There are many interactive design tools: Adobe Photoshop, GIMP, and so on. The interactive design tools often provide their users many visual effects. The users need to look for design parameter values appropriate to their desired visual effect. Interactive design can be dealt as a sort of optimal solution search problems. In optimal solution search, initial value setting plays an important role. Onomatopoeia can solve the initial value setting of the interactive design because onomatopoeia can easily describe the visual effect. We proposed a method that allows the users to input their own arbitrary onomatopoeia to design and obtain their desired visual effect. The method hires an onomatopoeia thesaurus map that can convert the arbitrary onomatopoeia to the initial values. We adopted Japanese brush font design system as an experimental example of the interactive design tool in order to evaluate our proposed method. Human subjects used the system and set the initial values of design parameters to design bold and scratched look of target fonts. As a result, the method was able to set more appropriate initial values closer to the optimal values to design the target in comparison with other conventional methods. The proposed method can be useful to solve the initial value setting of the interactive design.

Onomatopoeias are useful expression to communicate intuitive image of some designs. There are some approaches adopt onomatopoeias to design computer graphics, robot motion or Japanese calligraphic fonts. Murata et al. [11] introduced onomatopoeias to their system to design Japanese calligraphic fonts, however, it wasn't easy task to achieve suitable design using only onomatopoeias. On the other hand, Nakamura et al. [12] suggested that achieving an optimal design on an interactive design system corresponds to solving a search problem. To solve the search problem, selection of initial values plays an important role. Nakamura et al. proposed introducing onomatopoeias to set proper initial values of Murata's design system. Nakamura's experimental result showed that the proposed method is useful to achieve an suitable design of the calligraphic font. But the experiment was conducted for the fonts whose appearances were easily described by using onomatopoeias. Our study aims to reevaluate Nakamura's method. We adopted the fonts whose appearances were difficult to describe by onomatopoeias, and conducted an experiment to evaluate the cost to achieve the suitable design. As the experimental result, onomatopoeias can be a useful tool to achieve an suitable design without considering easiness or difficulty to describe by onomatopoeias.

In recent years, devices, such as household electrical appliances, have been created that enable a person using them to control them by pointing their fingers. This is also the case for sharing information with robots, but when a person points his or her finger, it is unknown whether the point position is accurate. In this paper, we investigate the difference between a target point and the actual point that someone has indicated when pointing his or her finger and propose a method for correcting the amount of difference by using the inclusion-exclusion integral.

With the growth of robot technology, more robots are being designed to support learning. Most studies in the field have focused on robot behavior, with only a few studies focusing on robot utterances. Correspondingly, the manner in which such utterances affect learning is poorly understood. This study investigates the effects of collaborative learning wherein a robot encourages a learner. We conducted an experiment to compare the learning effect in three groups. In the first group, learning was conducted with a robot that supplied praises using onomatopoeia, i.e., the representation of an object or state based on the sounds associated with it. In the second group, a robot supplied praises using adjectives or adverbs. In the third group, a robot supplied praise without using onomatopoeia, adjectives, or adverbs. The results of this study suggest that collaborative learning using the first or third method is more effective than that involving adjective/adverb communication.

Adobe Illustrator provides many tools for a user to create art works. The tools also provide many parameters or options that the user can tune up or select. This study focuses on black-and-white drawings (“Sumi-e” or “Suiboku-ga” in Japanese) on Adobe Illustrator. In order to create black-and-white drawings, the user usually has to select a proper brush from preset brushes Adobe Illustrator provides. But the selection is difficult for the user, especially beginners. This paper proposes a supporting plug-in tool for the user to decide and apply the proper brush. The plug-in can accept an onomatopoeic utterance input which expresses the user's own imagination or impression of the brush. Onomatopoeia is well known as a useful figurative expression for Japanese people to describe their own imagination or impression for something. This paper reports the configuration of the plug-in and illustrated some examples of black-and-white drawings created by using the plug-in. The architecture of the plug-in consists of CNN(convolution neural network), database of brush samples, brush image interpolation, fuzzy-based image expansion and contraction, and so on. CNN allows input of arbitrary onomatopoeias. The brush image interpolation generates a new brush from brush samples in the database. The fuzzy-based image expansion and contraction transforms the new brush into a natural-looked brush form with less jaggy.

