A benchmark of DIBR Synthesized View Quality Assessment Metrics on a new database for Immersive Media Applications

Shishun Tian (1, 2) , Lu Zhang (1, 2) , Luce Morin (1, 2) , Olivier Déforges (1, 2)

1 IETR - Institut d'Électronique et des Technologies du numéRique
2 INSA Rennes - Institut National des Sciences Appliquées - Rennes

Depth-Image-Based Rendering (DIBR) is a fundamental technology in several 3D-related applications, such as Free viewpoint video (FVV), Virtual Reality (VR) and Augmented Reality (AR). However, new challenges have also been brought in assessing the quality of DIBR-synthesized views since this process induces some new types of distortions, which are inherently different from the distortion caused by video coding. In this paper, we present a new DIBR-synthesized image database with the associated subjective scores. We also test the performances of the state-of-the-art objective quality metrics on this database. This work focuses on the distortions only induced by different DIBR synthesis methods. Seven state-of-the-art DIBR algorithms, including interview synthesis and single view based synthesis methods, are considered in this database. The quality of synthesized views was assessed subjectively by 41 observers and objectively using 14 state-of-the-art objective metrics. Subjective test results show that the interview synthesis methods, having more input information, significantly outperform the single view based ones. Correlation results between the tested objective metrics and the subjective scores on this database reveal that further studies are still needed for a better objective quality metric dedicated to the DIBR-synthesized views.

Mots clés: view synthesis; FVV; quality assessment; QoE; Depth-Image-Based-Rendering (DIBR)

Domaines: Multimédia [cs.MM]; Traitement du signal et de l'image [eess.SP]

Shishun Tian, Lu Zhang, Luce Morin, Olivier Déforges. A benchmark of DIBR Synthesized View Quality Assessment Metrics on a new database for Immersive Media Applications. IEEE Transactions on Multimedia, 2019, 21 (5), pp.1235-1247. ⟨10.1109/TMM.2018.2875307⟩. ⟨hal-01899625⟩