 3D visual content datasets relevant to research in the field of coding, transmission, and quality assessment. Description of regular stereoscopic or multiview image and video datasets is presented. Databases created using emerging technologies, including light-field imaging, are also addressed. Moreover, there are databases of multimedia content annotated with ratings from the subjective experiment, which are a necessary resource for understanding the complex problem of quality of experience while consuming the 3D visual content.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
