A human interface to search and draw facial images in mind by using psychometrical space model of faces

Sugimoto, Futoshi; Honda, Nakaji

doi:10.1109/fuzzy.1999.790141

Cited by 7 publications

(4 citation statements)

References 6 publications

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“…Generating faces of line drawing was frequently used as a research task of the IEC [8], [9], [118], [119], [130], [131], [184], [185], [54], [186]. One of such researches is autofitness assignment to accelerate EC convergence by estimating fitness values using Euclidian distance from individuals [118], [119] and positional relationship with userselected individuals [130], [131], [184], [185], [54], [186] (c.f. section IV-C).…”

Section: G Face Image Generationmentioning

confidence: 99%

“…One simple idea is to assign a same bias fitness values to the unselected individuals; another is to measure the Euclidian distances among chromosomes for them [54]; the other is to use approximate reasoning to predict their bias fitness values from the selected individuals [130], [131]. Further improvement for the IEC-based cartoon face drawing system is to measure the distances not in a phenotype space, face parameter space, but in a psychological space constructed by the multidimensional scaling method [184], [185], [186].…”

Section: Prediction Of Fitness Valuesmentioning

confidence: 99%

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Interactive evolutionary computation: fusion of the capabilities of EC optimization and human evaluation

2001

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We overview the research on interactive evolutionary computation (IEC). The IEC is an EC that optimizes systems based on human subjective evaluation. First, the definition and features of the IEC are described. Then, the overview of the IEC research follows. The overview consists of two parts: application and interface researches. The IEC application fields in this survey include graphic art and animation, 3-D CG lighting, music, editorial design, industrial design, face image generation, speech processing and synthesis, hearing aid fitting, virtual reality, media database retrieval, data mining, image processing, control and robotics, food industry, geophysics, education, entertainment, and so on. The interface research to reduce human fatigue in this survey includes interfaces of fitness input and display based on fitness prediction, accelerating EC convergence especially in early EC generations, combinations of interactive and normal ECs, and active user intervention. Finally, we discuss the IEC from the point of the future research direction of computational intelligence. The biggest feature of this paper is to wholly survey them with 200 IEC papers rather than to carefully select representative papers to show the status quo of the IEC researches.

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Section: G Face Image Generationmentioning

confidence: 99%

Section: Prediction Of Fitness Valuesmentioning

confidence: 99%

Interactive evolutionary computation: fusion of the capabilities of EC optimization and human evaluation

2001

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“…Futoshi Sugimoto et al [4] presented drawing of a facial image in users mind using psychometric space model of the face. An image in user mind represented as psychological space model and image sketch considered into the different model of drawing.…”

Section: Related Workmentioning

confidence: 99%

Untitled

2016

IJSC

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“…In such cases an Interactive Genetic Algorithm, which is a GA based system that uses human evaluation, has been shown to be useful in many areas such as face recognition [15], music [16] [17], architecture [18], fashion design [19] …”

Section: Genetic Terrain Generationmentioning

confidence: 99%

Terrain generation using an Interactive Genetic Algorithm

Walsh

Gade

2010

IEEE Congress on Evolutionary Computation

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This paper introduces the Auto Terrain Generation System (ATGS), which is based on an Interactive Genetic Algorithm (IGA) that enables non-specialist users to rapidly generate terrains. The motivation for using an IGA is discussed, existing terrain generation techniques are described and a new approach, based on a fractal terrain engine, is outlined. Graphics engines allow terrains to be specified with over 800 floating point parameters, which can overwhelm nonspecialist users. These parameters also create a vast search space for auto-terrain generation systems that can complicate procedural techniques. ATGS addresses these issues via interaction with the user, which is implemented in ATGS by a web based user interface that allows users to rapidly indicate terrain preferences. These user preferences are used by a genetic algorithm to explore a multi-dimensional parameter space that satisfies the user's intuition and aesthetics. Proof of concept experiments are outlined, results are presented and future research work is projected.

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A human interface to search and draw facial images in mind by using psychometrical space model of faces

Cited by 7 publications

References 6 publications

Interactive evolutionary computation: fusion of the capabilities of EC optimization and human evaluation

Interactive evolutionary computation: fusion of the capabilities of EC optimization and human evaluation

Untitled

Terrain generation using an Interactive Genetic Algorithm

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