Towards Large-Scale Visual Mapping and Localization View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2011

AUTHORS

Marc Pollefeys , Jan-Michael Frahm , Friedrich Fraundorfer , Christopher Zach , Changchang Wu , Brian Clipp , David Gallup

ABSTRACT

The topic of this paper is large-scale mapping and localization from images. We first describe recent progress in obtaining large-scale 3D visual maps from images only. Our approach consists of a multi-stage processing pipeline, which can process a recorded video stream in real-time on standard PC hardware by leveraging the computational power of the graphics processor. The output of this pipeline is a detailed textured 3D model of the recorded area. The approach is demonstrated on video data recorded in Chapel Hill containing more than a million frames. While for these results GPS and inertial sensor data was used, we further explore the possibility to extract the necessary information for consistent 3D mapping over larger areas from images only. In particular, we discuss our recent work focusing on estimating the absolute scale of motion from images as well as finding intersections where the camera path crosses itself to effectively close loops in the mapping process. For this purpose we introduce viewpoint-invariant patches (VIP) as a new 3D feature that we extract from 3D models locally computed from the video sequence. These 3D features have important advantages with respect to traditional 2D SIFT features such as much stronger viewpoint-invariance, a relative pose hypothesis from a single match and a hierarchical matching scheme robust to repetitive structures. In addition, we also briefly discuss some additional work related to absolute scale estimation and multi-camera calibration. More... »

PAGES

535-555

References to SciGraph publications

  • 2004-11. Distinctive Image Features from Scale-Invariant Keypoints in INTERNATIONAL JOURNAL OF COMPUTER VISION
  • 2004-09. Visual Modeling with a Hand-Held Camera in INTERNATIONAL JOURNAL OF COMPUTER VISION
  • 2011-01. Feature tracking and matching in video using programmable graphics hardware in MACHINE VISION AND APPLICATIONS
  • 2008. A Comparative Analysis of RANSAC Techniques Leading to Adaptive Real-Time Random Sample Consensus in COMPUTER VISION – ECCV 2008
  • 1999-08. Self-Calibration and Metric Reconstruction Inspite of Varying and Unknown Intrinsic Camera Parameters in INTERNATIONAL JOURNAL OF COMPUTER VISION
  • 2004-10. An Automated Method for Large-Scale, Ground-Based City Model Acquisition in INTERNATIONAL JOURNAL OF COMPUTER VISION
  • 2008-07. Detailed Real-Time Urban 3D Reconstruction from Video in INTERNATIONAL JOURNAL OF COMPUTER VISION
  • 1994-12. Review and analysis of solutions of the three point perspective pose estimation problem in INTERNATIONAL JOURNAL OF COMPUTER VISION
  • 2007. Visual Odometry for Non-overlapping Views Using Second-Order Cone Programming in COMPUTER VISION – ACCV 2007
  • 2002-06. Aligning Non-Overlapping Sequences in INTERNATIONAL JOURNAL OF COMPUTER VISION
  • 2002-04-12. Bundle Adjustment — A Modern Synthesis in VISION ALGORITHMS: THEORY AND PRACTICE
  • 2008. Modeling and Recognition of Landmark Image Collections Using Iconic Scene Graphs in COMPUTER VISION – ECCV 2008
  • 1992-11. Shape and motion from image streams under orthography: a factorization method in INTERNATIONAL JOURNAL OF COMPUTER VISION
  • 2005-11. A Comparison of Affine Region Detectors in INTERNATIONAL JOURNAL OF COMPUTER VISION
  • Book

    TITLE

    Robotics Research

    ISBN

    978-3-642-19456-6
    978-3-642-19457-3

    Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/978-3-642-19457-3_32

    DOI

    http://dx.doi.org/10.1007/978-3-642-19457-3_32

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1032571271


    Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
    Incoming Citations Browse incoming citations for this publication using opencitations.net

    JSON-LD is the canonical representation for SciGraph data.

    TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

    [
      {
        "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
        "about": [
          {
            "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0801", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Artificial Intelligence and Image Processing", 
            "type": "DefinedTerm"
          }, 
          {
            "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/08", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Information and Computing Sciences", 
            "type": "DefinedTerm"
          }
        ], 
        "author": [
          {
            "affiliation": {
              "name": [
                "Institute of Visual Computing, ETH Z\u00fcrich"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Pollefeys", 
            "givenName": "Marc", 
            "id": "sg:person.013372156770.67", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013372156770.67"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "University of North Carolina at Chapel Hill", 
              "id": "https://www.grid.ac/institutes/grid.10698.36", 
              "name": [
                "Dept. of Computer Science, University of North Carolina at Chapel Hill"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Frahm", 
            "givenName": "Jan-Michael", 
            "id": "sg:person.01214540412.56", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01214540412.56"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "name": [
                "Institute of Visual Computing, ETH Z\u00fcrich"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Fraundorfer", 
            "givenName": "Friedrich", 
            "id": "sg:person.016452351373.65", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016452351373.65"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "name": [
                "Institute of Visual Computing, ETH Z\u00fcrich"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Zach", 
            "givenName": "Christopher", 
            "id": "sg:person.01240477356.10", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01240477356.10"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "University of North Carolina at Chapel Hill", 
              "id": "https://www.grid.ac/institutes/grid.10698.36", 
              "name": [
                "Dept. of Computer Science, University of North Carolina at Chapel Hill"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Wu", 
            "givenName": "Changchang", 
            "id": "sg:person.014706435321.29", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014706435321.29"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "University of North Carolina at Chapel Hill", 
              "id": "https://www.grid.ac/institutes/grid.10698.36", 
              "name": [
                "Dept. of Computer Science, University of North Carolina at Chapel Hill"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Clipp", 
            "givenName": "Brian", 
            "id": "sg:person.016301376321.34", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016301376321.34"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "University of North Carolina at Chapel Hill", 
              "id": "https://www.grid.ac/institutes/grid.10698.36", 
              "name": [
                "Dept. of Computer Science, University of North Carolina at Chapel Hill"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Gallup", 
            "givenName": "David", 
            "id": "sg:person.011062507733.99", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011062507733.99"
            ], 
            "type": "Person"
          }
        ], 
        "citation": [
          {
            "id": "sg:pub.10.1023/a:1014803327923", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1004926552", 
              "https://doi.org/10.1023/a:1014803327923"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s11263-007-0086-4", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1015440148", 
              "https://doi.org/10.1007/s11263-007-0086-4"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/3-540-44480-7_21", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1021371683", 
              "https://doi.org/10.1007/3-540-44480-7_21"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/3-540-44480-7_21", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1021371683", 
              "https://doi.org/10.1007/3-540-44480-7_21"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/bf00129684", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1022340687", 
              "https://doi.org/10.1007/bf00129684"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/bf00129684", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1022340687", 
              "https://doi.org/10.1007/bf00129684"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00138-007-0105-z", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1024967344", 
              "https://doi.org/10.1007/s00138-007-0105-z"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.rti.2005.04.002", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1028006314"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.rti.2005.04.002", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1028006314"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1023/b:visi.0000027787.82851.b6", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1028136757", 
              "https://doi.org/10.1023/b:visi.0000027787.82851.b6"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1145/1457515.1409112", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1029206453"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1002/rob.20103", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1029949011"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1002/rob.20103", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1029949011"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1145/1618452.1618460", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1033840513"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1145/358669.358692", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1033921345"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1023/b:visi.0000025798.50602.3a", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1036329061", 
              "https://doi.org/10.1023/b:visi.0000025798.50602.3a"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-3-540-88682-2_33", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1040003675", 
              "https://doi.org/10.1007/978-3-540-88682-2_33"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-3-540-88682-2_33", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1040003675", 
              "https://doi.org/10.1007/978-3-540-88682-2_33"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1023/a:1008109111715", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1040628467", 
              "https://doi.org/10.1023/a:1008109111715"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1006/cviu.1997.0547", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1040876905"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1177/0278364908090961", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1042650840"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1177/0278364908090961", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1042650840"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s11263-005-3848-x", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1043375253", 
              "https://doi.org/10.1007/s11263-005-3848-x"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-3-540-88688-4_37", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1047496166", 
              "https://doi.org/10.1007/978-3-540-88688-4_37"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-3-540-88688-4_37", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1047496166", 
              "https://doi.org/10.1007/978-3-540-88688-4_37"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-3-540-76390-1_35", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1050374692", 
              "https://doi.org/10.1007/978-3-540-76390-1_35"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1023/b:visi.0000029664.99615.94", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1052687286", 
