Floating touch display systems, which allow touch interaction with a control panel formed as an aerial image by the user's finger, have the problem that the perceived depth position of the aerial image is uncertain, reducing operability. To overcome this problem, a semitransparent mirror is installed on the display device, which reflects light from the hand to form an aerial image of the hand using an optical imaging element. The coincident position between the actual fingertip and the fingertip of the optical image corresponds to the depth position of the aerial image. A prototype system of the floating touch display using a dihedral corner reflector array with the proposed visual feedback using a semitransparent mirror was constructed, and experiments were conducted using simple button operations to measure the accuracy of depth positioning in pointing tasks to evaluate the effectiveness of the proposed method.

In this paper, we introduce the Surface Universality Rating (SUR) method to accurately measure surface sharpness from a point cloud. Moreover, this study represents the first attempt to distinguish edge points automatically. The easy and accurate evaluation of surface sharpness is a critical challenge associated with point cloud processing. Although surface sharpness is an essential property for shape analysis, local analytical methods for the evaluation of surface properties exhibit limitations in terms of geometric shape. Furthermore, local analyses are insufficient for evaluating the sharpness of edge points owing to the scarcity of neighboring points. These challenges require more accurate assessments of surface sharpness, as well as more efficient thresholding for feature points. Although many methods have been developed to evaluate surface sharpness, they are generally difficult to use and require many parameters. We conducted experiments to verify the effectiveness of our method.

We propose a method for compressively acquiring a light field video using a single camera equipped with an optical aperture-exposure coding mechanism. The aperture-exposure coding is applied to each exposure time, enabling the embedding of the information of a light field video (a 5-D volume) into a single observed image (a 2-D measurement). Temporally-successive images obtained from the camera are used to computationally reconstruct the light field video at a faster frame rate than that of the camera. We also developed a hardware prototype to validate our method on real 3-D time-varying scenes. Using our method, we can obtain a light field video with 5 × 5 viewpoints over 4 temporal sub-frames (100 views in total) per each observed image. By repeating the capture and reconstruction processes over time, we can acquire a light field video of arbitrary length at 4 × the frame rate of the camera. To the best of our knowledge, we are the first to propose a method of joint angular-temporal compression for light-field acquisition, achieving a finer temporal resolution than that of the camera. A supplementary video is available from https://youtu.be/FAujrak8Dok.

This paper proposed the aerial optical system of aerial image and rear display for edge-based depth-fused 3D (DFD) display to improve visibility of 2D image outside 3D viewing zone. Edge-based DFD display is composed of 2D image and its edge patterns. This leads to visibility improvement of 2D image outside 3D viewing zone, which is the problem of conventional DFD display. The proposed optical system can easily reconstruct a 3D image by changing luminance of edge patterns in front of or behind 2D image. We clarify that the proposed optical system is effective as a 3D display technology.

We propose the optical system using two infinity mirrors for aerial imaging in four directions to solve the limitation of display direction in multiple aerial imaging. With no physical contact, aerial images are expected to be an aerial guide that can be displayed directly in front of a person on the walkway. As an additional advantage, the aerial guide can be displayed in any fixed position, even in flowing water or on narrow passageways. Multiple aerial imaging techniques in multiple directions are expected to be used as aerial guides in these situations. From the simulations and the experiments, multiple aerial imaging in four directions was confirmed to be performed using the non-collinear beam splitter arrangement. Furthermore, high reflectance of the beam splitter increased the luminance of the aerial image. In addition, the use of surface reflections from retro-reflector was also found to improve the luminance of the aerial image.

We present a method for estimating the parameters needed to compute a reflection model of thin-film interference, using multiple RGB values of the iridescent effects obtained from images taken with an RGB camera to render the iridescent effects of a real object. In the field of optics, many effective methods have been proposed to estimate the thickness and refractive index of thin films, assuming that the refractive index of the base material is known. We assume that the complex refractive index of the base material is also unknown. We consider the parameters related to thin-film interference such that the RGB values of the image appear as the iridescent effects as vectors and find the combination of vectors with the smallest Euclidean distance. We consider that we have estimated the parameters that appears an iridescent effect close to the reference image.

