Yuto Otsuki, B. Thornton, T. Maki, Yuya Nishida, A. Bodenmann, Kazunori Nagano
{"title":"基于海底场景复杂性的实时自主多分辨率视觉测量","authors":"Yuto Otsuki, B. Thornton, T. Maki, Yuya Nishida, A. Bodenmann, Kazunori Nagano","doi":"10.1109/AUV.2016.7778692","DOIUrl":null,"url":null,"abstract":"This paper describes a method to optimize the spatial resolution of image surveys based on the spatial scale of features on the seafloor that are not known prior to observation. The method makes use of the density of visual features as a measure of the complexity of a seafloor image. In order to achieve this, two approaches to assess scene complexity we investigated. The performance of the method was verified using seafloor imagery obtained in the Iheya North field in the Okinawa Trough. The results demonstrate that it is effective for a large range of feature sizes.","PeriodicalId":416057,"journal":{"name":"2016 IEEE/OES Autonomous Underwater Vehicles (AUV)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Real-time autonomous multi resolution visual surveys based on seafloor scene complexity\",\"authors\":\"Yuto Otsuki, B. Thornton, T. Maki, Yuya Nishida, A. Bodenmann, Kazunori Nagano\",\"doi\":\"10.1109/AUV.2016.7778692\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper describes a method to optimize the spatial resolution of image surveys based on the spatial scale of features on the seafloor that are not known prior to observation. The method makes use of the density of visual features as a measure of the complexity of a seafloor image. In order to achieve this, two approaches to assess scene complexity we investigated. The performance of the method was verified using seafloor imagery obtained in the Iheya North field in the Okinawa Trough. The results demonstrate that it is effective for a large range of feature sizes.\",\"PeriodicalId\":416057,\"journal\":{\"name\":\"2016 IEEE/OES Autonomous Underwater Vehicles (AUV)\",\"volume\":\"14 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE/OES Autonomous Underwater Vehicles (AUV)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/AUV.2016.7778692\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE/OES Autonomous Underwater Vehicles (AUV)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AUV.2016.7778692","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Real-time autonomous multi resolution visual surveys based on seafloor scene complexity
This paper describes a method to optimize the spatial resolution of image surveys based on the spatial scale of features on the seafloor that are not known prior to observation. The method makes use of the density of visual features as a measure of the complexity of a seafloor image. In order to achieve this, two approaches to assess scene complexity we investigated. The performance of the method was verified using seafloor imagery obtained in the Iheya North field in the Okinawa Trough. The results demonstrate that it is effective for a large range of feature sizes.