[Social Allostasis Regulation by Robots].

Social allostasis, the process by which social interactions dynamically regulate psychophysiological states (e.g., emotions), is attracting attention. Social allostasis can significantly impact people's mental and physical wellbeing. However, adaptive social relationships are not necessarily available to all people. The use of robots is expected to solve this problem. In this paper, we present three studies of our group that prove the influence of social interactions with robots on human psychophysiological states. Our results showed that robots could amplify human subjective and physiological emotional responses through conversation, touch, and television co-viewing experiences. These results suggest that robots may be helpful for adaptive social allostasis regulation.

Systematic Review of Augmented Reality Training Systems.

Recent augmented reality (AR) advancements have enabled the development of effective training systems, especially in the medical, rehabilitation, and industrial fields. However, it is unclear from the literature what the intrinsic value of AR to training is and how it differs across multiple application fields. In this work, we gathered and reviewed the prototypes and applications geared towards training the intended user's knowledge, skills, and abilities. Specifically, from IEEE Xplore plus other digital libraries, we collected 64 research papers present in high-impact publications about augmented reality training systems (ARTS). All 64 papers were then categorized according to the training method used, and each paper's evaluations were identified by validity. The summary of the results shows trends in the training methods and evaluations that incorporate ARTS in each field. The narrative synthesis illustrates the different implementations of AR for each of the training methods. In addition, examples of the different evaluation types of the current ARTS are described for each of the aforementioned training methods. We also investigated the different training strategies used by the prevailing ARTS. The insights gleaned from this review can suggest standards for designing ARTS regarding training strategy, and recommendations are provided for the implementation and evaluation of future ARTS.

Cross-talk elimination for lenslet array near eye display based on eye-gaze tracking.

Lenslet array (LA) near-eye displays (NEDs) are a recent technical development that creates a virtual image in the field of view of one or both eyes. A problem occurs when the user's pupil moves out of the LA-NED eye box (i.e., cross-talk) making the image look doubled or ghosted. It negatively impacts the user experience. Although eye-gaze tracking can mitigate this problem, the effect of the solution has not been studied to understand the impact of pupil size and human perception. In this paper, we redefine the cross-talk region as the practical pupil movable region (PPMR50), which differs from eye box size because it considers pupil size and human visual perception. To evaluate the effect of eye-gaze tracking on subjective image quality, three user studies were conducted. From the results, PPMR50 was found to be consistent with human perception, and cross-talk elimination via eye-gaze tracking was better understood in a static gaze scenario. Although the system latency prevented the complete elimination of cross-talk for fast movements or large pupil changes, the problem was greatly alleviated. We also analyzed system delays based on PPMR50, which we newly defined in this paper and provided an optimization scheme to meet the maximum eyeball rotation speed.

Robot touch with speech boosts positive emotions.

A gentle touch is an essential part of human interaction that produces a positive care effect. Previously, robotics studies have shown that robots can reproduce a gentle touch that elicits similar, positive emotional responses in humans. However, whether the positive emotional effects of a robot's touch combined with speech can be enhanced using a multimodal approach remains unclear. This study supports the hypothesis that a multimodal interaction combining gentle touch and speech by a robot enhances positive emotional responses. Here, we conducted an experiment using a robotic arm to perform a gentle touch combined with speech and compared three conditions: touch alone, speech alone, and touch with speech. We assessed participants' subjective ratings of valence, arousal, and human likeliness using subjective emotional responses. Furthermore, we recorded facial electromyography (EMG) from the corrugator supercilii and zygomaticus major muscles and measured skin conductance levels (SCLs) as physiological emotional responses. Our results show that touch combined with speech elicited higher subjective valence and arousal ratings, stronger zygomaticus major EMG and SCL activities than touch alone. The results suggest that the positive emotional effects of robotic touch can be boosted by combining elements of speech.

DFusion: Denoised TSDF Fusion of Multiple Depth Maps with Sensor Pose Noises.

The truncated signed distance function (TSDF) fusion is one of the key operations in the 3D reconstruction process. However, existing TSDF fusion methods usually suffer from the inevitable sensor noises. In this paper, we propose a new TSDF fusion network, named DFusion, to minimize the influences from the two most common sensor noises, i.e., depth noises and pose noises. To the best of our knowledge, this is the first depth fusion for resolving both depth noises and pose noises. DFusion consists of a fusion module, which fuses depth maps together and generates a TSDF volume, as well as the following denoising module, which takes the TSDF volume as the input and removes both depth noises and pose noises. To utilize the 3D structural information of the TSDF volume, 3D convolutional layers are used in the encoder and decoder parts of the denoising module. In addition, a specially-designed loss function is adopted to improve the fusion performance in object and surface regions. The experiments are conducted on a synthetic dataset as well as a real-scene dataset. The results prove that our method outperforms existing methods.

Surface Remeshing: A Systematic Literature Review of Methods and Research Directions.

Triangle meshes are used in many important shape-related applications including geometric modeling, animation production, system simulation, and visualization. However, these meshes are typically generated in raw form with several defects and poor-quality elements, obstructing them from practical application. Over the past decades, different surface remeshing techniques have been presented to improve these poor-quality meshes prior to the downstream utilization. A typical surface remeshing algorithm converts an input mesh into a higher quality mesh with consideration of given quality requirements as well as an acceptable approximation to the input mesh. In recent years, surface remeshing has gained significant attention from researchers and engineers, and several remeshing algorithms have been proposed. However, there has been no survey article on remeshing methods in general with a defined search strategy and article selection mechanism covering the recent approaches in surface remeshing domain with a good connection to classical approaches. In this article, we present a survey on surface remeshing techniques, classifying all collected articles in different categories and analyzing specific methods with their advantages, disadvantages, and possible future improvements. Following the systematic literature review methodology, we define step-by-step guidelines throughout the review process, including search strategy, literature inclusion/exclusion criteria, article quality assessment, and data extraction. With the aim of literature collection and classification based on data extraction, we summarized collected articles, considering the key remeshing objectives, the way the mesh quality is defined and improved, and the way their techniques are compared with other previous methods. Remeshing objectives are described by angle range control, feature preservation, error control, valence optimization, and remeshing compatibility. The metrics used in the literature for the evaluation of surface remeshing algorithms are discussed. Meshing techniques are compared with other related methods via a comprehensive table with indices of the method name, the remeshing challenge met and solved, the category the method belongs to, and the year of publication. We expect this survey to be a practical reference for surface remeshing in terms of literature classification, method analysis, and future prospects.

Positive Emotion Amplification by Representing Excitement Scene with TV Chat Agents.

This paper proposes emotion amplification for TV chat agents allowing users to get more excited in TV sports programs, and a model that estimates the excitement level of TV programs based on the number of social comment posts. The proposed model extracts the exciting intervals from social comments to the program scenes. By synchronizing recorded video streams and the intervals, the agents may talk with the user dynamically changing the frequency and volume of upbeat utterances, increasing the excitement of the user. To test these agents, participants watched TV content under three conditions: without an agent, with four agents that utter with a flat voice, and with four agents with emotion amplification. Results from 24 young adult Japanese individuals showed that their arousal of participants' subjective and physiological emotional responses were boosted because of the agents, enhancing their motivation to interact with the agent in the future. With empirical evidence, this paper supports these expectations and demonstrates that these agents can amplify the positive emotions of TV watchers, enhancing their motivation to interact with the agent in the future.