              "https://doi.org/10.1023/b:visi.0000029664.99615.94"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/bf02028352", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1053655398", 
              "https://doi.org/10.1007/bf02028352"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/bf02028352", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1053655398", 
              "https://doi.org/10.1007/bf02028352"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/34.888718", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1061157189"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/jra.1987.1087109", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1061308670"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/tpami.2004.17", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1061742704"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/tpami.2007.70732", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1061743375"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/iccv.2005.158", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1093209623"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/cvprw.2008.4563037", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1093271581"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/cvpr.2006.264", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1093301542"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/cvpr.1994.323794", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1093488775"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/cvpr.2005.342", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1093695806"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/cvpr.2008.4587676", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1093728357"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/wacv.2009.5403054", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1093747807"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/iccv.2009.5459148", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1093885278"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/wacv.2008.4544011", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1093926822"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/cvpr.2008.4587501", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1094017793"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/cvpr.2003.1211356", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1094136495"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/iccv.2009.5459387", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1094202115"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/iccv.2009.5459294", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1094264799"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/iccv.2007.4408997", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1094269460"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/cvpr.2007.383245", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1094603113"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/cvpr.2008.4587671", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1094610702"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/iccv.2007.4408945", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1094864184"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/iccv.2009.5459337", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1094940684"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/iccv.2007.4409218", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1095132002"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/iccv.2007.4408983", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1095358515"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/iccv.2003.1238399", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1095401302"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/cvprw.2008.4563089", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1095439034"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/iccv.2009.5459456", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1095543505"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/cvpr.2006.118", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1095567965"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://app.dimensions.ai/details/publication/pub.1108568702", 
            "type": "CreativeWork"
          }
        ], 
        "datePublished": "2011", 
        "datePublishedReg": "2011-01-01", 
        "description": "The topic of this paper is large-scale mapping and localization from images. We first describe recent progress in obtaining large-scale 3D visual maps from images only. Our approach consists of a multi-stage processing pipeline, which can process a recorded video stream in real-time on standard PC hardware by leveraging the computational power of the graphics processor. The output of this pipeline is a detailed textured 3D model of the recorded area. The approach is demonstrated on video data recorded in Chapel Hill containing more than a million frames. While for these results GPS and inertial sensor data was used, we further explore the possibility to extract the necessary information for consistent 3D mapping over larger areas from images only. In particular, we discuss our recent work focusing on estimating the absolute scale of motion from images as well as finding intersections where the camera path crosses itself to effectively close loops in the mapping process. For this purpose we introduce viewpoint-invariant patches (VIP) as a new 3D feature that we extract from 3D models locally computed from the video sequence. These 3D features have important advantages with respect to traditional 2D SIFT features such as much stronger viewpoint-invariance, a relative pose hypothesis from a single match and a hierarchical matching scheme robust to repetitive structures. In addition, we also briefly discuss some additional work related to absolute scale estimation and multi-camera calibration.", 
        "editor": [
          {
            "familyName": "Pradalier", 
            "givenName": "C\u00e9dric", 
            "type": "Person"
          }, 
          {
            "familyName": "Siegwart", 
            "givenName": "Roland", 
            "type": "Person"
          }, 
          {
            "familyName": "Hirzinger", 
            "givenName": "Gerhard", 
            "type": "Person"
          }
        ], 
        "genre": "chapter", 
        "id": "sg:pub.10.1007/978-3-642-19457-3_32", 
        "inLanguage": [
          "en"
        ], 
        "isAccessibleForFree": false, 
        "isPartOf": {
          "isbn": [
            "978-3-642-19456-6", 
            "978-3-642-19457-3"
          ], 
          "name": "Robotics Research", 
          "type": "Book"
        }, 
        "name": "Towards Large-Scale Visual Mapping and Localization", 
        "pagination": "535-555", 
        "productId": [
          {
            "name": "dimensions_id", 
            "type": "PropertyValue", 
            "value": [
              "pub.1032571271"
            ]
          }, 
          {
            "name": "doi", 
            "type": "PropertyValue", 
            "value": [
              "10.1007/978-3-642-19457-3_32"
            ]
          }, 
          {
            "name": "readcube_id", 
            "type": "PropertyValue", 
            "value": [
              "9b2abb6755857a6ab40b10fc4a97974b2c05869a85cde5e58e196b73ac4b73df"
            ]
          }
        ], 
        "publisher": {
          "location": "Berlin, Heidelberg", 
          "name": "Springer Berlin Heidelberg", 
          "type": "Organisation"
        }, 
        "sameAs": [
          "https://doi.org/10.1007/978-3-642-19457-3_32", 
          "https://app.dimensions.ai/details/publication/pub.1032571271"
        ], 
        "sdDataset": "chapters", 
        "sdDatePublished": "2019-04-16T08:42", 
        "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
        "sdPublisher": {
          "name": "Springer Nature - SN SciGraph project", 
          "type": "Organization"
        }, 
        "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000366_0000000366/records_112048_00000000.jsonl", 
        "type": "Chapter", 
        "url": "https://link.springer.com/10.1007%2F978-3-642-19457-3_32"
      }
    ]
     

