With the advancement of media and computing technologies, video compositing techniques have improved to a great extent. These techniques have been used not only in the entertainment industry but also in advertisement and new media. Match-moving is a cinematic technology in virtual-real image synthesis that allows the insertion of computer graphics (virtual objects) into real world scenes. To make a realistic virtual-real image synthesis, it is important to obtain internal parameters (such as focal length) and external parameters (position and rotation) from an Red-Green-Blue(RGB) camera. Conventional methods recover these parameters by extracting feature points from recorded video frames to guide the virtual camera. These methods fail when there is occlusion or motion blur in the recorded scene. In this paper, we propose a novel method (system) for pre-visualization and virtual-real image synthesis that overcomes the limitations of conventional methods. This system uses the spatial understanding principle of Microsoft HoloLens to perform the match-moving of virtual-real video scenes. Experimental results demonstrate that our system is much more accurate and efficient than existing systems for video compositing.

Floating holograms using holographic optical element screens differ from existing systems because they can float 2D images in the air and provide a sense of depth. Until now, the verification of such displays has been conducted only on the system implementation, and only the diffraction efficiency and angle of view of the hologram have been verified. Although such displays can be directly observed with the human eye, the eye’s control ability has not been quantitatively verified. In this study, we verified that the focus of the observer coincided with the appropriate depth value determined with experiments. This was achieved by measuring the amount of control reaction from the perspective of the observer on the image of the floating hologram using a holographic optical element (HOE). An autorefractor was used, and we confirmed that an image with a sense of depth can be observed from the interaction of the observer’s focus and convergence on the 2D floating image using a HOE. Thus, the realization of content with a sense of depth of 2D projected images using a HOE in terms of human factors was quantitatively verified.