{"title":"Image sequence processing applied to autonomous aerial navigation","authors":"A. Canhoto, E. H. Shiguemori, M. Domiciano","doi":"10.1109/ICSIPA.2009.5478706","DOIUrl":null,"url":null,"abstract":"Template matching in real-time is a fundamental issue in many applications in computer vision such as tracking, stereo vision and autonomous navigation. The goal of this paper is to present a system for automatic image sequence processing for autonomous aerial navigation research. Two main experiments were employed in this work, the first with clipping images of a geo-referenced aerial image, to simulate the unmanned aerial vehicle (UAV) navigation, and the second employing the video frames obtained from a camera fixed to a helicopter in a low level flight, simulating the vision system of an UAV. The image features used in recognition task were obtained by the SIFT algorithm. The recognition system consists on a video frame processing to estimate the UAV displacement. Promising results were obtained.","PeriodicalId":400165,"journal":{"name":"2009 IEEE International Conference on Signal and Image Processing Applications","volume":"531 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 IEEE International Conference on Signal and Image Processing Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSIPA.2009.5478706","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9
Abstract
Template matching in real-time is a fundamental issue in many applications in computer vision such as tracking, stereo vision and autonomous navigation. The goal of this paper is to present a system for automatic image sequence processing for autonomous aerial navigation research. Two main experiments were employed in this work, the first with clipping images of a geo-referenced aerial image, to simulate the unmanned aerial vehicle (UAV) navigation, and the second employing the video frames obtained from a camera fixed to a helicopter in a low level flight, simulating the vision system of an UAV. The image features used in recognition task were obtained by the SIFT algorithm. The recognition system consists on a video frame processing to estimate the UAV displacement. Promising results were obtained.