    Download the RDF metadata as:  json-ld nt turtle xml License info

    HOW TO GET THIS DATA PROGRAMMATICALLY:

    JSON-LD is a popular format for linked data which is fully compatible with JSON.

    curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/978-3-642-19457-3_32'

    N-Triples is a line-based linked data format ideal for batch operations.

    curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/978-3-642-19457-3_32'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/978-3-642-19457-3_32'

    RDF/XML is a standard XML format for linked data.

    curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/978-3-642-19457-3_32'


     

    This table displays all metadata directly associated to this object as RDF triples.

    286 TRIPLES      23 PREDICATES      77 URIs      20 LITERALS      8 BLANK NODES

    Subject Predicate Object
    1 sg:pub.10.1007/978-3-642-19457-3_32 schema:about anzsrc-for:08
    2 anzsrc-for:0801
    3 schema:author N320839cd16c6470d8f8a01ffd41ad55b
    4 schema:citation sg:pub.10.1007/3-540-44480-7_21
    5 sg:pub.10.1007/978-3-540-76390-1_35
    6 sg:pub.10.1007/978-3-540-88682-2_33
    7 sg:pub.10.1007/978-3-540-88688-4_37
    8 sg:pub.10.1007/bf00129684
    9 sg:pub.10.1007/bf02028352
    10 sg:pub.10.1007/s00138-007-0105-z
    11 sg:pub.10.1007/s11263-005-3848-x
    12 sg:pub.10.1007/s11263-007-0086-4
    13 sg:pub.10.1023/a:1008109111715
    14 sg:pub.10.1023/a:1014803327923
    15 sg:pub.10.1023/b:visi.0000025798.50602.3a
    16 sg:pub.10.1023/b:visi.0000027787.82851.b6
    17 sg:pub.10.1023/b:visi.0000029664.99615.94
    18 https://app.dimensions.ai/details/publication/pub.1108568702
    19 https://doi.org/10.1002/rob.20103
    20 https://doi.org/10.1006/cviu.1997.0547
    21 https://doi.org/10.1016/j.rti.2005.04.002
    22 https://doi.org/10.1109/34.888718
    23 https://doi.org/10.1109/cvpr.1994.323794
    24 https://doi.org/10.1109/cvpr.2003.1211356
    25 https://doi.org/10.1109/cvpr.2005.342
    26 https://doi.org/10.1109/cvpr.2006.118
    27 https://doi.org/10.1109/cvpr.2006.264
    28 https://doi.org/10.1109/cvpr.2007.383245
    29 https://doi.org/10.1109/cvpr.2008.4587501
    30 https://doi.org/10.1109/cvpr.2008.4587671
    31 https://doi.org/10.1109/cvpr.2008.4587676
    32 https://doi.org/10.1109/cvprw.2008.4563037
    33 https://doi.org/10.1109/cvprw.2008.4563089
    34 https://doi.org/10.1109/iccv.2003.1238399
    35 https://doi.org/10.1109/iccv.2005.158
    36 https://doi.org/10.1109/iccv.2007.4408945
    37 https://doi.org/10.1109/iccv.2007.4408983
    38 https://doi.org/10.1109/iccv.2007.4408997
    39 https://doi.org/10.1109/iccv.2007.4409218
    40 https://doi.org/10.1109/iccv.2009.5459148
    41 https://doi.org/10.1109/iccv.2009.5459294
    42 https://doi.org/10.1109/iccv.2009.5459337
    43 https://doi.org/10.1109/iccv.2009.5459387
    44 https://doi.org/10.1109/iccv.2009.5459456
    45 https://doi.org/10.1109/jra.1987.1087109
    46 https://doi.org/10.1109/tpami.2004.17
    47 https://doi.org/10.1109/tpami.2007.70732
    48 https://doi.org/10.1109/wacv.2008.4544011
