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14th International Conference on genetic and Evolutionary Computation Conference (GECCO)

作者： Yoon, Du-Mim Kim, Kyung-Joong Sejong Univ Dept Comp Engn Seoul South Korea

ISBN: (纸本)9781450311786

interactive evolutionary computation (IEC) is a useful tool to automate human's creative process such as image drawing, music composition, and so on. In this paper, we apply the IEC to generate a new image from the original one using a set of filters. In professional image editing software, there provides us with a lot of filters and sometimes the sequential use of several filters produces interesting results. Usually, searching for the useful combination of filters is a kind of trial-and-error tasks. Or, only experts can define a good combination of filters from their long experience. In this work, our system incrementally adds or deletes filters based on user's evaluation on the results of image retouching. Recently, people take photos using their smartphones and it is not a trivial to give a number of consecutive evaluations to guide the IEC search. Based on the observation, we try to compare several scoring methods for the IEC to get the best results for the image retouching system. They are a simple binary scoring (Good & Bad), discrete multiple choices (Five Star), and real-valued scoring (Slider). Experimental results on five human subjects show that the Good & Bad is appropriate for the retouching system.

关键词： interactive genetic algorithm Scoring method Photo retouching Variable-length genetic algorithm Subject test Personal photo Image filters GIMP

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Generating Facial Images for Steganography Based on IGA and Image Morphing

Generating Facial Images for Steganography Based on IGA and ...

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IEEE International Conference on Systems, Man, and Cybernetics (SMC)

作者： Zhao, Qiangfu Akatsuka, Mayuko Hsieh, Cheng-Hsiung Univ Aizu Dept Comp & Informat Syst Aizu Wakamatsu Fukushima Japan Chaoyang Univ Technol Dept Comp Sci & Informat Engn Taichung Taiwan

ISBN: (纸本)9781467317146

In our earlier study, we proposed an image morphing based method for information hiding. The basic idea is to hide a secrete image into a morphed image which is obtained from the secrete image and another reference image. To make this method practically useful, it is necessary to produce natural morphed images. This is a necessary condition conceal the existence of the secret image. To produce natural morphed images, we should choose a proper feature point set (FPS) for morphing. This is a tedious work if we do it manually, because the number of possible FPSs is very large. To solve the problem more efficiently, we adopted interactive genetic algorithm (IGA) in this study and conducted experiments for generating facial images. Results show that, if we provide a relatively good initial FPS, IGA can fine-tune the FPS, and produce more natural facial images with limited number of evaluations.

关键词： Information hiding steganography image morphing de-morphing interactive genetic algorithm

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Development and evaluation of an interactive texture design method

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COMPUTER SYSTEMS SCIENCE AND ENGINEERING 2012年第1期27卷 63-71页

作者： Kagawa, Tsuneo Nishino, Hiroaki Utsumiya, Kouichi Oita Univ Dept Comp Sci & Intelligent Syst Oita 8701192 Japan

Texture mapping is widely used to improve the visual richness of surface appearances for 3D computer graphics models. Texture pattern design is a problem for finding an appropriate pattern fitting in a 3D scene physically and psychologically. Therefore, supporting intuitive and simple method for texture pattern designing is an important research issue. This paper proposes an interactive texture design method for easily obtaining appropriate texture patterns. We apply an interactive genetic algorithm (iGA) framework to find the pleasant color texture pattern for 3D model surfaces. This method automatically generates multiple texture patterns through various image editing operations and allows the users to sensitively evaluate them. It supplies a powerful function for texture design support. We also propose a user interface appropriate for the iGA framework with a touch panel.

