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Abstract: In this paper, we first present a new audience-participating movie form in which 3D virtual characters of audiences are constructed by computer graphics (CG) technologies and are embedded into a in a pre-rendered movie as different roles. Then, we investigate how the audiences respond to these virtual characters using physiological and subjective evaluation methods. To facilitate the investigation, we present three versions of a movie to an audience—a Traditional version, its SDIM version with the participation of the audience’s virtual character, and its SFDIM version with the co-participation of the audience and her/his friends’ virtual characters. The subjective evaluation results show that the participation of virtual characters indeed causes increased subjective sense of spatial presence and engagement, and emotional reaction; moreover, SFDIM performs significantly better than SDIM, due to the co-participation of friends’ virtual characters. Also, we find that the audiences experience not only significantly different galvanic skin response (GSR) changes on average—changing trend over time and number of fluctuations—but they also show the increased phasic GSR responses to the appearance of their own or friends’ virtual 3D characters on the screen. The evaluation results demonstrate the success of the new audience-participating movie form and contribute to understanding how people respond to virtual characters in a role-playing entertainment interface. [Copyright &y& Elsevier]

Faces are very familiar to everyone and convey various information, including information that is specific to the individual and information that is part of mutual communication. Usually verbal media is not able to describe such information appropriately. Recently, detailed studies on facial information processing by computer have been carried out in the engineering field for application to communication media and human interfaces. Two main topics are recognition of human faces and synthesis of facial images. The objective of the former is to enable computers to recognize human faces and that of the latter is to provide a natural and impressive interface in the form of a “face” for communication media. These technologies have also been found to be useful in various fields related to the face, such as psychology, anthropology, cosmetology, and dentistry. Although most of the studies in these fields have been carried out independently, the above technologies provide for a common study tool among them. This paper focuses on processing facial information by computer. First, recent research trends on the synthesis of facial images and recognition of facial expressions are outlined. After considering the various characteristics of the face, the engineering applications of facial information are discussed from two standpoints: the support of face-to-face communication between humans, and communication between human and machine using facial information. The tools and databases used in studying facial information processing and some related topics are also described. © 1998 Scripta Technica, Electron Comm Jpn Pt 3, 81(10): 36–57, 1998 [ABSTRACT FROM AUTHOR]

Screen-space subsurface scattering is currently the most common approach to represent translucent materials in real-time rendering. However, most of the current approaches approximate the diffuse reflectance profile of translucent materials as a symmetric function, whereas the profile has an asymmetric shape in nature. To address this problem, we propose LinSSS, a numerical representation of heterogeneous subsurface scattering for real-time screen-space rendering. Although our representation is built upon a previous method, it makes two contributions. First, LinSSS formulates the diffuse reflectance profile as a linear combination of radially symmetric Gaussian functions. Nevertheless, it can also represent the spatial variation and the radial asymmetry of the profile. Second, since LinSSS is formulated using only the Gaussian functions, the convolution of the diffuse reflectance profile can be efficiently calculated in screen space. To further improve the efficiency, we deform the rendering equation obtained using LinSSS by factoring common convolution terms and approximate the convolution processes using a MIP map. Consequently, our method works as fast as the state-of-the-art method, while our method successfully represents the heterogeneity of scattering. [ABSTRACT FROM AUTHOR]

Indirect illumination involving with visually rich participating media such as turbulent smoke and loud explosions contributes significantly to the appearances of other objects in a rendering scene. However, previous real‐time techniques have focused only on the appearances of the media directly visible from the viewer. Specifically, appearances that can be indirectly seen over reflective surfaces have not attracted much attention. In this paper, we present a real‐time rendering technique for such indirect views that involves the participating media. To achieve real‐time performance for computing indirect views, we leverage layered polygonal area lights (LPALs) that can be obtained by slicing the media into multiple flat layers. Using this representation, radiance entering each surface point from each slice of the volume is analytically evaluated to achieve instant calculation. The analytic solution can be derived for standard bidirectional reflectance distribution functions (BRDFs) based on the microfacet theory. Accordingly, our method is sufficiently robust to work on surfaces with arbitrary shapes and roughness values. In addition, we propose a quadrature method for more accurate rendering of scenes with dense volumes, and a transformation of the domain of volumes to simplify the calculation and implementation of the proposed method. By taking advantage of these computation techniques, the proposed method achieves real‐time rendering of indirect illumination for emissive volumes. [ABSTRACT FROM AUTHOR]

3D car models are heavily used in computer games, visual effects, and even automotive designs. As a result, producing such models with minimal labour costs is increasingly more important. To tackle the challenge, we propose a novel system to reconstruct a 3D car using a single sketch image. The system learns from a synthetic database of 3D car models and their corresponding 2D contour sketches and segmentation masks, allowing effective training with minimal data collection cost. The core of the system is a machine learning pipeline that combines the use of a generative adversarial network (GAN) and lazy learning. GAN, being a deep learning method, is capable of modelling complicated data distributions, enabling the effective modelling of a large variety of cars. Its major weakness is that as a global method, modelling the fine details in the local region is challenging. Lazy learning works well to preserve local features by generating a local subspace with relevant data samples. We demonstrate that the combined use of GAN and lazy learning produces is able to produce high-quality results, in which different types of cars with complicated local features can be generated effectively with a single sketch. Our method outperforms existing ones using other machine learning structures such as the variational autoencoder. [ABSTRACT FROM AUTHOR]

