{"title":"进化艺术中的混合媒介","authors":"Jordan Maslen, B. Ross","doi":"10.1109/CEC55065.2022.9870271","DOIUrl":null,"url":null,"abstract":"Mixed media in the real world involves the creation of works of art that creatively combine a variety of media on the canvas, for example, watercolour, acrylic paint, and photographs. We present an evolutionary art system that implements a digital version of mixed media. A genetic programming system uses a language that renders different digital effects on a canvas. Each rendered effect takes the form of an “art object”, and the tree defines a s et o fa rt o bjects that together comprise a final rendered image. Available effects include procedural images (textures), image filters, and bitmaps. A n art o bject is rendered onto the canvas via a pre-defined mask shape, which c an range from simple geometric shapes such as circles or squares, to com-plex paintbrush strokes and paint splatters. Fitness evaluation measures the pixel-by-pixel colour distance between a rendered canvas and an input target image, which acts as a compositional guide for rendered images. Various runs of the system have produced an interesting variety of stylized, mixed-effect results, often appearing as abstract “glitchy” interpretations of target images.","PeriodicalId":153241,"journal":{"name":"2022 IEEE Congress on Evolutionary Computation (CEC)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Mixed Media in Evolutionary Art\",\"authors\":\"Jordan Maslen, B. Ross\",\"doi\":\"10.1109/CEC55065.2022.9870271\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Mixed media in the real world involves the creation of works of art that creatively combine a variety of media on the canvas, for example, watercolour, acrylic paint, and photographs. We present an evolutionary art system that implements a digital version of mixed media. A genetic programming system uses a language that renders different digital effects on a canvas. Each rendered effect takes the form of an “art object”, and the tree defines a s et o fa rt o bjects that together comprise a final rendered image. Available effects include procedural images (textures), image filters, and bitmaps. A n art o bject is rendered onto the canvas via a pre-defined mask shape, which c an range from simple geometric shapes such as circles or squares, to com-plex paintbrush strokes and paint splatters. Fitness evaluation measures the pixel-by-pixel colour distance between a rendered canvas and an input target image, which acts as a compositional guide for rendered images. Various runs of the system have produced an interesting variety of stylized, mixed-effect results, often appearing as abstract “glitchy” interpretations of target images.\",\"PeriodicalId\":153241,\"journal\":{\"name\":\"2022 IEEE Congress on Evolutionary Computation (CEC)\",\"volume\":\"13 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-07-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 IEEE Congress on Evolutionary Computation (CEC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CEC55065.2022.9870271\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE Congress on Evolutionary Computation (CEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CEC55065.2022.9870271","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Mixed media in the real world involves the creation of works of art that creatively combine a variety of media on the canvas, for example, watercolour, acrylic paint, and photographs. We present an evolutionary art system that implements a digital version of mixed media. A genetic programming system uses a language that renders different digital effects on a canvas. Each rendered effect takes the form of an “art object”, and the tree defines a s et o fa rt o bjects that together comprise a final rendered image. Available effects include procedural images (textures), image filters, and bitmaps. A n art o bject is rendered onto the canvas via a pre-defined mask shape, which c an range from simple geometric shapes such as circles or squares, to com-plex paintbrush strokes and paint splatters. Fitness evaluation measures the pixel-by-pixel colour distance between a rendered canvas and an input target image, which acts as a compositional guide for rendered images. Various runs of the system have produced an interesting variety of stylized, mixed-effect results, often appearing as abstract “glitchy” interpretations of target images.