{"title":"运动模型结构立体扫描叠加的三维-二维配准方法","authors":"Deepak Rajamohan, M. Garratt, M. Pickering","doi":"10.1109/DICTA51227.2020.9363423","DOIUrl":null,"url":null,"abstract":"Ahstract- The ability to detect and analyze changes or understand the scene while navigating close to buildings is very important for autonomous aerial and ground vehicle based surveillance applications. For this, the latest textured 3D scan of the platform's view frustum has to be placed accurately in the context of a big map like a Structure from Motion (SfM) map of the region. However, due to the drift in the camera trajectory, the scans are usually not aligned with the SfM model. This paper proposes a novel registration algorithm that aligns the 3D scan using known 2D images of the SfM model. The proposed 3D-2D registration method uses a heuristic approach which first performs a robust 2D-2D registration between the projection of the 3D scan and the SfM images and then calculates the 3D alignment parameters by combining registration results of multiple camera views of the SfM model. The results presented compare the robustness of the proposed registration techniques with traditional approaches.","PeriodicalId":348164,"journal":{"name":"2020 Digital Image Computing: Techniques and Applications (DICTA)","volume":"93 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A 3D-2D Registration Method for Stereo Scan Overlay on Structure from Motion Model\",\"authors\":\"Deepak Rajamohan, M. Garratt, M. Pickering\",\"doi\":\"10.1109/DICTA51227.2020.9363423\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Ahstract- The ability to detect and analyze changes or understand the scene while navigating close to buildings is very important for autonomous aerial and ground vehicle based surveillance applications. For this, the latest textured 3D scan of the platform's view frustum has to be placed accurately in the context of a big map like a Structure from Motion (SfM) map of the region. However, due to the drift in the camera trajectory, the scans are usually not aligned with the SfM model. This paper proposes a novel registration algorithm that aligns the 3D scan using known 2D images of the SfM model. The proposed 3D-2D registration method uses a heuristic approach which first performs a robust 2D-2D registration between the projection of the 3D scan and the SfM images and then calculates the 3D alignment parameters by combining registration results of multiple camera views of the SfM model. The results presented compare the robustness of the proposed registration techniques with traditional approaches.\",\"PeriodicalId\":348164,\"journal\":{\"name\":\"2020 Digital Image Computing: Techniques and Applications (DICTA)\",\"volume\":\"93 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-11-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 Digital Image Computing: Techniques and Applications (DICTA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/DICTA51227.2020.9363423\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 Digital Image Computing: Techniques and Applications (DICTA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DICTA51227.2020.9363423","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A 3D-2D Registration Method for Stereo Scan Overlay on Structure from Motion Model
Ahstract- The ability to detect and analyze changes or understand the scene while navigating close to buildings is very important for autonomous aerial and ground vehicle based surveillance applications. For this, the latest textured 3D scan of the platform's view frustum has to be placed accurately in the context of a big map like a Structure from Motion (SfM) map of the region. However, due to the drift in the camera trajectory, the scans are usually not aligned with the SfM model. This paper proposes a novel registration algorithm that aligns the 3D scan using known 2D images of the SfM model. The proposed 3D-2D registration method uses a heuristic approach which first performs a robust 2D-2D registration between the projection of the 3D scan and the SfM images and then calculates the 3D alignment parameters by combining registration results of multiple camera views of the SfM model. The results presented compare the robustness of the proposed registration techniques with traditional approaches.