{"title":"利用遗传算法增强目标的显著性","authors":"R. Pal, Dipanjan Roy","doi":"10.1109/CRV.2017.33","DOIUrl":null,"url":null,"abstract":"It is often required to emphasize an object in an image. Artists, illustrators, cinematographers and photographers have long used the principles of contrast and composition to guide visual attention. In order to achieve this, a novel perceptually-driven approach is put forth which leads to the enhancement of visual saliency of target object without destroying the naturalness of the contents of the image. The proposed approach computes new feature values for the intended object by maximizing the feature dissimilarity (which is weighted by positional proximity) with other objects. Too much change in feature values in the target segment may destroy naturality of the image. This poses as the constraint in the proposed maximization problem. Genetic algorithm has been used, in this context, to find the feature values which maximize the saliency of the target object. Experimental validation through objective evaluation metrics using saliency maps, as well as analysis of eye-tracking data, establish the success of the proposed method.","PeriodicalId":308760,"journal":{"name":"2017 14th Conference on Computer and Robot Vision (CRV)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Enhancing Saliency of an Object Using Genetic Algorithm\",\"authors\":\"R. Pal, Dipanjan Roy\",\"doi\":\"10.1109/CRV.2017.33\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"It is often required to emphasize an object in an image. Artists, illustrators, cinematographers and photographers have long used the principles of contrast and composition to guide visual attention. In order to achieve this, a novel perceptually-driven approach is put forth which leads to the enhancement of visual saliency of target object without destroying the naturalness of the contents of the image. The proposed approach computes new feature values for the intended object by maximizing the feature dissimilarity (which is weighted by positional proximity) with other objects. Too much change in feature values in the target segment may destroy naturality of the image. This poses as the constraint in the proposed maximization problem. Genetic algorithm has been used, in this context, to find the feature values which maximize the saliency of the target object. Experimental validation through objective evaluation metrics using saliency maps, as well as analysis of eye-tracking data, establish the success of the proposed method.\",\"PeriodicalId\":308760,\"journal\":{\"name\":\"2017 14th Conference on Computer and Robot Vision (CRV)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-05-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 14th Conference on Computer and Robot Vision (CRV)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CRV.2017.33\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 14th Conference on Computer and Robot Vision (CRV)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CRV.2017.33","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Enhancing Saliency of an Object Using Genetic Algorithm
It is often required to emphasize an object in an image. Artists, illustrators, cinematographers and photographers have long used the principles of contrast and composition to guide visual attention. In order to achieve this, a novel perceptually-driven approach is put forth which leads to the enhancement of visual saliency of target object without destroying the naturalness of the contents of the image. The proposed approach computes new feature values for the intended object by maximizing the feature dissimilarity (which is weighted by positional proximity) with other objects. Too much change in feature values in the target segment may destroy naturality of the image. This poses as the constraint in the proposed maximization problem. Genetic algorithm has been used, in this context, to find the feature values which maximize the saliency of the target object. Experimental validation through objective evaluation metrics using saliency maps, as well as analysis of eye-tracking data, establish the success of the proposed method.