Jun-ichiro Watanabe

VortexBath: study of tangible interaction with water in bathroom for accessing and playing media files

We describe an interface for places where people use water, such as the kitchen, toilet, or bathroom. We developed a prototype that can be operated by users by tangibly interacting with water. It enables image files and movie files to be browsed by projecting the images onto water, it plays music files with album jacket images, and it reads out information from the Internet using speech-synthesis technology. We also describe a demonstration of how users can access their media files by tangibly interacting with water, which is different from conventional way such as pressing buttons on a remote control.

Resting Time Activeness Determines Team Performance in Call Centers

Improving team performance has long been a great concern of leaders and managers. Recent progress in wearable sensor technologies has given them a strong means of grasping their team conditions. Studies using such technologies have shown, for example, that the cohesion of a face-to-face network, as measured using wearable sensors, correlates with performance. However, causality between face-to-face communication and performance has remained unclear. We investigated, in a call center environment, the relationships between a teams activity levels while working and while resting and its performance. We found that the activity level while working does not correlate with team performance whereas that while resting does. Furthermore, we found that improving face-to-face communication leads to increased activity levels and to better team performance. Our results demonstrate that team performance can be improved by managing workplace activity levels.

Two TV interfaces for accessing contents at ease in an "always-recording" multi-channel situation

We propose two TV interfaces for accessing a rich variety of contents stored in large-capacity HDD at ease. The first one is designed for handling multi-stream data received by multiple TV tuners and searching multiple TV channels simultaneously. The second one is deigned for handling a time range and searching for scenes in that range. These interfaces can be implemented on commercial products such as PCs, TVs and HDD recorders.

Profiting from IoT: the key is very-large-scale happiness integration

Big data without link to value is merely a cost. We have studied how to profit from data with Internet-of-Things technologies for over 10 years to reach the answer: the Wearable Happiness Meter. It allows us to integrate the measure of both wellbeing and productivity of 7-billion people worldwide, which was the dream of the 18th-century philosopher Jeremy Bentham, numeration of the greatest happiness of the greatest number to measure the right and wrong. Knowing right and wrong with the 10x speed over conventional financial feedback accelerates the growth of the enterprise, the economy, and the individual to maximize the worldwide happiness. Here the integration is not only on a chip, but in the distributed massive chips embedded in the society.

Two TV interfaces for freely accessing the content of continuous multi-channel recording

We propose two TV interfaces for freely accessing a rich variety of content stored on a large-capacity HDD by continuous multi-channel recording. The first is designed to handle multi-stream data received by multiple TV tuners and to simultaneously search multiple TV channels. The second is designed to handle specific time ranges and to search for scenes within those ranges. These interfaces can be incorporated into commercial products such as PCs, TVs, and HDD recorders.

Moving-icon-based GUI for accessing contents at ease on mobile phones

An icon-based graphical user interface (GUI) for mobile phones - which displays various contents without discrimination - was developed. The icons move around on the display and change their graphics or captions when linked contents are renewed. The moving icons can be browsed at ease, and contents that may not have been noticed in a normal text-based interface may be discovered. This interface is designed as a new portal to unknown or new contents.

Exploring Relationship between Face-to-Face Interaction and Team Performance Using Wearable Sensor Badges

Quantitative analyses of human-generated data collected in various fields have uncovered many patterns of complex human behaviors. However, thus far the quantitative evaluation of the relationship between the physical behaviors of employees and their performance has been inadequate. Here, we present findings demonstrating the significant relationship between the physical behaviors of employees and their performance via experiments we conducted in inbound call centers while the employees wore sensor badges. There were two main findings. First, we found that face-to-face interaction among telecommunicators and the frequency of their bodily movements caused by the face-to-face interaction had a significant correlation with the entire call center performance, which we measured as “Calls per Hour.” Second, our trial to activate face-to-face interaction on the basis of data collected by the wearable sensor badges the employees wore significantly increased their performance. These results demonstrate quantitatively that human-human interaction in the physical world plays an important role in team performance.