    49 https://doi.org/10.1109/wacv.2009.5403054
    50 https://doi.org/10.1145/1457515.1409112
    51 https://doi.org/10.1145/1618452.1618460
    52 https://doi.org/10.1145/358669.358692
    53 https://doi.org/10.1177/0278364908090961
    54 schema:datePublished 2011
    55 schema:datePublishedReg 2011-01-01
    56 schema:description The topic of this paper is large-scale mapping and localization from images. We first describe recent progress in obtaining large-scale 3D visual maps from images only. Our approach consists of a multi-stage processing pipeline, which can process a recorded video stream in real-time on standard PC hardware by leveraging the computational power of the graphics processor. The output of this pipeline is a detailed textured 3D model of the recorded area. The approach is demonstrated on video data recorded in Chapel Hill containing more than a million frames. While for these results GPS and inertial sensor data was used, we further explore the possibility to extract the necessary information for consistent 3D mapping over larger areas from images only. In particular, we discuss our recent work focusing on estimating the absolute scale of motion from images as well as finding intersections where the camera path crosses itself to effectively close loops in the mapping process. For this purpose we introduce viewpoint-invariant patches (VIP) as a new 3D feature that we extract from 3D models locally computed from the video sequence. These 3D features have important advantages with respect to traditional 2D SIFT features such as much stronger viewpoint-invariance, a relative pose hypothesis from a single match and a hierarchical matching scheme robust to repetitive structures. In addition, we also briefly discuss some additional work related to absolute scale estimation and multi-camera calibration.
    57 schema:editor N90e262cb918f40d2ac7b4e8b293f0bd4
    58 schema:genre chapter
    59 schema:inLanguage en
    60 schema:isAccessibleForFree false
    61 schema:isPartOf Nfcb50c372bd0474daf3da828810c288f
    62 schema:name Towards Large-Scale Visual Mapping and Localization
    63 schema:pagination 535-555
    64 schema:productId N5407dbcc1d9d40d0a6ba061ef9eef5f1
    65 N6b6a6b6f9f054079b9d71570e653b4b7
    66 Nb9880b4ea5934d59b4a34c4e67291755
    67 schema:publisher N594b5de5dfad44ce9c182202cdc7306b
    68 schema:sameAs https://app.dimensions.ai/details/publication/pub.1032571271
    69 https://doi.org/10.1007/978-3-642-19457-3_32
    70 schema:sdDatePublished 2019-04-16T08:42
    71 schema:sdLicense https://scigraph.springernature.com/explorer/license/
    72 schema:sdPublisher N25489ed6fb9b44c8b54cd5c7aa4bccf2
    73 schema:url https://link.springer.com/10.1007%2F978-3-642-19457-3_32
    74 sgo:license sg:explorer/license/
    75 sgo:sdDataset chapters
    76 rdf:type schema:Chapter
    77 N1551b2562a36458c90c7120a47d3b316 schema:familyName Hirzinger
    78 schema:givenName Gerhard
    79 rdf:type schema:Person
    80 N1e81f7a4aaf24a67ae920d47eac86704 rdf:first N1551b2562a36458c90c7120a47d3b316
    81 rdf:rest rdf:nil
