An objective 3D quality assessment model to adjust stereo camera baseline

Stereoscopic video systems aim to confer a true three-dimensional (3D) view of the real world. However, in the process of 3D image acquisition and display, eventual distortions may affect the 3D perceptual quality, leading to visual discomfort. As visual comfort is a key issue when dealing with 3D acceptance, subjective tests (that are time consuming and cannot provide quality scores on the fly) have been conducted in order to establish 3D assessment factors. In this work, we use the ground truth of a publicly available database in order to develop a method to automatically assess the visual comfort of stereoscopic imagery. The assessment has the objective of assisting in the adjustment of stereo camera baselines. The method employs stereo vision geometry and stereo matching algorithms to estimate depth planes, for each video frame, in order to associate their locations with different visual comfort zones. The proposed method shows a high level of correlation with subjective tests, comparing favorably with another proposal from the literature.