ABSTRACTe curved screen has a racted considerable a entions in recent years, since it enables to enlarge the view angle and to enhance the immersive perception for users. However, existing curved surface projections are frequently prone to geometric distortion or loss of content. is paper presents a content-aware and depth-aware image adaptation solution for curved displays. An e cient optimization approach of image deformation is proposed to preserve local scene content and to minimize scene geometry distortion. To follow the original 3D perception of objects in di erent depth layers, the depth information is re-mapped for individual content scaling. Objective evaluation results reveal that our approach can e ectively preserve foreground objects. We also perform a subjective evaluation of the proposed solution, and compare it to two alternative mapping methods, which are tested on di erent curvatures on both a traditional screen and an ad-hoc curvature-controllable curved display. Experimental results demonstrate that our approach outperforms other existing mapping methods for immersive display of rectangle images on curved screens.
A 3D human head scan contains both texture and mesh data to convey the illusion of a human head. We perform subjective tests with a set of observers to distil the relative importance of texture resolution versus mesh resolution for human head scans, which is important for bandwidth limited applications such as video conferencing. The mean observer scores (MOS) obtained from the tests allow us to propose a numeric model for estimating user perception in the tested conditions.
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