{"title":"基于相关性的高分辨率卫星图像目标定位注意机制","authors":"Phool Preet, P. Chowdhury, G. S. Malik","doi":"10.1109/NCVPRIPG.2013.6776221","DOIUrl":null,"url":null,"abstract":"Attentional Mechanism or Focus of Attention is the front end of object recognition systems with the task of rapidly reducing the search area in the image. In this paper we present correlation based template matching as an attentional mechanism for high resolution satellite images. We experimentally show that despite intra-class variations and object transformations, correlation based template matching can be deployed as attentional mechanism. Different image variants like gradient magnitude and gradient orientation are also compared for correlation matching. Based on the experiments a threshold selection mechanism is given.","PeriodicalId":436402,"journal":{"name":"2013 Fourth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Correlation based object-specific attentional mechanism for target localization in high resolution satellite images\",\"authors\":\"Phool Preet, P. Chowdhury, G. S. Malik\",\"doi\":\"10.1109/NCVPRIPG.2013.6776221\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Attentional Mechanism or Focus of Attention is the front end of object recognition systems with the task of rapidly reducing the search area in the image. In this paper we present correlation based template matching as an attentional mechanism for high resolution satellite images. We experimentally show that despite intra-class variations and object transformations, correlation based template matching can be deployed as attentional mechanism. Different image variants like gradient magnitude and gradient orientation are also compared for correlation matching. Based on the experiments a threshold selection mechanism is given.\",\"PeriodicalId\":436402,\"journal\":{\"name\":\"2013 Fourth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG)\",\"volume\":\"18 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 Fourth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NCVPRIPG.2013.6776221\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 Fourth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NCVPRIPG.2013.6776221","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Correlation based object-specific attentional mechanism for target localization in high resolution satellite images
Attentional Mechanism or Focus of Attention is the front end of object recognition systems with the task of rapidly reducing the search area in the image. In this paper we present correlation based template matching as an attentional mechanism for high resolution satellite images. We experimentally show that despite intra-class variations and object transformations, correlation based template matching can be deployed as attentional mechanism. Different image variants like gradient magnitude and gradient orientation are also compared for correlation matching. Based on the experiments a threshold selection mechanism is given.