关键词： Texture mapping interactive genetic algorithm Image processing

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Tournament Evaluation System Applying Win-Lose Result Presumption Considering Kansei Evaluation by Multiple People

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JOURNAL OF ADVANCED COMPUTATIONAL INTELLIGENCE AND INTELLIGENT INFORMATICS 2012年第3期16卷 453-461页

作者： Takenouchi, Hiroshi Tokumaru, Masataka Muranaka, Noriaki Kansai Univ Grad Sch Sci & Engn 3-3-35 Yamate Cho Suita Osaka 5648680 Japan Kansai Univ Fac Engn Sci Suita Osaka 5648680 Japan

We describe an interactive genetic algorithm (IGA) with tournament evaluation for applying win-lose results obtained from an evaluation using multiple people. In our previous study, we developed an IGA with tournament evaluation as a basic model for evaluating candidate solutions using votes from multiple people [13]. However, tournament evaluation requires that IGA users evaluate the same candidate solution multiple times. Therefore, our previous method can reduce a user's motivation for evaluating the solution. In addition, the number of users participating in a vote may decrease because of the decreased motivation to evaluate. To overcome this difficulty, we propose the application of a win-lose result presumption based on the tournament evaluation records of multiple people. When a system-based presumption is possible, the win-lose result presumption automatically determines the preferred and non-preferred candidates in each round. This method can reduce the number of times that users need to evaluate the same candidate solution. The effectiveness of the proposed method is verified using a numerical simulation that employs multiple numerical evaluation agents instead of human evaluators. The simulation results show an initial convergent improvement with the proposed method.

关键词： interactive genetic algorithm tournament evaluation win-lose result presumption

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Large population size IGA with individuals' fitness not assigned by user

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APPLIED SOFT COMPUTING 2011年第1期11卷 936-945页

作者： Gong, Dunwei Yuan, Jie China Univ Min & Technol Sch Informat & Elect Engn Xuzhou 221008 Jiangsu Peoples R China

User fatigue problem in traditional interactive genetic algorithms restricts the population size. It is necessary to maintain large population size in order to apply these algorithms to optimize complicated problems. We present a large population size interactive genetic algorithm with an individual's fitness not assigned by the user in this paper. The algorithm divides a population into several clusters, and the maximum number of clusters is changeable with the evolution and the distribution of the population. A user only evaluates one representative individual in each cluster, and others' fitness are estimated based on these representative ones. In addition, to assign a representative individual's fitness, we record time when the user evaluates it satisfactory or unsatisfactory according to his/her sensibility, and its fitness is automatically calculated based on the time. Finally, we apply the proposed algorithm in a fashion evolutionary design system, and compare it with other two IGAs each of which has one aspect, including the population size and the evaluation method, the same as the proposed algorithm. The experimental results validate its efficiency. (c) 2010 Elsevier B. V. All rights reserved.

关键词： Optimization genetic algorithm interactive genetic algorithm Cluster User fatigue

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Automatic Generation Method to derive for the design variable spaces for interactive genetic algorithms

Automatic Generation Method to derive for the design variabl...

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2010 IEEE World Congress on Computational Intelligence

作者： Tanaka, Misato Hiroyasu, Tomoyuki Miki, Mitsunori Sasaki, Yasunari Yoshimi, Masato Yokouchi, Hisatake Doshisha Univ Dept Life & Med Sci Kyoto 6100321 Japan Doshisha Univ Dept Sci & Engn Kyoto 6100321 Japan

ISBN: (纸本)9781424481262

In the growing E-commerce market, many online shopping sites have adopted product recommendation systems to expand their business opportunities. We have focused on iGA (interactive genetic algorithm) as a solution to product recommendation algorithms. Although iGA is an optimization technique for user's preference through the interaction between systems and users, iGA requires extraction of design variables to apply the product recommendation. Extracting design variables from existing products by hand is unrealistic because there are a wide variety of products on shopping sites that are updated rapidly. To address this problem, we have proposed an automatic generation method of a design variable space based on the collective preference data on the web. In this paper, we introduce several design variable spaces generated by books on Amazon, which maintain recommendation relations among products. The distributions of books generated by the proposed method are influenced by their authors. Then, subjective experiments confirmed that test subjects searched solutions by their unique preference.

关键词： Internet automatic generation method design variable space e-commerce market electronic commerce iGA interactive genetic algorithm online shopping sites product recommendation systems recommender systems retail data processing

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Product Form Design Based on Neural Network and genetic algorithm

Product Form Design Based on Neural Network and Genetic Algo...

