Masataka Tokumaru

Color design support system considering color harmony

Color design is very important for a product design. In this paper, we propose a system which aims to support such a color design. Proposed system is composed of 5 parts, such as the part which evaluates the harmony of colors, the color combining part, color scheme image judging part, image word output part and lastly image comparison part. First, the system requires the user to input a color and his preferring image of color scheme including his inputting color with image keyword. Next, the system selects colors from the Munsell color database, which are in harmony with the color inputted into the system. Then, the system builds color schemes to combine the color inputted by the user with the colors selected from the database by the system. Finally, images of the color schemes are evaluated and outputted the color combinations whose images accord with the image keyword which the user inputs into the system. Experimental result shows that effective judgments of color harmony and color image are executed and we can get some good color schemes by the system.

Design support system with votes from multiple people using digital signage

We propose a system to create designs that reflect multiple user preferences obtained by voting using digital signage. When creating such designs, it is important to collect a significant number of user opinions and adopt them in the designs. However, as the number of users increases, the collection of opinions becomes more difficult. We propose an interactive evolutionary computation system using digital signage. This system presents several designs. Each user evaluates the designs by voting. In other words, this system obtains the preferences of multiple users by voting and uses the preferences to evaluate designs. Therefore, the proposed system can create designs that please multiple users. In our previous research, we proposed a paired comparison voting (PCV) method that obtains preferences from multiple users by voting and confirmed the effectiveness of the method by simulation. Here, we construct a system using the PCV method and digital signage to demonstrate its effectiveness with real users. The proposed system uses the PCV method to create designs. The experimental results show that the designs generated by the proposed system converged visually and genetically. As a result, we verified that the proposed system creates designs reflecting the preferences of multiple people.

Signboard design system through social voting technique

We propose a signboard design system with votes by multiple people. When determining a signboard design with many people, it is important that local residents agree on a single signboard design. Therefore, we created a signboard design system that determines the design by popularity using an evolutionary computation algorithm to finalize the design. We have proposed a paired comparison voting method (PCV) that allows several thousand unspecified users to participate in the evaluation of candidate solutions. Specifically, the PCV method considers multiple opinion from the Internet votes to evaluate candidate solutions, accepting votes made during a defined time parameter. In our previous study, we confirmed the effectiveness of the PCV method by numerical simulations using evaluation agents that imitate human sensitivity. In this paper, we demonstrate its effectiveness for real users using a signboard design system. The system helps users to create a signboard design by considering the suitability of the grain pattern, background and character colors, and the signboards environment. The experimental results showed that the PCV method can reduce the load on users and produce a suitable and satisfactory design, verifying the effectiveness of the PCV method for real users.

Interactive tabu search vs. interactive genetic algorithm

We propose an interactive tabu search (ITS) to be used for the development support of a product that fits a humans feeling. Interactive evolutionary computation (IEC) is one of the technologies used in the development support of products that fit a humans feeling using a computer and person undergoing a communication. The interactive generic algorithm (IGA) is generally used in the IEC. A major problem with the use of the IEC is the increased burden on the IEC user to evaluate multiple solution candidates. Using the ITS instead of the IGA may reduce this burden, because the ITS user chooses only his most favorite solution candidate among multiple solution candidates. We performed a comparison of the search performance using simulations with the ITS and IGA. As a result of this simulation, the search performance of the ITS exceeded that of the IGA by a range from 2% to 10%.

An evolutionary fuzzy color emotion model for coloring support systems

In this study, we improved the coloring support system that was proposed in our previous research. The previous system could advise color combinations for clothing. The user enters some emotional keywords, such as ldquocasualrdquo and ldquopretty,rdquo which are impressions put forth by colors, and the system retrieves color combinations that seem to suit the keyword from a color database. The proposed system has many fuzzy color emotion models, which are controlled by parameters for defining membership functions or fuzzy rules. These models are evolved using interactive genetic algorithms, to adapt them to the userpsilas particular emotional responses, because human reactions vary for each individual. This paper proposes a method for the advanced evolution of the fuzzy color emotion model. This method supports co-evaluation of color combinations, which exhibits a better performance in evolving models compared to the previous method.

