In this paper, we designed the augmented reality (AR) -based visualization of metaphor that instructors in an Aikido community of practice use in everyday teaching to explain techniques. We deployed these AR-based visual metaphors in regular Aikido club training over a two-month period and examined their use through ethnographic observations and interviews. Our findings reveal three key points. First, instructors felt AR metaphors reduced misunderstandings and stress, although using metaphors created by others diminished agency unless they incorporated their own interpretations. Second, learners grasped successful techniques more quickly, increasing motivation, yet some felt anxious about teaching others later because they had not reasoned through the mechanics. Third, AR metaphors strengthened ties to the originating instructor while weakening connections with on-site members. Based on these findings, we present three design takeaways for deploying AR-based visual metaphors into communities of practice in the real-world.

Everyday tasks like hand-washing and tea-making require people to steer their hands to use tools, navigating their hands to reach targets while avoiding hazards. Hand-steering becomes challenging when one cannot visually recognize if their hand is approaching the target and is away from hazards. Currently, no practical technological solutions support blind and low-vision (BLV) individuals’ hand-steering. We designed and developed two auditory hand steering guidance methods: VERBAL and Follow-Your-Finger (FYF). VERBAL uses spoken directional instructions, while FYF uses sonification to guide hand-steering. We conducted a user study with 12 BLV participants to evaluate the feasibility of the methods in supporting hand-steering. VERBAL lacked precision, 24.6% error rate for one of the easiest conditions, but FYF showed promise, achieving 4.17% error rate for the same condition. Among the six participants who preferred FYF, the error rate was 1.39%. The results demonstrate the feasibility of auditory hand steering guidance for BLV individuals.

Understanding the social effects induced by the ambient observation of a robot is essential for their successful integration into human environments. This study explores the influence of eye-related design factors of robots on human perceptions associated with social facilitation. We conducted an online experiment to test the hypothesis that visual and behavioral features of the eyes of a robot influence the feeling of being watched and perceived agency, which together shape public self-awareness. Using a 2 × 3 ×2 ×2 between-subjects design, we manipulated four eye-related factors in a virtual robot: visual realism, size, gaze cue, and blinking. Our analysis revealed that, contrary to our expectations, visual realism and size did not influence the feeling of being watched. However, gaze cue positively affected perceived agency while blinking enhanced it. Perceived agency, in turn, emerged as a significant predictor of public self-awareness. The structural model highlighted a significant relationship: perceived agency enhances the feeling of being watched. These findings suggest that perceived agency mediates the relationship between robotic eye behaviors and public self-awareness. This study provides foundational insights for designing social robots to enhance human experiences in shared spaces.

Differences in text perception among users of diverse language backgrounds may be accentuated in immersive environments. To investigate this, we measured preferred perceptual viewing distances in virtual reality (VR) as a function of language familiarity, glyph complexity, font weight and font type. 30 native readers each of Chinese, English, and Japanese adjusted text panels—initially placed at 0.5 m, 2.5 m, 5 m, and 10 m—to the distance they perceived as most appropriate for reading. Stimuli varied in visual complexity (simple vs. complex characters or words) and in font style (serif vs. sans-serif, light vs. bold). Our results show that at the farthest distances, native English and Japanese readers positioned text significantly farther away than non-natives, indicating a top-down perceptual compensation effect; this advantage was not observed for native Chinese participants. Moreover, at the closest distances, native English readers also required slightly farther viewing distances across all language conditions. Across all groups, simple glyphs and bold fonts supported greater perceptual distances, whereas complex glyphs and light fonts required closer viewing. These findings suggests that how language background and font variables shape text perception in VR and provide a theoretical basis for adaptive rendering to optimize display parameters for diverse user populations.

Online music videos on video-sharing platforms offer video comments that viewers can read to enjoy their social-viewing experience. However, because these comments rely on visual elements through texts, they are not accessible to eyes-free listeners, such as those who listen to music videos while jogging, commuting, or showering. To address this gap, we explore Auditory Comment Display (ACD), which offers text comments via text-to-speech (TTS) synthesis, enabling eyes-free listeners to enjoy a social-viewing experience while listening to music videos. We used music concert videos as example content and prototyped varying comment-to-speech styles in this context. We conducted a formative study (N = 8), prototyping (N = 10), and a user study (N = 12). The results indicated that ACD enhanced eyes-free listeners' social-viewing experience, although it may not be appropriate for specific situations and users. We discuss the design implications and future directions for the eyes-free social-viewing experience via comment-to-speech synthesis.

While children with disabilities often face barriers to play including reduced time, exclusion, and ill-suited toys, impacting their development, social robots provide the potential to help: they can motivate children, increase task engagement, and facilitate social interactions. However, social robots (and technological interventions in general) struggle to be adopted into regular use within homes by families, commonly being abandoned after a short time. Rather than focusing on the utility of these interventions, we instead look how they integrate into family needs and lifestyles. We designed and conducted a study where we engaged children living with disabilities and their families, using interactions with real robots and exploratory exercises, to learn about their perspectives, needs, and concerns regarding adopting a social companion robot in their home. We analyzed participant task engagement and feedback from the perspective of supporting play for children with disabilities and presented resulting design recommendations for addressing primary concerns and matching key expectations, and to support adoption pathways to improve the chances of success.