This paper describes a deep learning-based method for long-term video interpolation that generates intermediate frames between two music performance videos of a person playing a specific instrument. Recent advances in deep learning techniques have successfully generated realistic images with high-fidelity and high-resolution in short-term video interpolation. However, there is still room for improvement in long-term video interpolation due to lack of resolution and temporal consistency of the generated video. Particularly in music performance videos, the music and human performance motion need to be synchronized. We solved these problems by using human poses and music features essential for music performance in long-term video interpolation. By closely matching human poses with music and videos, it is possible to generate intermediate frames that synchronize with the music. Specifically, we obtain the human poses of the last frame of the first video and the first frame of the second video in the performance videos to be interpolated as key poses. Then, our encoder–decoder network estimates the human poses in the intermediate frames from the obtained key poses, with the music features as the condition. In order to construct an end-to-end network, we utilize a differentiable network that transforms the estimated human poses in vector form into the human pose in image form, such as human stick figures. Finally, a video-to-video synthesis network uses the stick figures to generate intermediate frames between two music performance videos. We found that the generated performance videos were of higher quality than the baseline method through quantitative experiments. [ABSTRACT FROM AUTHOR]

The realization of an anthropomorphic agent which looks like a real human is an important research topic for the broadening of the range of human-to-human communications through the use of a computer. We have proposed a technique for synthesizing natural talking-face animation that permits such communications. How to evaluate the performance of talking-face animation, however, has remained an outstanding issue. The performance of talking-face animation is determined in three parameters: (1) Does it reproduce human talking to an extent that permits lipreading? (2) Does it appear visually natural? (3) Is it accurately synchronized with voice? In this paper, we first presented talking-face animation along with the voice to subjects and conducted experiments on how well the subjects heard the contents of the spoken words to examine Parameter (1). In the next step, with regard to Parameter (2), the visual naturalness of the talking-face animation and the smoothness of the motion of the talking mouth were evaluated on a scale of 5 points. Lastly, with regard to Parameter (3), talking-face animation in which the synchronization of the animation with sound was off by a fixed interval was shown to subjects to investigate the subjective perception of the synchronization gap, and the extent of the resulting strange feeling was evaluated on a scale of 5 points. In addition, the effect of the synchronization gap between voice and talking-face animation on the manner in which the spoken words are understood was also evaluated. Through these evaluation experiments, the quality of synthetic talking-face animation proposed by the authors was evaluated, and we studied naturally-appearing synchronization between synthetic talking-face animation and voice. © 2006 Wiley Periodicals, Inc. Electron Comm Jpn Pt 3, 89(5): 39–52, 2006; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ecjc.20180 [ABSTRACT FROM AUTHOR]

We present a novel concept audio–visual object removal in 360-degree videos, in which a target object in a 360-degree video is removed in both the visual and auditory domains synchronously. Previous methods have solely focused on the visual aspect of object removal using video inpainting techniques, resulting in videos with unreasonable remaining sounds corresponding to the removed objects. We propose a solution which incorporates direction acquired during the video inpainting process into the audio removal process. More specifically, our method identifies the sound corresponding to the visually tracked target object and then synthesizes a three-dimensional sound field by subtracting the identified sound from the input 360-degree video. We conducted a user study showing that our multi-modal object removal supporting both visual and auditory domains could significantly improve the virtual reality experience, and our method could generate sufficiently synchronous, natural and satisfactory 360-degree videos. [ABSTRACT FROM AUTHOR]

Subsurface scattering involves the complicated behavior of light beneath the surfaces of translucent objects that includes scattering and absorption inside the object's volume. Physically accurate numerical representation of subsurface scattering requires a large number of parameters because of the complex nature of this phenomenon. The large amount of data restricts the use of the data on memory-limited devices such as video game consoles and mobile phones. To address this problem, this paper proposes an efficient data compression method for heterogeneous subsurface scattering. The key insight of this study is that heterogeneous materials often comprise a limited number of base materials, and the size of the subsurface scattering data can be significantly reduced by parameterizing only a few base materials. In the proposed compression method, we represent the scattering property of a base material using a function referred to as the base scattering profile. A small subset of the base materials is assigned to each surface position, and the local scattering property near the position is described using a linear combination of the base scattering profiles in the log scale. The proposed method reduces the data by a factor of approximately 30 compared to a state-of-the-art method, without significant loss of visual quality in the rendered graphics. In addition, the compressed data can also be used as bidirectional scattering surface reflectance distribution functions (BSSRDF) without incurring much computational overhead. These practical aspects of the proposed method also facilitate the use of higher-resolution BSSRDFs in devices with large memory capacity. [ABSTRACT FROM AUTHOR]

Due to the recent advancement of computer graphics hardware and software algorithms, deformable characters have become more and more popular in real-time applications such as computer games. While there are mature techniques to generate primary deformation from skeletal movement, simulating realistic and stable secondary deformation such as jiggling of fats remains challenging. On one hand, traditional volumetric approaches such as the finite element method require higher computational cost and are infeasible for limited hardware such as game consoles. On the other hand, while shape matching based simulations can produce plausible deformation in real-time, they suffer from a stiffness problem in which particles either show unrealistic deformation due to high gains, or cannot catch up with the body movement. In this paper, we propose a unified multi-layer lattice model to simulate the primary and secondary deformation of skeleton-driven characters. The core idea is to voxelize the input character mesh into multiple anatomical layers including the bone, muscle, fat and skin. Primary deformation is applied on the bone voxels with lattice-based skinning. The movement of these voxels is propagated to other voxel layers using lattice shape matching simulation, creating a natural secondary deformation. Our multi-layer lattice framework can produce simulation quality comparable to those from other volumetric approaches with a significantly smaller computational cost. It is best to be applied in real-time applications such as console games or interactive animation creation. [ABSTRACT FROM AUTHOR]