This paper proposes a new approach to archive the robust tracking of moving objects under moving camera environment where the similar moving objects cross each other. Tracking with moving camera sometimes fails to track the object with similar color objects or similar background. Proposed approach is a particle filter based approach. It introduces the likelihood calculated by probabilistic background model which is constructed using dense optical flow and fast density estimation. Proposed approach introduces SVM (Support Vector Machine)1 to judge the scene where it is difficult to construct the probabilistic background model with non-uniform optical flow. This SVM uses the degree histogram of optical flow. Usefulness of proposed approach is evaluated in the experiments using actual video and the performance is compared with recent tracking approaches by quantitative evaluations.

This paper proposes an approach for a tracking method robust to the intersection with objects with appearances similar to a target object. The proposed method targets image sequences taken by a moving camera and is based on the particle filter. Tracking methods using color information tend to track mistakenly a background region or an object with color similar to the target object. The method constructs the probabilistic background model by the histogram of the optical flow and defines the likelihood function so that the likelihood in the region of the target object may become large. This causes increasing the accuracy of tracking. The probabilistic background model is made by the density forests. It can infer a probabilistic density fast. Results are demonstrated by experiments using the real videos of outdoor scenes.

Onomatopoeias are useful tool to communicate intuitively and conveniently among people. This paper focused on the utility of onomatopoeias and proposed a design supporting system of Japanese Kanji-calligraphic “Shodo” font using onomatopoeia utterance. The system can generate a variety of scratched- and blurred-look design of “Shodo”. In order to realize the design, the system utilized the correspondence between onomatopoeias and the scratched- and blurred-look. This paper reported the concept and the architecture of the proposed system. And we demonstrated some output examples generated by the system.

A proposed robot provides functionality inspired by the behavior of hearing dogs, which assist hearing-impaired people by alerting them to important sounds such as fire and smoke alarms. Hearing dogs use body contact for communication with hearing-impaired people, a process heavily depending on haptic communication. The proposed robot also uses physical contact for urgent notification, like a hearing dog's touching behavior. The robot can move using its wheels and then approach and bump people. To be explicit our proposal, our bumping behavior model was simplified and an experiment was conducted with hearing-impaired participants and a prototype robot. This paper reports the experimental results and discusses effectiveness of the robot's bumping behavior.

An endoscope is a medical instrument that acquires images inside the human body. In this paper, a new 3-D reconstruction approach is proposed to estimate the size and shape of the polyp under conditions of both point light source illumination and perspective projection. Previous approaches could not know the size of polyp without assuming reflectance parameters as known constant. Even if it was possible to estimate the absolute size of polyp, it was assumed that the parameter of camera movement ∆Z is treated as a known along the depth direction. Here two images are used with a medical suture which is known size object to solve this problem and the proposed approach shows the parameter of camera movement can be estimated with robust accuracy with correspondence between two images taken via slight movement of Z. Experiments with endoscope images are demonstrated to evaluate the validity of proposed approach.

In this paper, we propose a new method for object tracking robust to the intersection with other objects with similar appearance and to the great rotation of the camera. The method uses 3D information of the feature points and the camera position by the image-based localization method. The movement information of the camera is used by the prediction process and the calculation process of the likelihood. Furthermore, the method extracts foreground objects by the homography transformation. The result is used by the likelihood function and by the process judging whether the target object is occluded by a background object or not. The proposed method can track the target object robustly when the camera rotates greatly and when the target object is occluded by the background object or the other object. Results are demonstrated by experiments using real videos.

Research on physical human-robot interaction has been attracting attention recently, focusing on robot embodiment. The work reported here proposes Active Touch Communication Robot (AcToR), a robot that is modeled on the hearing dog. A hearing dog is a type of dog assist people who are deaf or hard of hearing by alerting their handler to important sounds. AcToR uses the sense of touch to notify a human of the intention to transfer information. For example, when AcToR detects that a cell phone that is in another location has received a call, AcToR moves to the user's location and makes contact with the user's body to notify the user of the incoming call. The AcToR robot is based on the Roomba®and uses the Roomba's bumper and contact sensors to detect contact. This paper reports the results of psychological experiments using the AcToR robot that indicate the feasibility of using touch to transfer information from a robot to a person.