Eyes have been widely found to play an important role in communicating emotions and intentions for social robots. However, when introducing robots with eyes into people’s personal living spaces, it is necessary to consider how the social aspects of a robot impact perceptions of privacy. Specifically, in this paper we explored how the design of a robot’s eyes and eye-use behavior impacts use perception of privacy and related concerns. We developed a prototype robot with display-based eyes and investigated the impacts on perceptions of privacy concerns living with the robot. Our findings indicated that robot eye design does impact perceptions of privacy concerns, with the unexpected result of robots whose eyes that stay always on garnering lower concerns than eyes that close or turn off (the display) just before a person leaves. This result offer valuable insights for robot development and present empirical evidence on the influence of robot eye design on user privacy concerns.

The maximum physical range of horizontal human eye movement is approximately 45°. However, in a natural gaze shift, the difference in the direction of the gaze relative to the frontal direction of the head rarely exceeds 25°. We name this region of 25° − 45° the “Kuiper Belt” in the eye-gaze interaction. We try to utilize this region to solve the Midas touch problem to enable a search task while reducing false input in the Virtual Reality environment. In this work, we conduct two studies to figure out the design principle of how we place menu items in the Kuiper Belt as an “out-of-natural angle” region of the eye-gaze movement, and determine the effectiveness and workload of the Kuiper Belt-based method. The results indicate that the Kuiper Belt-based method facilitated the visual search task while reducing false input. Finally, we present example applications utilizing the findings of these studies.

“Angels and Devils” express a human’s dilemma. In this paper, we produced this expression with multiple robots and investigated how humans change their decision and behavior in a moral dilemma environment. We divided the participants into Neutral-Neutral and Angel-Devil robot groups and investigated the willpower of the two groups by the alphabet writing task. We also examined the impression of the robots by Godspeed questionnaires and the results of the questionnaire.

Emotional expressions are essential in augmenting a robot’s expression. Many robots with limited facial expression freedom, such as the Nao robot, can effectively express emotions using body movement. Previous studies have used a single robot and evaluated its expression. Multiple robots expressing emotion in their interactions may have a greater impact than robots expressing emotion only when interacting with humans. The relationships between these robots should allow them to develop more diverse modes of expression. However, it is unclear how people perceive relationships by observing robots’ emotional expressions. In this study, we applied every combination of four characteristic body emotion expressions (Sadness, Fear, Pride, and Happiness) based on Russell’s circumplex model to robots. Furthermore, we investigated how the relationships were evaluated in an online video-based experiment. The results show that the relationships between the two robots are influenced by each robot’s body emotional movement and can be interpreted using the valence-arousal model.

“Angel and Devil” expression has been used to cause a dilemma in various animations and comics. In this video demo, we implemented this expression with multiple robots. We supposed a scene in daily life, a student carrying a backpack and two robots riding on both shoulders to encourage the student to make decisions. This research concept can be the novelty use case of personal AI robots. In future works, the decision-making methodologies suggested by behavioral economics, such as nudging and boosting, can adopt to human-robot interaction by using multiple robots.

A variety of chatbots were developed to elicit people’s emotional responses and manage the emotions of people. These chatbots often use text-based emotional sentences. However, there are few studies that chatbots use extremely simplified communications to induce some emotional responses. We investigated the effect of mood contagion and tried to induce positive or negative words from people on our web-based ”word chain game” system as the most simplified conversational style. We also defined the system’s emotion as making the system use words that have polarity, which means each word’s strength of positive or negative emotion. The result shows that users of the system using positive words were slightly influenced to use more positive words than the neutral or negative system.

This paper presents a method to track two magnets using one magnetometer on a smart device (e.g., smartphone), which detects the locations of the magnets around the device. A magnetometer measures the overlapping data signals generated by the two magnets. Thus, a data-separation technique is required to separately track the continuous and simultaneous signals generated by the two magnets. In this study, we develop a separation algorithm based on nonnegative matrix factorization to continuously and simultaneously track two magnets, and then conduct an experiment to validate our concept. We then compare our method in both simulated and actual environments. In the actual environment, we observe real data signals arising from the two magnets on a magnetometer. Finally, we present example applications to demonstrate the use cases of our model in human–computer interaction systems.

We conducted two studies exploring how an area cursor technique can improve the eye-gaze interface. We first examined the bubble cursor technique. We developed an eye-gaze-based cursor called the bubble gaze cursor and compared it to a standard eye-gaze interface and a bubble cursor with a mouse. The results revealed that the bubble gaze cursor interface was faster than the standard point cursor-based eye-gaze interface. In addition, the usability and mental workload were significantly better than those of the standard interface. Next, we extended the bubble gaze cursor technique and developed a bubble gaze lens. The results indicated that the bubble gaze lens technique was faster than the bubble gaze cursor method and the error rate was reduced by 54.0%. The usability and mental workload were also considerably better than those of the bubble gaze cursor.

In sports, studies commonly use agents as coaches or partners for motivation. However, despite the proven positive effect of cheering on athletes? mental state in the field of sports psychology, no studies have examined the effects of agent-based motivation. Hence, we created three scenarios: computer graphics animation (CG) and voice agent cheering,voice agent cheering, and no cheering and conducted experiments under their conditions. The experiment questionnaire results showed that ?CG and voice agent cheering? was more effective in novice participants than no cheering, confirming the former's positive effect on motivation.