In this paper, we propose a high-resolution, full-color light-field display using a super-multiview method capable of presenting parallax in both horizontal and vertical directions. Our objective is to project nine full-color views to the viewer's eye, generating parallax effects. To achieve this, we introduce a method that involves generating nine viewpoints through nine-fold time-division and color multiplexing. This method utilizes 3.1-inch LCD panels with a refresh rate of 120 Hz. Additionally, we have reduced the size of the display system to a hand-held size, intending to develop a head-mount display. Our proposed method not only reproduces the natural blur effect when the image is defocused but also successfully induces focal accommodation in observers. To validate our approach, we conducted measurements of focal responses using a refractometer. The experiments confirmed the effectiveness of our method in inducing focal accommodation.

This study discusses the phenomenal characteristics of depth perception on a Plane Fog Screen (PFS) through multiple basic evaluations to expect its potential as a new simple 3D display. Basic evaluations revealed that the observation angle is important for depth perception on PFS. Then, the fixed PFS requires the observer to move in front of PFS to achieve the desired depth perception. Based on these results, in this study, we propose the PFS with rotation function that achieves unfixed depth perception even when the observer is stationary and investigate the depth perception characteristics on the variable projection angle PFS.

Emergency medical care involves a high level of urgency and requires a team approach. Thus, the need for simulation-based education is high. Evaluation, however, is difficult to perform. Therefore, we carried out a study to analyze the trajectories of medical personnel during treatment to contribute to simulation-based medical education. We installed four stereo cameras on the ceiling around one treatment bed in an emergency room (ER). We extracted the trajectories of medical personnel and recorded their conversations and the ambient sounds during treatment. In this paper, to investigate the meaning of trajectories in the ER, we analyzed the relationship between the trajectories and the progress of medical activities. Our results showed a clear correlation of the progress of the medical activities with the trajectory distance and the number of starts of movement.

We propose deep learning based Hierarchical Object Detection System (HODS) adopting a depth correction scheme designed to improve detection performance in high-resolution aerial images obtained by UAVs. This system consists of a hierarchical two-stage inference unit such as Global Detecting Unit (GDU) and Local Detecting Unit (LDU) for detecting large and small objects respectively, while the Small-object Collecting Unit (SCU) component creates a reconstruction image for local detection. The high-resolution aerial images are first downsampled, and then coarse inference is performed by the GDU to detect large objects and small object candidates. Next, based on the distribution of small object candidates, the SCU collects rectangular areas where small objects are located and creates a reconstruction image with a new normalization approach, the depth correction scheme. Finally, the LDU performs fine inference on the reconstruction image to detect small objects. In evaluations, HODS achieved the highest mean average precision score.

We have studied high-speed optical phased arrays (OPAs) using electro-optic (EO) polymers for various applications, including range imaging, three-dimensional shape measurement, spatial light communication, and image display. The suppression of the stray light caused by radiation loss in curved waveguides and coupling loss in optical splitters is very important in OPAs using EO polymer. Stray light causes degradation, for example, in the image quality on a display or the signal-to-noise ratio on an optical sensor. In this study, we investigate optical loss reduction by optimizing the design of a curved waveguide and an optical splitter to suppress stray light and improve the optical beam quality from OPAs. We perform numerical simulations and an experimental evaluation of the designed OPAs and confirm the effectiveness of the optimal design for stray light suppression.