Robots are being used more and more in dangerous environments such as space and disaster areas. However, when robots are at risk in dangerous environments, the time during which robot operators can issue risk avoidance instructions is limited. Therefore, robots should be able to acquire behaviors that enable them to autonomously avoid danger. In this paper, we present a probability-based reinforcement learning (PrRL) method and apply it to robot behavior acquisition.

Embodied expertise, which expresses skills of experts, is a kind of tacit knowledge that is difficult to transfer to another person by means of writing it down or verbalizing it. The aim of our study is to translate embodied expertise into explicit knowledge, i.e. onomatopoeias. We call the onomatopoeias "embodied expertise onomatopoeias" which could facilitate people to intuitively and easily understand the skills. Acquiring "embodied expertise onomatopoeias" is considered as a problem of pattern recognition. Our study adopted a skill of Japanese penmanship "Pen Shodo" which is Japanese calligraphy using pen to be translated to onomatopoeias, and investigated a possibility to construct a classification system for the skill.

We investigated the effect of robot's utterances using onomatopoeia on collaborative learning. The robot was designed to praise or comfort by using onomatopoeia when learners are given problem to solve through a learning system. When learners can correctly solve a problem, the robot praises the learner's success. When learners cannot solve it, the robot comforts the learners to keep working at it. Eight college students learns mathematics by using a learning system with a robot for three weeks and took exams. We found that a robot could comfort learners that used onomatopoeia more than a robot that did not use onomatopoeia. This suggests that the robot that praises or comforts by using onomatopoeia helps learners maintain their motivation in collaborative learning.

We propose a crossover operation for multi-terminal decision diagrams (MTBDDs). To survey this crossover operation, we conducted experiments of the evolution of MTBDDs with and without the proposed crossover operation. We confirmed that MTBDDs that have better fitness were obtained in the evolution of MTBDDs with the proposed crossover operation than without it. We also confirmed that MTBDDs that possess the smaller number of vertices were obtained in the evolution of MTBDDs with the proposed crossover operation than without it.

In this paper, we proposed a fuzzy approach to segmenting objects using spatial location information from depth image. The optical and location information are combined by proposed fuzzy rules tale which base on K-means clustering. The segmentation of our framework is an efficient graph-based image segmentation algorithm. This framework combined obvious changes in color and physical location to segment reality scenes into uniform regions. The performance of our proposed framework is demonstrated in a series of reality-scene images using experimental data from the Middlebury stereo image data.

An endoscope is a medical instrument that acquires images inside the human body. This paper proposes a new approach to recover 3-D shape under conditions of both point light source illumination and perspective projection. Previous approaches recovered shape based on a Fast Marching Method under conditions of parallel light source and orthographic projection. The new approach uses optimization based on constraints provided by geometry and by a suitable image irradiance equation. Experiments with endoscope images are demonstrated to confirm that the recovered shape is improved.

In line with the effects of Japan's aging society with fewer children, the number of elderly with dementia who live alone and without care is increasing, therefore at-home care is beginning to be required. Doll therapy is a way of at-home dementia care. Doll therapy can help improve mental status of the elderly, because their logical and rational thinking is activated by imaging the child care experience with feeling and emotion at the times. In this research, we consider using Babyloid, a baby type robot, for doll therapy. As a first step of this research, we investigated whether elderly people in a nursing home for the elderly home accept Babyloid.

Given the remarkable recent progress in robotics research, we can envision the day when robots and humans coexist and robots become closely integrated into our daily lives. This means endowing robots with the ability to communicate so they perceive human emotion, adapt their behavior to humans, and sense situations even without explicit instructions. Meanwhile, affective computing, that interprets emotion or other affective phenomena from human biosignals, has emerged as an area of great interest. In addition to biosignals-brain waves, heart rate, pulse, electrical activity, and the like-affective computing is concerned with facial expressions, gestures, and a wide range of other indicators of emotion. Here we explore the latest insights of affective computing in relation to human-robot interaction (HRI). There is good reason to believe robots will soon have the ability to read human emotions, so here we investigate the feasibility of inferring human psychological states from biosensor signals. Obviously, non-invasive biosensors that don't interfere with normal everyday activities would be preferable. A number of inexpensive user-friendly brain-wave sensors have been brought to market recently, and we employ one of these devices, the NeuroSky Mindset EEG neuroheadset, in assessment trials to explore the feasibility of inferring subjective assessments. Using our experimental setup, we find that it is indeed possible to infer subjective assessments from biosignals, and this capability could prove immensely useful for future HRI applications.