We propose the use of face-related gestures involving the movement of the face, eyes, and head for augmented reality (AR). This technique allows us to use computer systems via hands-free, discreet interactions. In this paper, we present an elicitation study to explore the proper use of facial gestures for daily tasks in the context of a smart home. We used Amazon Mechanical Turk to conduct this study (N=37). Based on the proposed gestures, we report usage scenarios and complexity, proposed associations between gestures/tasks, a user-defined gesture set, and insights from the participants. We also conducted a technical feasibility study (N=13) with participants using smart eyewear to consider their uses in daily life. The device has 16 optical sensors and an inertial measurement unit (IMU). We can potentially integrate the system into optical see-through displays or other smart glasses. The results demonstrate that the device can detect eight temporal face-related gestures with a mean F1 score of 0.911 using a convolutional neural network (CNN). We also report the results of user-independent training and a one-hour recording of the experimenter testing two of the gestures.

In this research, we present a cushion interface for operating smart home applications. We developed a gesture recognition system using convolutional neural networks and embedded the acceleration sensor arrays in the cushion cover. To evaluate the system, we conducted experiments and measured recognition accuracy.

The way a smart house system interacts with the user could limit the full potential a smart house is capable to provide, and an agent-mediated interface has been proved to broaden users' mental models. We designed four different conceptual smart house interfaces and surveyed to find out what kind of agent interface is desired under a wide variety of smart house needs.

As voice recognition technology develops, we talk to smart speakers and other voice assistants more and more frequently in everyday life. Many such speech dialog systems are designed to use honorifics. However, humans do not always use honorifics in everyday conversation. Thus, we consider that voice assistants need to use other forms of expression in addition to so-called polite language. In this study, we conducted a comparative experiment to investigate how the speaking styles of smart speakers affect human listeners. In this experiment, a participant talked to a smart speaker to make travel plans. We analyzed the results of questionnaires. We found that a smart speaker's friendly speaking style influenced the participants' impressions and thus shaped the development of good relationships between humans and agents. Our findings indicate that people regard agents as friends if they speak in a friendly manner.

In recent years, social listening data analysis is adopted in various business areas as a measure to analyze customers’ voices. While sentiment information systems in social listening data analysis have been highly developed, their verification data requires sentiment score by humans. Sentiment means emotions such as Joy, anger and so on. Sentiment score by humans, however, depends on individuals and is not consistent enough. Thus, the accuracy of evaluation is uncertain. If verification data has uncertainty, it is apparent that uncertainty also occurs in the verification of systems. It is therefore important to exclude the uncertainty of verification data as much as possible. In this paper, we studied a standardization method for reducing such uncertainty and its effect. We set three choices, “Positive,” “Negative,” and “Not Sure,” for the verification data used in this study, and sentiment score evaluated the data as social listening data. We first showed an example of uncertainty in the verification data. We then proposed a correction method for reducing uncertainty in the verification data. The method adopted correction formulas using the average sentiment score of all the subjects as the norm. We used these formulas to suppress the bias of sentiment score of each individual subject. Consequently, compared with the result processed by simple decision by a majority, the frequency of “Not Sure” and the amount of mixed data of different sentiment scores decreased. Namely the method was effective in reducing the discarded data of indecisive sentiment score. Furthermore, the variance of data decreased consequently. These results showed that the standardization method was effective in reducing uncertainty in verification data.

In recent years, plagiarism that uses the sentences or phrases of others without permission has become a social problem. It is widely spread from very familiar student reports to novels and worldwide academic papers. In this paper, we deal with plagiarism in student reports, and explain the plagiarism patterns often found there. Then we propose a method to detect them efficiently and accurately. This method is based on the way of making two texts to be compared with into one-dimension string respectively, repeating shift and mutual comparison, and checking the matching section of words. This method can accurately detect perfect matches of any size, regardless of its placement in the text. To this basic detection method, we combine some heuristics which are estimation of detection possibility and compression of strings, to improve both detection accuracy of the plagiarism sections and the reduction of calculation time, and propose it as a plagiarism detection method. This method has only one parameter for plagiarism judgement, and it is also intuitive and easy to set. Finally, we show the effectiveness of the proposed method, especially the introduced heuristics, using real data.

We present an indoor navigation system, SCAN, which displays the user's current location on a user-scanned indoor map. Smartphones use the global positioning system (GPS) to determine their position on the earth, but it does not work in interior environments. SCAN uses indoor map images scanned by a smartphone camera and displays the user's position on the indoor map while they move around a floor. It tracks the user's position using an inertial measurement unit (IMU) on the smartphone. Camera calibration is required for precise navigation, but our system estimates the user's position based on a single landscape image. Results of our preliminary user study suggest that participants' experiences were similar to using outdoor GPS navigation systems.

We present an interactive 360-degree tabletop display system for collaborative work around a round table. Users are able to see 3D objects on the tabletop display anywhere around the table without 3D glasses. The system uses a visual perceptual mechanism for smooth motion parallax in the horizontal direction with fewer projectors than previous works. A 360-degree camera mounted above the table and image recognition software detects users' positions around the table and the heights of their faces (eyes) as they move around the table in real-time. Those mechanics help display correct vertical and horizontal direction motion parallax for different users simultaneously. Our system also has a user interaction function with a tablet device that manipulates 3D objects displayed on the table. These functions support collaborative work and communication between users. We implemented a prototype system and demonstrated the collaborative features of the 360-degree tabletop display system.

