In this paper, we present an efficient approach for the compression of stereoscopic video sequences. By extending an H.264/AVC-based multi-view video coding (MVC) codec as described in a previous paper to mixed-resolution imagery, i.e., to stereoscopic videos where the right-eye view had been spatially down-sampled in order to reduce the total amount of data to be encoded, we are able to combine the benefits of both disparity-compensated prediction (DCP) and asymmetric coding. By doing so, we expect to achieve very high compression gains without reducing the overall visual quality of the resulting three-dimensional (3D) percept.

A holographic display system with a 22-inch LCD panel is developed to provide a wide viewing angle and large holographic 3D image. It is realized by steering a narrow viewing window resulting from a very large pixel pitch compared to the wave length of the laser light. Point light sources and a lens array make it possible to arbitrarily control the position of the viewing window for a moving observer. The holographic display provides both eyes of the observer with a holographic 3D image using two vertically placed LCD panels and a beam splitter to support the holographic stereogram.

In this study, we thoroughly investigated the reactive ion etching mechanism of RuO₂ film in oxygen plasma with the addition of CF₄, Cl₂, and N₂. The etch rate of RuO₂ was examined as functions of flow rates of input gases, substrate temperature, DC bias applied to the substrate, and pressure. The concentrations of the etching species in the plasma were determined using optical emission spectroscopy (OES) and a quadrupole mass spectrometer (QMS). The etch products were determined with a QMS and the etched surface of RuO₂ film was examined with X-ray photoelectron spectroscopy (XPS). RuO₄ and RuO₃, which are formed by the reactions between RuO₂ film and oxygen radicals, are the only etch products regardless of the kind of additive gas. The additive gases (CF₄, Cl₂, and N₂) are not directly involved in the chemical reaction with the RuO₂ film, but they increase the concentration of oxygen radicals and accordingly, appreciably increase the etch rate of the RuO₂ films. The etch rate is limited by the formation rate of the etch products, which is enhanced by the bombardment of energetic ions. Therefore, the etch rate depends not only on the concentration of oxygen radicals, but also on the flux and energy of the ions bombarding the film surface. In this study, for the first time, we introduced the use of the O₂/N₂ plasma system in RuO₂ etching.

As the next‐generation video coding standard, High Efficiency Video Coding (HEVC) has adopted advanced coding tools despite the increase in computational complexity. In this paper, we propose a selec...

The use of human gesturing to interact with devices such as computers or smartphones has presented several problems. This form of interaction relies on gesture interaction technology such as Leap Motion from Leap Motion, Inc, which enables humans to use hand gestures to interact with a computer. The technology has excellent hand detection performance, and even allows simple games to be played using gestures. Another example is the contactless use of a smartphone to take a photograph by simply folding and opening the palm. Research on interaction with other devices via hand gestures is in progress. Similarly, studies on the creation of a hologram display from objects that actually exist are also underway. We propose a hand gesture recognition system that can control the Tabletop holographic display based on an actual object. The depth image obtained using the latest Time-of-Flight based depth camera Azure Kinect is used to obtain information about the hand and hand joints by using the deep-learning model CrossInfoNet. Using this information, we developed a real time system that defines and recognizes gestures indicating left, right, up, and down basic rotation, and zoom in, zoom out, and continuous rotation to the left and right.

RGB-D cameras have been commercialized, and many applications using them have been proposed. In this paper, we propose a robust registration method of multiple RGB-D cameras. We use a human body tracking system provided by Azure Kinect SDK to estimate a coarse global registration between cameras. As this coarse global registration has some error, we refine it using feature matching. However, the matched feature pairs include mismatches, hindering good performance. Therefore, we propose a registration refinement procedure that removes these mismatches and uses the global registration. In an experiment, the ratio of inliers among the matched features is greater than 95% for all tested feature matchers. Thus, we experimentally confirm that mismatches can be eliminated via the proposed method even in difficult situations and that a more precise global registration of RGB-D cameras can be obtained.