Given a remarkable recent progress in robotics research, we can envision the day when robots and humans coexist and robots become closely integrated into our daily lives. This means endowing robots with the ability to communicate so they perceive human emotion, adapt their behavior to humans, and sense situations even without explicit instructions. Meanwhile, affective computing, that interprets emotion or other affective phenomena from human biosignals, has emerged as an area of great interest. In addition to biosignals-brain waves, heart rate, pulse, electrical activity, and the like-affective computing is concerned with facial expressions, gestures, and a wide range of other indicators of emotion. Here we explore the latest insights of affective computing in relation to human-robot interaction (HRI). There is good reason to believe robots will soon have the ability to read human emotions, so here we investigate the feasibility of inferring human psychological states from biosensor signals. Obviously, non-invasive biosensors that don't interfere with normal everyday activities would be preferable. A number of inexpensive user-friendly brain-wave sensors have been brought to market recently, and we employ one of these devices, the Neuro Sky Mindset EEG neuroheadset, in assessment trials to explore the feasibility of inferring subjective assessments. Using our experimental setup, we find that it is indeed possible to infer subjective assessments from biosignals, and this capability could prove immensely useful for future HRI applications.

In this paper, we propose a method, using multivalued decision diagrams (MDDs), to obtain motion representation of humanoid robots. Kanoh et al. have proposed a method, which uses multiterminal binary decision diagrams (MTBDDs), to acquire robot controller. However, nonterminal vertices of MTBDDs can only treat values of 0 or 1; multiple variables are needed to represent a single joint angle. This increases the number of the non-terminal vertices and MTBDDs that represent that the controller becomes complex. Therefore, we consider using the MDD, in which its nonterminal vertices can take on multiple output values. To obtain humanoid robot motion representation, we propose evolutionary MDDs and show experimental results comparing evolutionary MDDs and evolutionary MTBDDs through simulations of acquisition of robot motion in this paper. Moreover, we verify whether the evolution of MDD using a memetic algorithm is effective.

It could be very important and useful to enable human stress to be estimated on basis of quantitative values via objective analysis. There have been several approaches to estimate the stress so far. Most of them need a lot of time to measure or calculate it, and what is more, they might cause physical or mental burden for human subjects. The purpose of our study is to propose and develop a method to estimate subjective stress through a simple approach which doesn't cause much burden for users. In this paper we propose a method, which is called TPAf (Turning Point Amplitude via finger plethysmogram). Original TPA is a kind of heart rate variability analysis and needs to attach sensors on his/her breast. Our experimental results indicated that it has a certain relationship between subjective stress and TPAf. A method based on TPAf could be efficient to estimate subjective stress.

A method in which multi-valued decision diagrams (MDDs) are used to acquire robot action rules is proposed. Kanoh et al. have proposed a method, which uses multi-terminal binary decision diagrams (MTBDDs), to acquire robot action rules. But the variables of MTBDDs can only take values of 0 or 1; multiple variables are needed to represent a single joint angle. This increases the number of variables and the MTBDDs that represent the action rules become complex. Here, a method that uses MDDs, in which a single variable can take on multiple values, is proposed and experimental results are shown comparing MTBDDs and MDDs through simulations to acquire robot action rules.

In this paper, we introduce a method for generating a dynamic motion such that a two-wheeled inverted pendulum robot kicks a ball far away utilizing its own body dynamics while it keeps standing. Such a dynamic motion can be acquired through trial and error based on a reinforcement learning scheme. We utilize a simple policy gradient method to acquire a kicking motion which is designed by defining the desired parameters such as body angle, wheel angular velocity and so on. To show the validity of our approach, we perform computer simulation experiments of behavior acquisition for the two-wheeled inverted pendulum robot. Based our approach, we succeeded in acquiring the kicking motion of the two-wheeled inverted pendulum robot. A very interesting finding is: each of the acquired motions deviates from the desired trajectory, which is given by the human designer while keeping evaluation value of the acquired motion high.

Onomatopoeia refers to words that represent the sound, appearance, or voice of things, which makes it possible to create expressions that bring a scene to life in a subtle fashion. In this study, we propose an onomatopoeia thesaurus map to enable the construction of a map that visually confirms "similarity relationships between a number of onomatopoetic words" and "similarity relationships between unknown onomatopoetic words and existing onomatopoetic words", which are difficult to grasp from a conventional thesaurus. It is also possible to label objects with onomatopoetic words and visualize the similarity relationships between the objects on a map. In this paper, we introduce an example of labeling onomatopoetic words relating to the textures of sweets (desserts).