In recent years, data on SNS has been gathered and utilized for various marketing activities such as advertisement publicity activities, product planning, etc., are being implemented in many companies. When collecting data, it is common to set conditions such as collection period, language, sending country, and keywords. However, it is often necessary to confront a huge amount of data. Furthermore, it is usual that the collected data contains a large amount of unnecessary noise. Therefore, appropriate classification / extraction work is required in order to reach useful information and hot topics. But the operation is not always easy for everyone; hence we aimed to make everyone easily reach them. This system focuses on "sentiment" that many users are interested in. First, collect data such as posted sentences, extract sentiment (such as good, bad, praise and criticism) in them, and store in the database together with the original ones. This operation is automatically executed. Then, it is surveyed what kind of sentiment is included in a target topic, or conversely, what topic has relationship with a certain sentiment. This system searches information from the previously explained database, and aggregates and visualizes it. This operation is executed based on user’s input. These functions help us to discover hot topics in SNS from various perspectives because the operation is easy for everyone. In this paper, we explain the function, configuration and usage of this developed system.

The study of demand forecasting for automobile has been tried for a long time. The demand forecasting for automobile is a quite important matter for business profit point of view. In this report, we show a new forecasting approach to understand the trend of automobile market.

We present the MyoTilt target selection method for smartwatches, which employs a combination of a tilt operation and electromyography (EMG). First, a user tilts his/her arm to indicate the direction of cursor movement on the smartwatch; then s/he applies forces on the arm. EMG senses the force and moves the cursor to the direction where the user is tilting his/her arm to manipulate the cursor. In this way, the user can simply manipulate the cursor on the smartwatch with minimal effort, by tiling the arm and applying force to it. We conducted an experiment to investigate its performance and to understand its usability. Result showed that participants selected small targets with an accuracy greater than 93.89%. In addition, performance significantly improved compared to previous tilting operation methods. Likewise, its accuracy was stable as targets became smaller, indicating that the method is unaffected by the "fat finger problem".

We present new alternative interfaces for zooming out on a mobile device: Bounce Back and Force Zoom. These interfaces are designed to be used with a single hand. They use a pressure-sensitive multitouch technology in which the pressure itself is used to zoom. Bounce Back senses the intensity of pressure while the user is pressing down on the display. When the user releases his or her finger, the view is bounced back to zoom out. Force Zoom also senses the intensity of pressure, and the zoom level is associated with this intensity. When the user presses down on the display, the view is scaled back according to the intensity of the pressure. We conducted a user study to investigate the efficiency and usability of our interfaces by comparing with previous pressure-sensitive zooming interface and Google Maps zooming interface as a baseline. Results showed that Bounce Back and Force Zoom was evaluated as significantly superior to that of previous research; number of operations was significantly lower than default mobile Google Maps interface and previous research.

Self-driving technologies have been increasingly developed and tested in recent years (e.g., Volvo's and Google's self-driving cars). However, only a limited number of investigations have so far been conducted into communication between self-driving cars and pedestrians. For example, when a pedestrian is about to cross a street, that pedestrian needs to know the intension of the approaching self-driving car. In the present study, we designed a novel interface known as "Eyes on a Car" to address this problem. We added eyes onto a car so as to establish eye contact communication between that car and pedestrians. The car looks at the pedestrian in order to indicate its intention to stop. This novel interface design was evaluated via a virtual reality (VR) simulated environment featuring a street-crossing scenario. The evaluation results show that pedestrians can make the correct street-crossing decision more quickly if the approaching car has the novel interface "eyes" than in the case of normal cars. In addition, the results show that pedestrians feel safer with regard to crossing a street if the approaching car has eyes and if the eyes look at them.

Experimentation plays an essential role in exploratory programming, and programmers apply version control operations when switching the part of the source code back to the past state during experimentation. However, these operations, which we refer to as micro-versioning, are not well supported in current programming environments. We first examined previous studies to clarify the requirements for a micro-versioning tool. We then developed a micro-versioning tool that displays visual cues representing possible micro-versioning operations in a textual code editor. Our tool includes a history model that generates meaningful candidates by combining a regional undo model and tree-structured undo model. The history model uses code executions as a delimiter to segment text edit operations into meaning groups. A user study involving programmers indicated that our tool satisfies the above-mentioned requirements and that it is useful for exploratory programming.

Pets are humanity'V?stra G?talands oldest friend since ancient times. People have been living with them since then, and the relationship between people and pets as family members at home is well researched. Recently, social robots are entering family lives, and a new research field is being born, namely, a triad relationship between people, pets, and social robots. To investigate how a social robot affects a human-animal relationship in the home, an exploratory field experiment was conducted. In this experiment, a robot, called NAO, was introduced into the homes of 10 families, and 22 participants (with 12 pets:4 dogs and 8 cats), called 'owners' hereafter, were asked to interact with NAO. NAO was operated under two conditions:speaking positively to the pets, and speaking negatively to them. Just five sentenses that NAO spoke to the pets and two sentenses to the owners were different. The results of the study show that changing NAO's attitude to the pets affected both the owners? impression of the robot and the pet's impression of the robot (perceived by the owners).