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International Conference on Components, Packaging and Manufacturing Technology

作者： Yang, Cheng Wu, Qun Wu, Jianfeng Zhejiang Univ City Coll Hangzhou 310003 Zhejiang Peoples R China Zhejiang Univ Coll Comp Hangzhou 310003 Zhejiang Peoples R China

ISBN: (纸本)9780878492138

A method of product innovation design was presented. Based on product gene and interactive genetic algorithm, designs of products evolved into new programs, with which make customers be satisfied. In the evolutionary process, a similar model, which was made by neural network learning, was used to evaluate the fitness of products. This method not only shortened the time which was taken in the process of evolution, but also to avoid the decline in the quality of evaluations which resulted from the mental fatigue of user, and ensured the accuracy of the solution.

关键词： Product form interactive genetic algorithm Evolution Neural network

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interactive genetic algorithms with Individual's Fuzzy and Stochastic Fitness

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CHINESE JOURNAL OF ELECTRONICS 2009年第4期18卷 619-624页

作者： Sun Xiaoyan Gong Dunwei China Univ Min & Technol Sch Informat & Elect Engn Xuzhou 221116 Peoples R China

We presented a novel interactive genetic algorithm to effectively characterize a user's cognition on the evaluated objects and the stochastic phenomena in the evolutionary process. A fuzzy number is adopted to express an individual's fitness to reflect a user's cognition, and a stochastic variable with normal distribution to depict the stochastic behavior in the fitness based on the error theory. The fuzzy number and the stochastic variable are transformed into different intervals with A cut set level and confidence level, respectively, and different individuals in the same generation are compared based on interval dominance. The values of A and stochastic parameter are determined according to the uncertainty degree of a user's cognition which is quantitatively described with the fuzzy entropy of a fuzzy number. Finally, the algorithm was applied to a fashion evolutionary design system and the experimental results show its rationality and efficiency.

关键词： interactive genetic algorithm Cognitive uncertainty Fuzzy number Stochastic variable Interval dominance

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Impact of Individuals' Fitness Expressions on interactive genetic algorithms' Performances

Impact of Individuals' Fitness Expressions on Interactive Ge...

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21st Chinese Control and Decision Conference

作者： Gong, Dun-wei Yuan, Jie China Univ Min & Technol Sch Informat & Elect Engn Xuzhou 221116 Peoples R China

ISBN: (纸本)9781424427239

interactive genetic algorithms involve a user to evaluate an individual's fitness. So far, there have been many expressions of an individual's fitness, but no mature result of their influences on IGAs' performances has come out. We review 5 representative fitness expressions in this paper, i.e. precise fitness, discrete fitness, interval fitness, fuzzy fitness, as well as the fitness not directly assigned by the user. Establishing a RGB Color evolutionary system to collect data and based on many statistical methods, we analyze the impact of the above fitness expressions on interactive genetic algorithms' performances in detail, and make a research on the user's satisfaction degree. The achievements in this paper provide a foundation for choosing an appropriate fitness expression in real-world applications.

关键词： genetic algorithm interactive genetic algorithm Fitness Expression

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Rhythm Generation Method for Automatic Musical Composition Using genetic algorithm

Rhythm Generation Method for Automatic Musical Composition U...

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2010 IEEE World Congress on Computational Intelligence

作者： Maeda, Yoichiro Kajihara, Yusuke Univ Fukui Dept Human & Artificial Intelligent Syst Grad Sch Engn Fukui 9108507 Japan

ISBN: (纸本)9781424469208

In recent years, genetic algorithm (GA) and interactive genetic algorithm (IGA) are usually used for the sound generation process in the field of computer music. However, it is difficult to just handle these methods directly for the music composition. In this research we have already proposed a music composition system based on the Twelve-tone Technique which uses twelve notes of the chromatic scale equally and composes the music step by step. We have designed the fitness function based on the relation between the consonant interval and dissonant interval that are a part of general musical theory and performed the automatic generation of twelve-tone row by searching the consonant tone row with GA. In the next step, we design a fitness function for evaluating the rhythm that we defined. In this paper, we propose an automatic rhythm generation method and try to obtain the musical rhythm using GA.

关键词： IGA automatic musical composition chromatic scale computer music consonant interval dissonant interval fitness function genetic algorithms interactive genetic algorithm music musical theory rhythm generation method sound generation process twelve-tone technique

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