Abstract The rapid evolution of augmented reality (AR) technology has presented new opportunities in the domain of education. Acting as a bridge between the virtual and real worlds, AR technology overcomes the physical limitations of our classrooms at a low cost and provides an interactive learning experience. In this study, we present a smartphone AR application, named the AR‐E‐Helper, which assists the learning of students in higher education lectures. Our goal is to provide an AR‐enhanced learning experience for students. To validate the effectiveness of the AR‐E‐Helper, we conducted an experiment that compares three classes: AR‐enhanced, smartphone‐enhanced, and nontechnology‐enhanced classes. Through the experiment, we observed that our application was helpful in maintaining student's focus in class, promoting their interest, and increasing their satisfaction. Furthermore, we also found how to improve our application based on the observations that the application brought some downsides to the learning activities. We expect that this study will be helpful to design AR learning tools in the future.

In this paper, we propose a three-dimensional (3D) convolutional neural network (CNN)-based method for predicting the degree of motion sickness induced by a 360° stereoscopic video. We consider the user's eye movement as a new feature, in addition to the motion velocity and depth features of a video used in previous work. For this purpose, we use saliency, optical flow, and disparity maps of an input video, which represent eye movement, velocity, and depth, respectively, as the input of the 3D CNN. To train our machine-learning model, we extend the dataset established in the previous work using two data augmentation techniques: frame shifting and pixel shifting. Consequently, our model can predict the degree of motion sickness more precisely than the previous method, and the results have a more similar correlation to the distribution of ground-truth sickness.

Most geographic maps visually represent physical distance; however, travel time can in some cases be more important than distance because it directly indicates availability. The technique of creating maps from temporal data is known as isochronal cartography, and is a form of distortion for clarification. In an isochronal map, congestion expands areas, while ideal travel conditions make the map shrink in comparison to the actual distance scale of a traditional map. Although there have been many applications of this technique, detailed user studies of its efficacy remain scarce, and there are conflicting views on its practical value. To attempt to settle this issue, we utilized a user-centered design process to determine which features of isochronal cartography might be most usable in practice. We developed an interactive cartographic visualization system, Traffigram, that features a novel combination of efficient isochronal map algorithms and an interface designed to give map users a quick and seamless experience while preserving geospatial integrity and aesthetics. We validated our design choices with multiple usability studies. We present our results and discuss implications for design.

We present a method for constructing 3D feature flow from video and its application to video stylization. Our method extracts smoothly aligned 3D vectors that describe the smallest variation of colors within a spatiotemporal video cube, and thus effectively preserves both spatial and temporal coherence in a relatively inexpensive manner. As an application of this flow field we present a particle-based video stylization technique to rerender the video in a feature enhancing, painterly style. Our method consists of per-pixel operations and is suitable for GPU implementation, which enables real-time video stylization.

Abstract We propose a fast and effective technique to improve sub‐grid visual details of the grid based fluid simulation. Our method procedurally synthesizes the flow fields coming from the incompressible Navier‐Stokes solver and the vorticity fields generated by vortex particle method for sub‐grid turbulence. We are able to efficiently animate smoke which is highly turbulent and swirling with small scale details. Since this technique does not solve the linear system in high‐resolution grids, it can perform fluid simulation more rapidly. We can easily estimate the influence of turbulent and swirling effect to the fluid flow.

Abstract A hidden‐picture puzzle contains objects hidden in a background image, in such a way that each object fits closely into a local region of the background. Our system converts image of the background and objects into line drawing, and then finds places in which to hide transformed versions of the objects using rotation‐invariant shape context matching. During the hiding process, each object is subjected to a slight deformation to enhance its similarity to the background. The results were assessed by a panel of puzzle‐solvers.

Abstract Developing suitable interpolation methods to simulate dynamic motions of continuous materials such as fluids is an important problem. In this paper, we propose a novel method to enforce the divergence condition to the interpolated velocity field by moving least squares (MLS), by means of the diffusive derivatives and moving divergence constraints that allow the practical use and easy implementation. As results, we present the velocity interpolation examples and a fluid‐like particle simulation method to show the meaningful potential of our method as a tool of physical interpolation for fluid simulations. Copyright © 2008 John Wiley & Sons, Ltd.

We propose a hybrid method for simulating multiphase fluids such as bubbly water. The appearance of subgrid visual details is improved by incorporating a new bubble model based on smoothed particle hydrodynamics (SPH) into an Eulerian grid-based simulation that handles background flows of large bodies of water and air. To overcome the difficulty in simulating small bubbles in the context of the multiphase flows on a coarse grid, we heuristically model the interphase properties of water and air by means of the interactions between bubble particles. As a result, we can animate lively motion of bubbly water with small scale details efficiently.

Abstract Noise is used to create realistic animations that look like natural phenomena as well as procedural textures and shapes by adding randomness to graphical applications. In this paper, we suggest a method to edit noise values to satisfy the constraints that reflect the user's demands while maintaining the inherent statistical features of the noise function. Noise editing uses optimization to minimize the difference between the statistical characteristics of the ideal and edited versions of a noise source. Using our editing method, detailed control of animation and shape data that include noise is possible. Copyright © 2004 John Wiley & Sons, Ltd.