In recent years, automatic or semiautomatic processing and analysis systems for a large amount of social listening data have been introduced and used in many industries. Honda Motor Co., Ltd. is also collecting and analyzing voice of customers from much type of media such as SNS using automatic Social Listening System. And verifying whether corporate images and brands are appropriately communicated or not every day. This verification is also used to find symptoms of risk that may be recalled. On the other hand, we found that there were many copied sentences which were delivered from us to society in collected information as voice and opinion of customers. In this case, if these collected sentences are automatically processed as voice of customers using a normal language processing algorithm, we should have a risk to get excessively more positive result than actual. This is because the information delivered from the company like announcement of a new product etc., always includes many positive expressions. And it has been confirmed that the distributor’s advertisement and a large amount of retweets follows it, also causes the same risk for the same reasons. It’s hard to say that we are correctly measuring the voice of customers. Based on the above situations, in this paper, firstly, we named the phenomenon as “Echo Phenomenon”, which incorrectly recognizes delivered information from us as voice of customers. And present it as a problem. Secondly, we propose a simple method to avoid this Echo Phenomenon problem without damaging useful information as much as possible, and show examples of application and its effect.

Parameter tweaking is a common task in various design scenarios. For example, in color enhancement of photographs, designers tweak multiple parameters such as "brightness" and "contrast" to obtain the best visual impression. Adjusting one parameter is easy; however, if there are multiple correlated parameters, the task becomes much more complex, requiring many trials and a large cognitive load. To address this problem, we present a novel extension of Bayesian optimization techniques, where the system decomposes the entire parameter tweaking task into a sequence of one-dimensional line search queries that are easy for human to perform by manipulating a single slider. In addition, we present a novel concept called crowd-powered visual design optimizer , which queries crowd workers, and provide a working implementation of this concept. Our single-slider manipulation microtask design for crowdsourcing accelerates the convergence of the optimization relative to existing comparison-based microtask designs. We applied our framework to two different design domains: photo color enhancement and material BRDF design, and thereby showed its applicability to various design domains.

Color enhancement is a very important aspect of photo editing. Even when photographers have tens of or hundreds of photographs, they must enhance each photo one by one by manually tweaking sliders in software such as brightness and contrast, because automatic color enhancement is not always satisfactory for them. To support this repetitive manual task, we present self-reinforcing color enhancement, where the system implicitly and progressively learns the user's preferences by training on their photo editing history. The more photos the user enhances, the more effectively the system supports the user. We present a working prototype system called SelPh, and then describe the algorithms used to perform the self-reinforcement. We conduct a user study to investigate how photographers would use a self-reinforcing system to enhance a collection of photos. The results indicate that the participants were satisfied with the proposed system and strongly agreed that the self-reinforcing approach is preferable to the traditional workflow.

We present a concept of using a movable background to navigate a caret on small mobile devices. The standard approach to selecting text on mobile devices is to directly touch the location on the text that a user wants to select. This is problematic because the user's finger hides the area to select. Our concept is to use a movable background to navigate the caret. Users place a caret by tapping on the screen and then move the background by touching and dragging. In this method, the caret is fixed on the screen and the user drags the background text to navigate the caret. We compared our technique with the iPhone's default UI and found that even though participants were using our technique for the first time, average task completion time was not different or even faster than Default UI in the case of the small font size and got a significantly higher usability score than Default UI.

Abstract We present an interactive design system for designing free‐formed bamboo‐copters, where novices can easily design free‐formed, even asymmetric bamboo‐copters that successfully fly. The designed bamboo‐copters can be fabricated using digital fabrication equipment, such as a laser cutter. Our system provides two useful functions for facilitating this design activity. First, it visualizes a simulated flight trajectory of the current bamboo‐copter design, which is updated in real time during the user's editing. Second, it provides an optimization function that automatically tweaks the current bamboo‐copter design such that the spin quality—how stably it spins—and the flight quality—how high and long it flies—are enhanced. To enable these functions, we present non‐trivial extensions over existing techniques for designing free‐formed model airplanes [ UKSI14 ], including a wing discretization method tailored to free‐formed bamboo‐copters and an optimization scheme for achieving stable bamboo‐copters considering both spin and flight qualities.

We propose subtle foot-based gestures named foot plantar-based (FPB) gestures that are used with sock-placed pressure sensors. In this system, the user can control a computing device by changing his or her foot plantar distributions, e.g., pressing the floor with his/her toe. Because such foot movement is subtle, it is suitable for use especially in a public space such as a crowded train. In this study, we first conduct a guessability study to design a user-defined gesture set for interaction with a computing device. Then, we implement a gesture recognizer with a machine learning technique. To avoid unexpected gesture activations, we also collect foot plantar pressure patterns made during daily activities such as walking, as negative training data. Additionally, we evaluate the unobservability of FPB gestures by using crowdsourcing. Finally, we conclude with several applications to further illustrate the utility of FPB gestures.

We present a video annotation system called ``AnnoTone', which can embed various contextual information describing a scene, such as geographical location. Then the system allows the user to edit the video using this contextual information, enabling one to, for example, overlay with map or graphical annotations. AnnoTone converts annotation data into high-frequency audio signals (which are inaudible to the human ear), and then transmits them from a smartphone speaker placed near a video camera. This scheme makes it possible to add annotations using standard video cameras with no requirements for specific equipment other than a smartphone. We designed the audio watermarking protocol using dual-tone multi-frequency signaling, and developed a general-purpose annotation framework including an annotation generator and extractor. We conducted a series of performance tests to understand the reliability and the quality of the watermarking method. We then created several examples of video-editing applications using annotations to demonstrate the usefulness of Annotone, including an After Effects plug-in.