Informal Face-to-Face Interaction Improves Mood State Reflected in Prefrontal Cortex Activity

Recent progress with wearable sensors has enabled researchers to capture face-to-face interactions quantitatively and given great insight into human dynamics. One attractive field for applying such sensors is the workplace, where the relationship between the face-to-face behaviors of employees and the productivity of the organization has been investigated. One interesting result of previous studies showed that informal face-to-face interaction among employees, captured by wearable sensors that the employees wore, significantly affects their performance. However, the mechanism behind this relationship has not yet been adequately explained, though experiences at the job scene might qualitatively support the finding. We hypothesized that informal face-to-face interaction improves mood state, which in turn affects the task performance. To test this hypothesis, we evaluated the change of mood state before and after break time for two groups of participants, one that spent their breaks alone and one that spent them with other participants, by administering questionnaires and taking brain activity measurements. Recent neuroimaging studies have suggested a significant relationship between mood state and brain activity. Here, we show that face-to-face interaction during breaks significantly improved mood state, which was measured by Profiles of Mood States (POMS). We also observed that the verbal working memory (WM) task performance of participants who did not have face-to-face interaction during breaks decreased significantly. In this paper, we discuss how the change of mood state was evidenced in the prefrontal cortex (PFC) activity accompanied by WM tasks measured by near-infrared spectroscopy (NIRS).

A Method for Analyzing Influence of Emotions of Posts in SNS Conversations

We devised a method for analyzing communication, which focuses on influences between two sequential posts in a conversation on a social-network service (SNS). Posts expressed on an SNS are classified into three emotions: positive, negative, or neutral. Two influences were analyzed: the emotion of a persons preceding post on the emotion of a post from another person, and the emotion of a persons post on the emotion of a subsequent post from the same person. To analyze these influences, the basis of the frequency of emotional transitions of two sequential posts in actual conversational data is evaluated by probability and information entropy analysis. Three tendencies were found: first, a person who posted positively before is likely to post positively again, second, a neutral emotion of a persons post is more likely to be induced when both that person and another person expressed a neutral emotion in the past, third, negative posts do not have a strong influence on the emotion of subsequent posts of that person and other persons. These findings may be useful, for example, in promoting positive conversations.

UAV vision-based localization techniques using high-altitude images and barometric altimeter

Position information of unmanned aerial vehicles (UAVs) and objects is important for inspections conducted with UAVs. The accuracy with which changes in object to be inspected are detected depends on the accuracy of the past object data being compared; therefore, accurate position recording is important. A global positioning system (GPS) is commonly used as a tool for estimating position, but its accuracy is sometimes insufficient. Therefore, other methods have been proposed, such as visual simultaneous localization and mapping (visual SLAM), which uses monocular camera data to reconstruct a 3D model of a scene and simultaneously estimates the trajectories of the camera using only photos or videos. In visual SLAM, UAV position is estimated on the basis of stereo vision (localization), and 3D points are mapped on the basis of the estimated UAV position (mapping). Processing is implemented sequentially between localization and mapping. Finally, all the UAV positions are estimated and an integrated 3D map is created. For any given iteration in the sequential processing, there will be estimation error, but in the next iteration, the previous estimated position will be used as a base position regardless of this error. As a result, error accumulates until the UAV returns to a location it passed before. Our research aims to mitigate this problem. We propose two new methods. (1) Accumulated error caused by local matching with sequential low-altitude images (i.e. close-up photos) is corrected with global-matching between low- and high-altitude images. To perform global-matching that is robust against error, we implemented a method wherein the expected matching areas are narrowed down on the basis of UAV position and barometric altimeter measurements. (2) Under the assumption that absolute coordinates include axis-rotation error, we proposed an error-reduction method that minimizes the difference in the UAVs’ altitude between the visual SLAM and sensor (bolometer and thermometer) results. The proposed methods reduced accumulated error by using high-altitude images and sensors. Our methods improve the accuracy of UAV- and object-position estimation.