    82 N20f7821829e348b0948a3e33b0ff0115 schema:name Institute of Visual Computing, ETH Zürich
    83 rdf:type schema:Organization
    84 N25489ed6fb9b44c8b54cd5c7aa4bccf2 schema:name Springer Nature - SN SciGraph project
    85 rdf:type schema:Organization
    86 N320839cd16c6470d8f8a01ffd41ad55b rdf:first sg:person.013372156770.67
    87 rdf:rest N3bfc8d9ef8df468dafddf0c54f83ff62
    88 N3bfc8d9ef8df468dafddf0c54f83ff62 rdf:first sg:person.01214540412.56
    89 rdf:rest Nd3b83968890f42f0b2689154c262c94c
    90 N5407dbcc1d9d40d0a6ba061ef9eef5f1 schema:name doi
    91 schema:value 10.1007/978-3-642-19457-3_32
    92 rdf:type schema:PropertyValue
    93 N5687a60791ca472b9c3ae3ca89a6336d schema:name Institute of Visual Computing, ETH Zürich
    94 rdf:type schema:Organization
    95 N57bfdc14f4e7485fbb3e537843fd70f1 rdf:first sg:person.01240477356.10
    96 rdf:rest Nbf44ca7d61a847608f32aa6e98a84a91
    97 N594b5de5dfad44ce9c182202cdc7306b schema:location Berlin, Heidelberg
    98 schema:name Springer Berlin Heidelberg
    99 rdf:type schema:Organisation
    100 N6b6a6b6f9f054079b9d71570e653b4b7 schema:name readcube_id
    101 schema:value 9b2abb6755857a6ab40b10fc4a97974b2c05869a85cde5e58e196b73ac4b73df
    102 rdf:type schema:PropertyValue
    103 N7f52d3780f45420dba05fae3480a02a3 rdf:first sg:person.016301376321.34
    104 rdf:rest Na875fa8b12454b4a9705c490cc223538
    105 N88c3a9ac00aa489282b4a36e08910fb3 rdf:first Nc45cf3615e284ede8badcfef89cff3cf
    106 rdf:rest N1e81f7a4aaf24a67ae920d47eac86704
    107 N90e262cb918f40d2ac7b4e8b293f0bd4 rdf:first N9745c78ff83e4e6cb6580a90f71650ee
    108 rdf:rest N88c3a9ac00aa489282b4a36e08910fb3
    109 N9745c78ff83e4e6cb6580a90f71650ee schema:familyName Pradalier
    110 schema:givenName Cédric
    111 rdf:type schema:Person
    112 Na875fa8b12454b4a9705c490cc223538 rdf:first sg:person.011062507733.99
    113 rdf:rest rdf:nil
    114 Nb4b995a2f20940618a55f447d9089210 schema:name Institute of Visual Computing, ETH Zürich
    115 rdf:type schema:Organization
    116 Nb9880b4ea5934d59b4a34c4e67291755 schema:name dimensions_id
    117 schema:value pub.1032571271
    118 rdf:type schema:PropertyValue
    119 Nbf44ca7d61a847608f32aa6e98a84a91 rdf:first sg:person.014706435321.29
    120 rdf:rest N7f52d3780f45420dba05fae3480a02a3
    121 Nc45cf3615e284ede8badcfef89cff3cf schema:familyName Siegwart
    122 schema:givenName Roland
    123 rdf:type schema:Person
    124 Nd3b83968890f42f0b2689154c262c94c rdf:first sg:person.016452351373.65
    125 rdf:rest N57bfdc14f4e7485fbb3e537843fd70f1
    126 Nfcb50c372bd0474daf3da828810c288f schema:isbn 978-3-642-19456-6
    127 978-3-642-19457-3
    128 schema:name Robotics Research
    129 rdf:type schema:Book
    130 anzsrc-for:08 schema:inDefinedTermSet anzsrc-for:
    131 schema:name Information and Computing Sciences
    132 rdf:type schema:DefinedTerm
    133 anzsrc-for:0801 schema:inDefinedTermSet anzsrc-for:
    134 schema:name Artificial Intelligence and Image Processing
    135 rdf:type schema:DefinedTerm
    136 sg:person.011062507733.99 schema:affiliation https://www.grid.ac/institutes/grid.10698.36
