Image-based rendering (IBR) technique enables presenting real scenes interactively to viewers and hence is a key component for implementing VR telepresence. The quality of IBR results depends on the set of pre-captured views, the rendering algorithm used, and the camera parameters of the novel view to be synthesized. Numerous methods were proposed for optimizing the set of captured images and enhancing the rendering algorithms. However, from which regions IBR methods can synthesize satisfactory results is not yet well studied. In this work, we introduce the concept of renderability, which predicts the quality of IBR results at any given viewpoint and view direction. Consequently, the renderability values evaluated for the 5D camera parameter space form a field, which effectively guides viewpoint/trajectory selection for IBR, especially for challenging large-scale 3D scenes. To demonstrate this capability, we designed 2 VR applications: a path planner that allows users to navigate through sparsely captured scenes with controllable rendering quality and a view selector that provides an overview for a scene from diverse and high quality perspectives. We believe the renderability concept, the proposed evaluation method, and the suggested applications will motivate and facilitate the use of IBR in various interactive settings.

Capturing the 3D geometry of transparent objects is a challenging task, ill-suited for general-purpose scanning and reconstruction techniques, since these cannot handle specular light transport phenomena. Existing state-of-the-art methods, designed specifically for this task, either involve a complex setup to reconstruct complete refractive ray paths, or leverage a data-driven approach based on synthetic training data. In either case, the reconstructed 3D models suffer from over-smoothing and loss of fine detail. This paper introduces a novel, high precision, 3D acquisition and reconstruction method for solid transparent objects. Using a static background with a coded pattern, we establish a mapping between the camera view rays and locations on the background. Differentiable tracing of refractive ray paths is then used to directly optimize a 3D mesh approximation of the object, while simultaneously ensuring silhouette consistency and smoothness. Extensive experiments and comparisons demonstrate the superior accuracy of our method.