This paper presents a texture transfer that considers continuous structure of texture patches in target and source images. Previous texture transfers focus on local features, such as color distance, standard deviation and directional factors. In addition to those local factors it might be important and useful to use continuous structure of texture patches in the images of some cases. For instance, we aim at design of "Shodo" fonts based on examples. Shodo, the Japanese calligraphy, is a form of artistic writing used for writing the Japanese and Chinese language. This study proposes and develops a method of designing Japanese calligraphic fonts which contain artistic representations similar to actual Shodo art. Figure 1c illustrates our result which preserves the flow of salient brushwork of the source image (Figure 1a). On the other hand, Figure 1d, which is generated by the algorithm of Texture by numbers [Hertzmann et al. 2001], doesn't seem to express the flow of brushwork of the source. Our approach deals with the flow of brushwork as the continuous structure of texture patches. Our results could be preserve the continuous structure of source texture patches and express the artistic effect of brushwork.

Non-photorealistic rendering (NPR) is a technique used in the field of computer graphics. Here, we restrict our attention to the subset of NPR developed to synthesize drawing and painting techniques. Specifically, we focus on the style of Cubist art, such as the works of Picasso. First, we examine the actual works of Picasso in order to understand and improve the qualities of Cubist style rendering. As a result, the painting composition rules are expected to be extracted from the analysis of Picasso's works. In the present paper, we propose a Cubist style rendering based on the analysis of painting compositions. The present paper describes the proposed method by which to construct a painting composition database and illustrates the rules extracted from the database. We use rough set theory to extract the rules, and using these rules; we render and illustrate a sample image in Cubist style.

To improve face-to-face interaction with robots, we developed a model for generating interactive facial expressions by using a simple recurrent network (SRN). Conventional models for robot facial expression use predefined expressions, so only a limited number of expressions can be presented. This means that the expression may not match the interaction and that the person may find the expressions monotonous. Both problems can be overcome by generating expressions dynamically. We tested this model by incorporating it into a robot and comparing the expressions generated with those of a conventional model. The results demonstrated that using our model increases the diversity of face-to-face interaction with robots.

Some research has been conducted on applying coloration of painterly art to a photographic image. Most of the proposed methods use some absolute criteria, e.g., the nearest distance in CIEL*a*b* color space, converting a color to another uniquely. However, we think that basic color transfer depends on the subjective feelings and sensitivities of users themselves. We describe an algorithm where every user can produce an original color-transformed image resulting from two inputs, which are a target photograph and a reference painting. Our algorithm is based on interactive evolutionary computation (IEC) and can produce a variety of color-transformed images semi-automatically. Some color-transformed examples similar to reference paintings are illustrated, and the searching efficiency of our method is discussed.

Genetic algorithm (GA) is an effective method of solving combinatorial optimization problems. Generally speaking most of search algorithms require a large execution time in order to calculate some evaluation value, especially in real-world applications as well. Crossover is very important in GA because discovering a good solution efficiently requires that the good characteristics of the parent individuals be recombined. The multiple crossover per couple (MCPC) is a method that permits a number of children for each mating pair, and MCPC generates a huge amount of execution time to find a good solution. This paper proposes a novel approach to reduce time needed for fitness evaluation by "prenatal diagnosis" using fitness prediction. In the experiments based on actual problems, the proposed method found an optimum solution about 50% faster than the conventional method did. The experimental results from standard test functions show that the proposed method is applicable to other problem as well.

Thinning is a fundamental concept of computer processing of line images, and it plays an important role in pattern recognition. Most existing thinning algorithms have the problem to produce distorted skeletons. Some methods to correct the distorted skeleton have been proposed, but non of them produce complete results. In order to solve the problem, we propose an improved thinning algorithm which is a skeleton revision algorithm using maximal circles (SRAMCs). SRAMCs is a hybrid algorithm and the processing route is divided into three stages: 1) thinning using Hilditch algorithm; 2) removal of spurious pixels using maximal circle; and 3) skeleton reconstruction. The results of experiments indicates that SRAMCs can be useful for detection of lines and curves in digitized line images.