Itaru Kuramoto

Augmented Practice Mirror: A Self-learning Support System of Physical Motion with Real-Time Comparison to Teacher's Model

An effective way to learn some physical motions such as dancing, playing sports, making traditional crafts, and so on, is to mimic teachers motion. In this style of learning, it is important for the learner to recognize the difference between the teachers motion and his/her one. We propose Augmented Practice Mirror (APM) learning support system. APM shows the mirror image of learners motion overlapped teachers one, and the difference between them. These three images are shown simultaneously on a large screen as virtual mirror in real time. As a result of the experimental evaluations, it was found that APM was better in recognizing the difference between the participants motion and the teachers one than two common methods, and that the hybrid interface of voice recognition and gesture was better than the single interface of voice recognition or gesture for operating APM.

Presenter Supporting System with Visual-Overlapped Positive Response on Audiences

When we speak in public, we sometimes fail to speak well because of anxiety and strain. To solve such a problematic situation, we propose a method of overlapping positive response on audiences, and implement the system which overlaps an image of smiling pumpkin with nodding on each audience using video see-through HMD. As the result of an experimental evaluation of the proposed system, it is found that this system can reduce the anxiety and strain compared with the situation that scowling audiences are in view. It is considered that the result comes from two facts: (1) participants’ anxiety and strain increase in case that audiences or pumpkins are scowling, and (2) they decrease in case that audiences or pumpkins are smiling. In addition, it is found that the feeling of relief and satisfaction, which are factors of reducing the anxiety and strain, are more improved in smiling pumpkins than smiling audiences.

Visualizing Velocity and Acceleration on Augmented Practice Mirror Self-Learning Support System of Physical Motion

An effective way to learn some physical motions such as dancing, playing sports, making traditional crafts, and so on, is to mimic teachers motion. In this style of learning, it is important for the learner to recognize the difference between the teachers motion and his/her one. Augmented Practice Mirror (APM) is a learning support system which shows the mirror image of learners motion overlapped teachers one, and the difference between them. In addition, the velocity and acceleration of the body movement is also important to understand the teachers motion. In this paper, we propose a visualization method of the velocity and acceleration of the teachers motion for the learner to understand it more easily and clearly.

Analysis of Stroking Motions in Drawing by Experts for Development of a Learning Support System

Illustrators who have some drawing experience can sometimes draw an ideal stroke repeatedly. However, they cannot always reproduce an ideal stroke that they have drawn, because they do not understand how they moved their own hands to draw it. In order to solve this problem, a new learning support system based on presenting the ideal stroking motion of the learner as a teachers motion is needed so that learners can enhance their own drawing skills. In order to clarify the differences in motion between good and bad drawing strokes as the first step in the development of such a system, this paper analyzes the stroking motions of experts in the process of drawing circles. Several features are exploited, namely, the pen speed, the pen pressure, the time required to draw each quarter circle, and the movement of the hand. With these features, the accuracy of classification using machine learning is 67% on average. This means that stroke speed, pen pressure, and stroke rhythm (which is the specific pattern of changes in speed) may be useful to distinguish between good and bad strokes.

Ghost-hunting: a cursor-based pointing technique with picture guide indication of the shortest path

Ghost-Hunting (GH) is a new technique that improves pointing performance in a graphical user interface (GUI) by expanding targets to facilitate easier access. In GH, the effect of decreasing the movement distance of a cursor by expanding the size of onscreen targets is utilized to improve the GUI. GH shows the guides of the end point of the shortest movement path, called ghosts, inside expanded target areas. Users can optimize their cursor movements by only moving their cursor towards the ghosts in GH, unlike other techniques that use the invisible outline of an expanded target such as with Bubble Cursor. We conduct an experimental evaluation to clarify the effectiveness of GH in menu-item selection tasks. The result shows that GHs selection time was significantly faster than that of the ordinal cursor or Bubble Cursor. In particular, GH is faster than Bubble Cursor in environments with a high density of targets.

Supporting novice waiters by indicating next action based on partial task integration algorithm

Staffs are classified to veterans and novices. When executing a certain amount of tasks, novices need time more than veterans because novices cannot decide which task should be done next and take long time to execute each task. In this paper, we focus on the problem that novices who are requested many tasks cannot judge which task should be executed now, and propose a system which constructs the appropriate order of tasks and present the proper action to novices to solve the problem. In the system, we introduce “Partial Task Integration” algorithm that can shorten the time for executing tasks by integrating some actions in different tasks to one action. To evaluate this system, we have implemented two types of the prototype, and experimentally compared task execution time and mental burden on prototypeusing case and no-system case. As the result, prototype-using case took longer time than no-system case because the time for looking at the display to confirm the next action are needed.

Airway Cursor: A Pointing Technique Based on Direction of Mouse Movement Towards a Targets

In conventional pointing cursor environments, selecting a small object or an object that is at a distance from the cursor takes a considerable amount of time. To solve this problem, we propose a new pointing technique called “Airway Cursor.” In the proposed technique, to select a target object, all users need to do is to specify the direction toward the target object. To specify the direction, the user simply moves the cursor a little toward the target object and then clicks. If there are multiple objects between the cursor and the target object, the user can select the target object by carrying out this operation on the intervening non-target objects until the target object is reached. This technique reduces the time to select an object by shortening the distance the mouse has to move.

Notification design using mother-like expressions

People often ignore their reminders or schedulers, which notify them about their requisite tasks using monotonous message expressions, usually because they do not pay sufficient attention to their notifications and they feel that they are under no pressure to respond. In this study, we propose a notification design method that uses mother-like expressions to enhance user acceptability of notifications. Mother-like expressions are highly variable, such as euphemistic expressions and imperative forms, and notifications that use them may apply different levels of pressure on users. To implement a reminder system that provides notifications regarding various tasks using mother-like expressions, we classified tasks collected from actual reminders, schedulers, and diaries. As a result, we found that the tasks could be classified into six verb-based categories, which could be adapted using mother-like expressions.

IUstream: personal live streaming support system with automatic collection and real-time recommendation of topics

Nowadays, it becomes much easier to perform live streaming personally via the Internet. When performers broadcast their programs, they sometimes have no idea for what they should talk. In this paper, we propose a system, named IUstream, to recommend one of proper topics which have been collected automatically. As the result of an empirical evaluation, it is found that IUstream can support performers.

Empirical Evaluation of Throwing Method to Move Object for Long Distance in 3D Information Space on Mobile Device

In our previous work, a throwing method to move an object for long distance in 3D information space on a mobile device was proposed. With the method, as we throw the object to move it far away in the real world, we can throw the virtual object in 3D information space. This simple throwing method was improved by adding following three functions. They were real time adjusting the direction of moving object, moving viewpoint to follow the thrown object, and initializing viewpoint after the movement. The purpose of this paper is to examine the performance of the improved throwing method to move the object for long distance in 3D information space. From the experiment, it is found that the improved throwing method is efficient to move the object for long distance in 3D information space on mobile devices.