{"title":"INSPORAMA:基于特征的全景图像拼接中的ins辅助错位校正","authors":"Yuan Gao, Chenguang Wang, E. Chang","doi":"10.1109/ICMEW.2012.120","DOIUrl":null,"url":null,"abstract":"Feature-based image stitching, which aligns images with overlapping fields of view and then stitches them together, is a widely used panorama-construction technology. However, the current scale-, view- and illumination-invariant features can still result in misalignment because of occurrences of congruent or near-congruent features. We propose an INS (inertial navigation system) aided image-alignment method, named INSPORAMA, to reduce such misalignment. INSPORAMA improves image alignment accuracy by reducing both image area and the number of candidate feature-pairs to compare. Based on INSPORAMA, we have built an Android application, which is able to construct panoramic images in near real-time.","PeriodicalId":385797,"journal":{"name":"2012 IEEE International Conference on Multimedia and Expo Workshops","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2012-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"INSPORAMA: INS-Aided Misalignment Correction in Feature-Based Panoramic Image Stitching\",\"authors\":\"Yuan Gao, Chenguang Wang, E. Chang\",\"doi\":\"10.1109/ICMEW.2012.120\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Feature-based image stitching, which aligns images with overlapping fields of view and then stitches them together, is a widely used panorama-construction technology. However, the current scale-, view- and illumination-invariant features can still result in misalignment because of occurrences of congruent or near-congruent features. We propose an INS (inertial navigation system) aided image-alignment method, named INSPORAMA, to reduce such misalignment. INSPORAMA improves image alignment accuracy by reducing both image area and the number of candidate feature-pairs to compare. Based on INSPORAMA, we have built an Android application, which is able to construct panoramic images in near real-time.\",\"PeriodicalId\":385797,\"journal\":{\"name\":\"2012 IEEE International Conference on Multimedia and Expo Workshops\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-07-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 IEEE International Conference on Multimedia and Expo Workshops\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICMEW.2012.120\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 IEEE International Conference on Multimedia and Expo Workshops","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMEW.2012.120","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
INSPORAMA: INS-Aided Misalignment Correction in Feature-Based Panoramic Image Stitching
Feature-based image stitching, which aligns images with overlapping fields of view and then stitches them together, is a widely used panorama-construction technology. However, the current scale-, view- and illumination-invariant features can still result in misalignment because of occurrences of congruent or near-congruent features. We propose an INS (inertial navigation system) aided image-alignment method, named INSPORAMA, to reduce such misalignment. INSPORAMA improves image alignment accuracy by reducing both image area and the number of candidate feature-pairs to compare. Based on INSPORAMA, we have built an Android application, which is able to construct panoramic images in near real-time.