Abstract We presentfacetons, geometric modeling primitives designed for building architectural models especially effective for a virtual environment where six degrees of freedom input devices are available. Afacetonis an oriented point floating in the air and defines a plane of infinite extent passing through the point. The polygonal mesh model is constructed by taking the intersection of the planes associated with thefacetons. With the simple interaction offaceton, users can easily create 3D architecture models. Thefacetonprimitive and its interaction reduce the overhead associated with standard polygonal mesh modeling, where users have to manually specify vertexes and edges which could be far away. Thefacetonrepresentation is inspired by the research on boundary representations (B‐rep) and constructive solid geometry, but it is driven by a novel adaptive bounding algorithm and is specifically designed for 3D modeling activities in an immersive virtual environment. We describe the modeling method and our current implementation. The implementation is still experimental but shows potential as a viable alternative to traditional modeling methods. Copyright © 2014 John Wiley & Sons, Ltd.

We present a system called Aibiki, which can support users in practicing the shamisen, a three-stringed Japanese musical instrument, via an automatic and adaptive score scroll. We chose Nagauta, as an example of a type of shamisen music. Each piece typically lasts 10-40 min; furthermore, both hands are required to play the shamisen, and it is not desirable to turn pages manually during a performance. In addition, there are some characteristic issues that are particular to the shamisen, including the variable tempo of the music and the unique timbre of the instrument, which makes pitch detection difficult using standard techniques. In this work, we describe an application that automatically scrolls through a musical score, initially at a predefined tempo. Because there is often a difference between the predefined tempo and tempo with which the musician plays the piece, the application adjusts speed of the score scroll based on the input from a microphone. We evaluated the performance of the application via a user study. We find that the system was able to scroll the score in time to the actual performance, and that the system was useful for practicing and playing the shamisen.

We present an animation creation workflow for integrating offline physical, painted media into the digital authoring of Flash-style animations. Generally, animators create animations with standardized digital authoring software. However, the results tend to lack the individualism or atmosphere of physical media. In contrast, illustrators have skills in painting physical media but have limited experience in animation. To incorporate their skills, we present a workflow that integrates the offline painting and digital animation creation processes in a labor-saving manner. First, a user makes a rough sketch of the visual elements and defines their movements using our digital authoring software with a sketch interface. Then these images are exported to printed pages, and users can paint using offline physical media. Finally, the work is scanned and imported back into the digital content, forming a composite animation that combines digital and physical media. We present an implementation of this system to demonstrate its workflow. We also discuss the advantages of using physical media in digital animations through design evaluations.

In this paper, we propose a to-do list interface for sharing tasks between human and multiple agents including robots and software personal assistants. While much work on software architectures aims to achieve efficient (semi-)autonomous task coordination among human and agents, little work on user interfaces can be found for user-oriented flexible task coordination. Instead, most of the existing human-agent interfaces are designed to command a single agent to handle specific kinds of tasks. Meanwhile, our interface is designed to be a platform to share any kinds of tasks between users and multiple agents. When agents can handle the task, they ask for details and permission to execute it. Otherwise, they try supporting users or just keep silent. New tasks can be registered not only by humans but also by agents when errors occur that can only be fixed by human users. We present the interaction design and implementation of the interface, Sharedo, with three example agents, followed by brief user feedback collected from a preliminary user study.

One of the difficulties with standard route maps is accessing to multi-scale routing information. The user needs to display maps in both a large scale to see details and a small scale to see an overview, but this requires tedious interaction such as zooming in and out. We propose to use a hierarchical structure for a route map, called a "Route Tree", to address this problem, and describe an algorithm to automatically construct such a structure. A Route Tree is a hierarchical grouping of all small route segments to allow quick access to meaningful large and small-scale views. We propose two Route Tree applications, "RouteZoom" for interactive map browsing and "TreePrint" for route information printing, to show the applicability and usability of the structure. We conducted a preliminary user study on RouteZoom, and the results showed that RouteZoom significantly lowers the interaction cost for obtaining information from a map compared to a traditional interactive map.

Parameter tweaking is one of the fundamental tasks in the editing of visual digital contents, such as correcting photo color or executing blendshape facial expression control. A problem with parameter tweaking is that it often requires much time and effort to explore a high-dimensional parameter space. We present a new technique to analyze such high-dimensional parameter space to obtain a distribution of human preference. Our method uses crowdsourcing to gather pairwise comparisons between various parameter sets. As a result of analysis, the user obtains a goodness function that computes the goodness value of a given parameter set. This goodness function enables two interfaces for exploration: Smart Suggestion, which provides suggestions of preferable parameter sets, and VisOpt Slider, which interactively visualizes the distribution of goodness values on sliders and gently optimizes slider values while the user is editing. We created four applications with different design parameter spaces. As a result, the system could facilitate the user's design exploration.

