{"title":"评估基于实例的地形合成中的真实感","authors":"Joshua J. Scott, Neil A. Dodgson","doi":"https://dl.acm.org/doi/10.1145/3531526","DOIUrl":null,"url":null,"abstract":"<p>We report two studies that investigate the use of subjective believability in the assessment of objective realism of terrain. The first demonstrates that there is a clear subjective feature bias that depends on the types of terrain being evaluated: Our participants found certain natural terrains to be more believable than others. This confounding factor means that any comparison experiment must not ask participants to compare terrains with different types of features. Our second experiment assesses four methods of example-based terrain synthesis, comparing them against each other and against real terrain. Our results show that, while all tested methods can produce terrain that is indistinguishable from reality, all also can produce poor terrain; that there is no one method that is consistently better than the others; and that those who have professional expertise in geology, cartography, or image analysis are better able to distinguish real terrain from synthesized terrain than the general population, but those who have professional expertise in the visual arts are not.</p>","PeriodicalId":50921,"journal":{"name":"ACM Transactions on Applied Perception","volume":"53 2","pages":""},"PeriodicalIF":1.9000,"publicationDate":"2022-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Evaluating Realism in Example-based Terrain Synthesis\",\"authors\":\"Joshua J. Scott, Neil A. Dodgson\",\"doi\":\"https://dl.acm.org/doi/10.1145/3531526\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>We report two studies that investigate the use of subjective believability in the assessment of objective realism of terrain. The first demonstrates that there is a clear subjective feature bias that depends on the types of terrain being evaluated: Our participants found certain natural terrains to be more believable than others. This confounding factor means that any comparison experiment must not ask participants to compare terrains with different types of features. Our second experiment assesses four methods of example-based terrain synthesis, comparing them against each other and against real terrain. Our results show that, while all tested methods can produce terrain that is indistinguishable from reality, all also can produce poor terrain; that there is no one method that is consistently better than the others; and that those who have professional expertise in geology, cartography, or image analysis are better able to distinguish real terrain from synthesized terrain than the general population, but those who have professional expertise in the visual arts are not.</p>\",\"PeriodicalId\":50921,\"journal\":{\"name\":\"ACM Transactions on Applied Perception\",\"volume\":\"53 2\",\"pages\":\"\"},\"PeriodicalIF\":1.9000,\"publicationDate\":\"2022-09-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACM Transactions on Applied Perception\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/https://dl.acm.org/doi/10.1145/3531526\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"COMPUTER SCIENCE, SOFTWARE ENGINEERING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM Transactions on Applied Perception","FirstCategoryId":"94","ListUrlMain":"https://doi.org/https://dl.acm.org/doi/10.1145/3531526","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, SOFTWARE ENGINEERING","Score":null,"Total":0}
Evaluating Realism in Example-based Terrain Synthesis
We report two studies that investigate the use of subjective believability in the assessment of objective realism of terrain. The first demonstrates that there is a clear subjective feature bias that depends on the types of terrain being evaluated: Our participants found certain natural terrains to be more believable than others. This confounding factor means that any comparison experiment must not ask participants to compare terrains with different types of features. Our second experiment assesses four methods of example-based terrain synthesis, comparing them against each other and against real terrain. Our results show that, while all tested methods can produce terrain that is indistinguishable from reality, all also can produce poor terrain; that there is no one method that is consistently better than the others; and that those who have professional expertise in geology, cartography, or image analysis are better able to distinguish real terrain from synthesized terrain than the general population, but those who have professional expertise in the visual arts are not.
期刊介绍:
ACM Transactions on Applied Perception (TAP) aims to strengthen the synergy between computer science and psychology/perception by publishing top quality papers that help to unify research in these fields.
The journal publishes inter-disciplinary research of significant and lasting value in any topic area that spans both Computer Science and Perceptual Psychology. All papers must incorporate both perceptual and computer science components.