We are currently developing Advanced Integrated Services Digital Broadcasting-Terrestrial (Advanced ISDB-T) system toward the next generation of digital terrestrial television broadcasting. Advanced ISDB-T can provide a fixed reception service and a mobile reception service simultaneously. Furthermore, a channel bonding (CB) scheme that uses multiple radio frequency (RF) signals is useful to expand the transmission capacity as an optional function of Advanced ISDB-T. For example, CB scheme in Advanced ISDB-T enables to provide a flexible service such that an ultra-high definition (UHD) service can use the CB and HD service in a single channel. In this paper, we study the application of a CB scheme for Advanced ISDB-T, which has two division modes: division of the data stream in the transport layer and that in the physical layer. We evaluated the transmission performances using computer simulations and laboratory tests. Furthermore, the feasibilities of the CB transmissions were verified by a laboratory test using a prototype equipment.

Compressing the sign information of discrete cosine transform (DCT) coefficients is an intractable problem in image coding schemes due to the equiprobable characteristics of the signs. To overcome this difficulty, we propose an efficient compression method for the sign information called “sign retrieval.” This method is inspired by phase retrieval, which is a classical signal restoration problem of finding the phase information of discrete Fourier transform coefficients from their magnitudes. The sign information of all DCT coefficients is excluded from a bitstream at the encoder and is complemented at the decoder through our sign retrieval method. We show through experiments that our method outperforms previous ones in terms of the bit amount for the signs and computation cost. Our method, implemented in Python language, is available from https://github.com/ctsutake/dsr.

In this paper, we propose a method for action representation learning from spatiotemporal signals of salient pixel-value changes and salient skeleton motion cues using both videos and skeleton sequences. The method simultaneously implements prediction of position relationships of movements with salient pixel-value changes using a vision transformer and multimodality-contrastive learning between representations respectively learned from videos and skeleton sequences. Our method is unsupervised and does not rely on semantic annotations to associate input data with actions. Instead of entire videos, sparse parts of videos are taken as training data, which are picked up according to probabilistic values of the size of pixel-value changes of movements. In experiments using supervised settings, our proposed network obtained remarkable generalization ability and higher accuracies. In experiments using unsupervised settings, our method achieved state-of-the-art performance. The experimental results demonstrate the superiority of the proposed method, which efficiently learns discriminative features.

High-gas-barrier layer deposition technology is very important for fabricating film-based organic light-emitting diode lighting. In this study, we fabricated high-quality water vapor barrier films using hexamethyldisiloxane, TG-41, or both as precursors. The barrier layer was deposited on polyethylene naphthalate or polyethylene terephthalate using roll-to-roll plasma-enhanced chemical vapor deposition. The barrier film fabricated using TG-41 as the precursor had high transparency. It is found that the stacking structure of layers with compositions close to SiO_x and carbon components remaining in SiO_x is important for depositing a barrier layer with good water vapor barrier properties using a roll-to-roll process.

This paper aims to QoE (Quality of Experience) enhancement of video and audio transmission over ICN (Information-Centric Networking)/ CCN (Content-Centric Networking). Each intermediate node can cache content in ICN/CCN. Then, cache decision policies, which decide whether the node cache chunks or not when receiving the chunks, have an important role. We therefore focus on a cache decision policy for QoE enhancement. We propose and evaluate a cache decision policy that combines the ideas of LCD (Leave Copy Down) and probabilistic caching, which does not require special resources or prior knowledge. We assess application-level QoS (Quality of Service) using a computer simulation with a tree network and QoE by means of a subjective experiment. We then show that the proposed policy can enhance QoE against conventional policies.

In photo-based line drawing rendering, existing algorithms often rely on edge information, leading to rendering that neglects the line density in real line drawings. This study proposes a Line Generative Adversarial Network (LineGAN) model to transform photos into manga-style line drawings by emphasizing line densities while minimizing the influence of edge information, resulting in more realistic line drawings. The LineGAN model coordinates global structure and local detail features, considering the spatial position and inter-channel contributions. This approach helps us to finely control the generation of lines, resulting in more artistic and expressive manga line effects. In addition, we collected an aligned dataset and developed two data-driven tools for creating interactive line drawings. Experiments have proven that LineGAN can produce superior manga line drawings compared to existing methods. Consequently, our model offers artists and designers an effective approach to craft high-quality manga-style line drawings.