This paper presents a method for view synthesis from multiple views and their depth maps for free navigation in Virtual Reality with six degrees of freedom (6DoF) and 360 video (3DoF+), including synthesizing views corresponding to stepping in or out of the scene. Such scenarios should support large baseline view synthesis, typically going beyond the view synthesis involved in light field displays [1]. Our method allows to input an unlimited number of reference views, instead of the usual left and right reference views. Increasing the number of reference views overcomes problems such as occlusions, tangential surfaces to the cameras axis and artifacts in low quality depth maps. We outperform MPEG's reference software, VSRS [2], with a gain of up to 2.5 dB in PSNR when using four reference views.Index Terms -View synthesis, depth image based rendering, free navigation
This paper presents a novel approach to provide immersive free navigation with 6 Degrees of Freedom in real-time for natural and virtual scenery, for both static and dynamic content. Stemming from the state-of-the-art in Depth Image-Based Rendering and the OpenGL pipeline, this new View Synthesis method achieves free navigation at up to 90 FPS and can take any number of input views with their corresponding depth maps as priors. Video content can be played thanks to GPU decompression, supporting free navigation with full parallax in real-time. To render a novel viewpoint, each selected input view is warped using the camera pose and associated depth map, using an implicit 3D representation. The warped views are then blended all together to generate the chosen virtual view. Various view blending approaches specifically designed to avoid visual artifacts are compared. Using as few as four input views appears to be an optimal trade-off between computation time and quality, allowing to synthesize high-quality stereoscopic views in real-time, offering a genuine immersive virtual reality experience. Additionally, the proposed approach provides high-quality rendering of a 3D scenery on holographic light field displays. Our results are comparable -objectively and subjectively -to the state of the art view synthesis tools NeRF and LLFF, while maintaining an overall lower complexity and real-time rendering.
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