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To explore methods that are currently used by professional virtual reality (VR) filmmakers to tell their stories and guide users, we analyze how end-users view 360 • video in the presence of directional cues and evaluate if they are able to follow the actual story of narrative 360 • films. In this context, we first collected data from five professional VR filmmakers. The data contains eight 360 • videos, the directors cut, which is the intended viewing direction of the director, plot points and directional cues used for user guidance. Then, we performed a subjective experiment with 20 test subjects viewing the videos while their head orientation was recorded. Finally, we present and discuss the experimental results and show, among others, that visual discomfort and disorientation on part of the viewer not only lessen the immersive quality of the films but also cause difficulties in the viewer gaining a full understanding of the narrative that the director wished them to view.

Increasing popularity of 3D videos calls for new methods to ease the conversion process of existing monocular video to stereoscopic or multi-view video. A popular way to convert video is given by depth image-based rendering methods, in which a depth map that is associated with an image frame is used to generate a virtual view. Because of the lack of knowledge about the 3D structure of a scene and its corresponding texture, the conversion of 2D video, inevitably, however, leads to holes in the resulting 3D image as a result of newly-exposed areas. The conversion process can be altered such that no holes become visible in the resulting 3D view by superimposing a regular grid over the depth map and deforming it. In this paper, an adaptive image warping approach as an improvement to the regular approach is proposed. The new algorithm exploits the smoothness of a typical depth map to reduce the complexity of the underlying optimization problem that is necessary to find the deformation, which is required to prevent holes. This is achieved by splitting a depth map into blocks of homogeneous depth using quadtrees and running the optimization on the resulting adaptive grid. The results show that this approach leads to a considerable reduction of the computational complexity while maintaining the visual quality of the synthesized views.