We present a series of projects for end-user authoring of interactive robotic behaviors, with a particular focus on the style of those behaviors: we call this approach Style-by-Demonstration (SBD). We provide an overview introduction of three different SBD platforms: SBD for animated character interactive locomotion paths, SBD for interactive robot locomotion paths, and SBD for interactive robot dance. The primary contribution of this article is a detailed cross-project SBD analysis of the interaction designs and evaluation approaches employed, with the goal of providing general guidelines stemming from our experiences, for both developing and evaluating SBD systems. In addition, we provide the first full account of our Puppet Master SBD algorithm, with an explanation of how it evolved through the projects.

Current programming environments use textual or symbolic representations. While these representations are appropriate for describing logical processes, they are not appropriate for representing raw values such as human and robot posture data, which are necessary for handling gesture input and controlling robots. To address this issue, we propose Picode, a text-based development environment integrated with visual representations: photos of human and robots. With Picode, the user first takes a photo to bind it to posture data. S/he then drag-and-drops the photo into the code editor, where it is displayed as an inline image. A preliminary in-house user study implied positive effects of taking photos on the programming experience.

We propose a technique called voice augmented manipulation (VAM) for augmenting user operations in a mobile environment. This technique augments user interactions on mobile devices, such as finger gestures and button pressing, with voice. For example, when a user makes a finger gesture on a mobile phone and voices a sound into it, the operation will continue until stops making the sound or makes another finger gesture. The VAM interface also provides a button-based interface, and the function connected to the button is augmented by voiced sounds. Two experiments verified the effectiveness of the VAM technique and showed that repeated finger gestures significantly decreased compared to current touch-input techniques, suggesting that VAM is useful in supporting user control in a mobile environment.

We present faceton, a geometric modeling primitive designed for building architectural models, using a six degrees of freedom (DoF) input device in a virtual environment (VE). A faceton is given as an oriented point floating in the air and defines a plane of infinite extent passing through the point. The polygonal mesh model is constructed by taking the intersection of the planes associated with the facetons. With the simple drag-and-drop and group interaction of faceton, users can easily create 3D architecture models in the VE. The faceton primitive and its interaction reduce the overhead associated with standard polygonal mesh modeling in VE, where users have to manually specify vertexes and edges which could be far away. The faceton representation is inspired by the research on boundary representations (B-rep) and constructive solid geometry (CSG), but it is driven by a novel adaptive bounding algorithm and is specifically designed for the 3D modeling activities in an immersive virtual environment.

As robots continue to enter people's everyday spaces, we argue that it will be increasingly important to consider the robots' movement style as an integral component of their interaction design. That is, aspects of the robot's movement which are not directly related to a task at hand (e.g., pick up a ball) can have a strong impact on how people perceive that action (e.g., aggressively or hesitantly). We call these elements the movement style. We believe that perceptions of this kind of style will be highly dependent on the culture, group, or individual, and so people will need to have the ability to customize their robot. Therefore, in this work we use Style by Demonstration, a style focus on the more-traditional programming by demonstration technique, and present the Puppet Dancer system, an interface for constructing paired and interactive robotic dances. In this paper we detail the Puppet Dancer interface and interaction design, explain our new algorithms for teaching dance by demonstration, and present the results from a formal qualitative study.

There are many toolkits for physical UIs, but most physical UI applications are not locomotive. When the programmer wants to make things move around in the environment, he faces difficulty related to robotics. Toolkits for robot programming, unfortunately, are usually not as accessible as those for building physical UIs. To address this interdisciplinary issue, we propose Phybots, a toolkit that allows researchers and interaction designers to rapidly prototype applications with locomotive robotic things. The contributions of this research are the combination of a hardware setup, software API, its underlying architecture and a graphical runtime debug tool that supports the whole prototyping activity. This paper introduces the toolkit, applications and lessons learned from three user studies.

PINOKY is a wireless ring-like device that can be externally attached to any plush toy as an accessory that animates the toy by moving its limbs. A user is thus able to instantly convert any plush toy into a soft robot. The user can control the toy remotely or input the movement desired by moving the plush toy and having the data recorded and played back. Unlike other methods for animating plush toys, PINOKY is non-intrusive, so alterations to the toy are not required. In a user study, 1) the roles of plush toys in the participants' daily lives were examined, 2) how participants played with plush toys without PINOKY was observed, 3) how they played with plush toys with PINOKY was observed, and their reactions to the device were surveyed. On the basis of the results, potential applications were conceptualized to illustrate the utility of PINOKY.

We present universal earphones that use both a proximity sensor and a skin conductance sensor and we demonstrate several implicit interaction techniques they achieve by automatically detecting the context of use. The universal earphones have two main features. The first involves detecting the left and right sides of ears, which provides audio to either ear, and the second involves detecting the shared use of earphones and this provides mixed stereo sound to both earphones. These features not merely free users from having to check the left and right sides of earphones, but they enable them to enjoy sharing stereo audio with other people.

This paper introduces DressUp, a computerized system for designing dresses with 3D input using the form of the human body as a guide. It consists of a body-sized physical mannequin, a screen, and tangible prop tools for drawing in 3D on and around the mannequin. As the user draws, he/she modifies or creates pieces of digital cloth, which are displayed on a model of the mannequin on the screen. We explore the capacity of our 3D input tools to create a variety of dresses. We also describe observations gained from users designing actual physical garments with the system.

