With the popularity of immersive display systems that fill the viewer’s field of view (FOV) entirely, demand for wide FOV content has increased. A video extrapolation technique based on reuse of existing videos is one of the most efficient ways to produce wide FOV content. Extrapolating a video poses a great challenge, however, due to the insufficient amount of cues and information that can be leveraged for the estimation of the extended region. This article introduces a novel framework that allows the extrapolation of an input video and consequently converts a conventional content into one with wide FOV. The key idea of the proposed approach is to integrate the information from all frames in the input video into each frame. Utilizing the information from all frames is crucial because it is very difficult to achieve the goal with a two-dimensional transformation based approach when parallax caused by camera motion is apparent. Warping guided by three-dimensnional scene points matches the viewpoints between the different frames. The matched frames are blended to create extended views. Various experiments demonstrate that the results of the proposed method are more visually plausible than those produced using state-of-the-art techniques.

In this letter, we investigate the dynamic rate allocation and forwarding strategy adaption scheme for wireless networks with potential selfish nodes. Aided by an incentive mechanism, we develop a stochastic differential equation (SDE) to portray the dynamic node selfishness in terms of node's energy resource and incentives. Then, a stochastic optimization model is employed to maximize the average network utility while bounding the node selfishness. Based on the continuous-time Lyapunov optimization theory, we solve the optimization problem and propose a dynamic rate allocation and forwarding strategy update (DRAF) algorithm to accommodate the dynamic network state. We further analyze the tracking errors between the output of DRFA algorithm and the optimal solution. Then, an adaptive-compensation rate allocation and forwarding strategy update (ACRAF) algorithm is designed, which iterates only once when network state changes. Finally, we provide a sufficient condition that the ACRAF algorithm asymptotically tracks the moving equilibrium point with no tracking errors. Simulation results validate the theoretical analysis.

This paper presents Rich360, a novel system for creating and viewing a 360° panoramic video obtained from multiple cameras placed on a structured rig. Rich360 provides an as-rich-as-possible 360° viewing experience by effectively resolving two issues that occur in the existing pipeline. First, a deformable spherical projection surface is utilized to minimize the parallax from multiple cameras. The surface is deformed spatio-temporally according to the depth constraints estimated from the overlapping video regions. This enables fast and efficient parallax-free stitching independent of the number of views. Next, a non-uniform spherical ray sampling is performed. The density of the sampling varies depending on the importance of the image region. Finally, for interactive viewing, the non-uniformly sampled video is mapped onto a uniform viewing sphere using a UV map. This approach can preserve the richness of the input videos when the resolution of the final 360° panoramic video is smaller than the overall resolution of the input videos, which is the case for most 360° panoramic videos. We show various results from Rich360 to demonstrate the richness of the output video and the advancement in the stitching results.

Abstract The reconstruction of 3D terrain geometry from images is essential for compositing CG objects into a live‐action background or for 2D to 3D conversion of terrain scenes. We present a novel mesh refinement algorithm for the creation of stereoscopic images of terrain scenes. Previous approaches emphasise the smoothness of the resulting terrain mesh over accuracy 1 . Point cloud‐based methods cannot effectively recover the entire surface, leading to visual discrepancies after monocular sequences are converted into 3D stereo. As misalignment or inaccurate 3D terrain data over corresponding 2D background images can result in visual fatigue when stereo sequences are generated, ensuring accuracy of the reconstructed geometry is very important. To achieve the necessary accuracy, our method evaluates mesh errors utilising a texture projection onto the geometry and refines the mesh using Laplacian‐based editing. Our algorithm automatically generates stereoscopic images of terrain scenes. In addition, our method simplifies identification and compositing of foreground objects on the terrain geometry. Copyright © 2011 John Wiley & Sons, Ltd.