A Support System for Healthy Eating Habits: Optimization of Recipe Retrieval

In this paper, we propose a support system for healthy eating habits. Current methods of recipe retrieval generally rely on keywords or popularity. However, such approaches offer the same results to different users. In order to resolve this issue, we have developed a support system that incorporates nutritional management and preferential retrieval. In the preferential retrieval system, a recommender agent takes account of user tastes to extract and present menus. The user then, evaluates the menus recommended by various agents. Each recommender agents evolves on the basis of these menu appraisals. Over time, the preferences of the agents become similar to those of the users, resulting in menus that correspond to user tastes. This study thus utilizes an interactive immune algorithm (IIA) to optimize the preferential retrieval system. We tested the proposed system with a simulated user but genuine recipe data.

An emotion-generation model for a robot that reacts after considering the dialogist

This paper proposes an emotion-generation model for a robot that distinguishes different aspects of a humans personality. The robot reacts differently, depending on the human communication it receives. In this cutting-edge research area, several studies have demonstrated robots that generate reactions to humans by judging their interaction. However, these reactions do not change when the communicating human displays a variety of personality traits. This is because the robot only responds to the input without taking the humans personality into account. To solve this issue, we propose an emotion-generation model for robots that produces different reactions depending on the human communication it receives. In this model, the robot has a degree of intimacy that judges the humans personality. The degree of intimacy increases when the human satisfies the robots desire and decreases when he/she does not. The simulation results confirmed that the robot shows a friendly reaction to a human with a high degree of intimacy and an unfriendly reaction to one with a low degree of intimacy.

Developing Sophisticated Robot Reactions by Long-Term Human Interaction

In this study, we proposed an emotion generation model for robots that considers mutual effects of desires and emotions. Many researchers are developing partner robots for communicating with people and entertaining them, rather than for performing practical functions. However, people quickly grow tired of these robots owing to their simplistic emotional responses. To solve this issue, we attempted to implement the mutual effects of desires and emotions using internal-states, such as physiological factors. Herein, the simulation results verified that the proposed model expresses complex emotions similar to humans. The results confirmed that the emotions expressed by the proposed model are more complex and realistic than those expressed by a reference model.

Clothing image retrieval based on a similarity evaluation method for Kansei retrieval system

This paper proposes a similar image retrieval for the Kansei retrieval. The Kansei retrieval system is designed to search for users clothing articles by considering their Kansei. The system adopts a Kansei retrieval agent. The agent identifies userss choice of clothing by imitating their Kansei. However, the agents structure can become excessively complicated because considerable information is potentially available. Therefore, a Kansei retrieval system needs to utilizes similar image retrieval. Similar image retrieval searches for a clothing image on the basis of clothing images. Clothing design contains less information than clothing image. A design includes features intended to create a general impression of piece of clothing. In addition, the Kansei retrieval agent evaluates the design, and searches for the designs that a user likes on the basis of the evaluation. Therefore, the agents structure does not become complicated. In this study, we created a similar image retrieval application and verified it effectiveness. The application searches for clothing images on the basis of the design that a user chooses. The results show that similar image retrieval can identify clothing images similar to the design. Thus, the effectiveness of the proposed similar image retrieval system was confirmed.

Interactive Evolutionary Computation Using Multiple Users’ Gaze Information

We propose an interactive evolutionary computation (IEC) method that uses the gaze information of multiple users to reduce user evaluation loads. The IEC method employs user sensitivity to evaluate candidate solutions of evolutionary computation. However, IEC has a problem that user evaluation loads of candidate solutions are large. To solve this problem, some researchers have proposed various methods using a simple evaluation of candidate solutions or biological information. Therefore, we use the gaze information of users to evaluate candidate solutions in IEC. By using gaze information, the system can reduce the user evaluation load without the need for users to wear a special measuring device. We created a women’s clothing coordination system using IEC with gaze information. We conducted an evaluation experiment to verify the effectiveness of the proposed system. The experimental results show that the proposed system is effective for incorporating users’ gaze information into IEC evaluation.