As various home robots come into homes, the need for efficient robot task management tools is arising. Current tools are designed for controlling individual robots independently, so they are not ideally suitable for assigning coordinated action among multiple robots. To address this problem, we developed a management tool for home robots with a graphical editing interface. The user assigns instructions by selecting a tool from a toolbox and sketching on a bird's-eye view of the environment. Layering supports the management of multiple tasks in the same room. Layered graphical representation gives a quick overview of and access to rich information tied to the physical environment. This paper describes the prototype system and reports on our evaluation of the system.

We present the FuwaFuwa sensor module, a round, hand-size, wireless device for measuring the shape deformations of soft objects such as cushions and plush toys. It can be embedded in typical soft objects in the household without complex installation procedures and without spoiling the softness of the object because it requires no physical connection. Six LEDs in the module emit IR light in six orthogonal directions, and six corresponding photosensors measure the reflected light energy. One can easily convert almost any soft object into a touch-input device that can detect both touch position and surface displacement by embedding multiple FuwaFuwa sensor modules in the object. A variety of example applications illustrate the utility of the FuwaFuwa sensor module. An evaluation of the proposed deformation measurement technique confirms its effectiveness.

We propose a cooking system that operates in an open environment. The system cooks a meal by pouring various ingredients into a boiling pot on an induction heating cooker and adjusts the heating strength according to the user's instructions. We then describe how the system incorporates robotic- and human-specific elements in a shared workspace so as to achieve a cooperative rudimentary cooking capability. First, we use small mobile robots instead of built-in arms to save space, improve flexibility and increase safety. Second, we use detachable visual markers to allow the user to easily configure the real-world environment. Third, we provide a graphical user interface to display detailed cooking instructions to the user. We hope insights obtained in this experiment will be useful for the design of other household systems in the future.

Numerous robots have been developed, and some of them are already being used in homes, institutions, and workplaces. Despite the development of useful robot functions, the focus so far has not been on user interfaces of robots. General users of robots find it hard to understand what the robots are doing and what kind of work they can do. This paper presents an interface for the commanding home robots by using stroke gestures on a computer screen. This interface allows the user to control robots and design their behaviors by sketching the robot's behaviors and actions on a top-down view from ceiling cameras. To convey a feeling of directly controlling the robots, our interface employs the live camera view. In this study, we focused on a house-cleaning task that is typical of home robots, and developed a sketch interface for designing behaviors of vacuuming robots.

The first robotic copies of real humans have become available. They enable their users to be physically present in multiple locations at the same time. This study investigates what influence the embodiment of an agent has on its persuasiveness and its perceived personality. Is a robotic copy as persuasive as its human counterpart? Does it have the same personality? We performed an experiment in which the embodiment of the agent was the independent variable and the persuasiveness and perceived personality were the dependent measurement. The persuasive agent advertised a Bluetooth headset. The results show that an android is found to be as persuasive as a real human or a video recording of a real human. The personality of the participant had a considerable influence on the measurements. Participants that were more open to new experiences rated the persuasive agent lower on agreeableness and extroversion. They were also more willing to spend money on the advertised product.

This paper reports an initial field trial with a prototype of a semiautonomous communication robot at a train station. We developed an operator-requesting mechanism to achieve semiautonomous operation for a communication robot functioning in real environments. The operator-requesting mechanism autonomously detects situations that the robot cannot handle by itself; a human operator helps by assuming control of the robot.

This paper reports a method that uses humanoid robots as a communication medium. There are many interactive robots under development, but due to their limited perception, their interactivity is still far poorer than that of humans. Our approach in this paper is to limit robots' purpose to a non-interactive medium and to look for a way to attract people's interest in the information that robots convey. We propose using robots as a passive-social medium, in which multiple robots converse with each other. We conducted a field experiment at a train station for eight days to investigate the effects of a passive-social medium.

In this research, we realize human telepresence by developing a remote-controlled android system called Geminoid HI-1. Experimental results confirm that participants felt stronger presence of the operator when he talked through the android than when he appeared on a video monitor in a video conference system. In addition, participants talked with the robot naturally and evaluated its human likeness as equal to a man on a video monitor. At this paper's conclusion, we will discuss a remote-control system for telepresence that uses a human-like android robot as a new telecommunication medium.

With developments in robotics, robots "living" with people will become a part of daily life in the near future. However, there are many problems with social robots. In particular, the behavior of robots can influence human relations, and societies have not yet clarified this. In this paper, we report on an experiment we conducted to verify the influence of robot behavior on human relations using the "balance theory." The results show that robots can have both good and bad influence on human relations. One person's impression of another can undergo changes because of a robot. In other words, robots can construct or collapse human relations.

Previous research works in robotics and cognitive science have reported that humans utilize embodied cooperative behaviors in communication, such as nodding in response to another's it utterance and looking at a certain object in a certain direction as others look or point at. We have developed a humanoid robot that utilizes such an embodied cooperative behavior for natural communication in a route guidance situation. It obtains numerical data on a human's body movement via a motion capturing system and then autonomously selects appropriate cooperative embodiment units from 18 implemented units. Each unit realizes a certain cooperative embodiment behaviors such as eye-contact by using the motion capturing system as well. As a result of a subject experiment, we have verified the effectiveness of the embodied cooperative behaviors of the robot for reliable and sympathetic communication. Moreover, we analyzed how the auditory expression and the embodiment contributed to the effect.