    137 schema:familyName Gallup
    138 schema:givenName David
    139 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011062507733.99
    140 rdf:type schema:Person
    141 sg:person.01214540412.56 schema:affiliation https://www.grid.ac/institutes/grid.10698.36
    142 schema:familyName Frahm
    143 schema:givenName Jan-Michael
    144 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01214540412.56
    145 rdf:type schema:Person
    146 sg:person.01240477356.10 schema:affiliation Nb4b995a2f20940618a55f447d9089210
    147 schema:familyName Zach
    148 schema:givenName Christopher
    149 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01240477356.10
    150 rdf:type schema:Person
    151 sg:person.013372156770.67 schema:affiliation N5687a60791ca472b9c3ae3ca89a6336d
    152 schema:familyName Pollefeys
    153 schema:givenName Marc
    154 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013372156770.67
    155 rdf:type schema:Person
    156 sg:person.014706435321.29 schema:affiliation https://www.grid.ac/institutes/grid.10698.36
    157 schema:familyName Wu
    158 schema:givenName Changchang
    159 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014706435321.29
    160 rdf:type schema:Person
    161 sg:person.016301376321.34 schema:affiliation https://www.grid.ac/institutes/grid.10698.36
    162 schema:familyName Clipp
    163 schema:givenName Brian
    164 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016301376321.34
    165 rdf:type schema:Person
    166 sg:person.016452351373.65 schema:affiliation N20f7821829e348b0948a3e33b0ff0115
    167 schema:familyName Fraundorfer
    168 schema:givenName Friedrich
    169 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016452351373.65
    170 rdf:type schema:Person
    171 sg:pub.10.1007/3-540-44480-7_21 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021371683
    172 https://doi.org/10.1007/3-540-44480-7_21
    173 rdf:type schema:CreativeWork
    174 sg:pub.10.1007/978-3-540-76390-1_35 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050374692
    175 https://doi.org/10.1007/978-3-540-76390-1_35
    176 rdf:type schema:CreativeWork
    177 sg:pub.10.1007/978-3-540-88682-2_33 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040003675
    178 https://doi.org/10.1007/978-3-540-88682-2_33
    179 rdf:type schema:CreativeWork
    180 sg:pub.10.1007/978-3-540-88688-4_37 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047496166
    181 https://doi.org/10.1007/978-3-540-88688-4_37
    182 rdf:type schema:CreativeWork
    183 sg:pub.10.1007/bf00129684 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022340687
    184 https://doi.org/10.1007/bf00129684
    185 rdf:type schema:CreativeWork
    186 sg:pub.10.1007/bf02028352 schema:sameAs https://app.dimensions.ai/details/publication/pub.1053655398
    187 https://doi.org/10.1007/bf02028352
    188 rdf:type schema:CreativeWork
    189 sg:pub.10.1007/s00138-007-0105-z schema:sameAs https://app.dimensions.ai/details/publication/pub.1024967344
    190 https://doi.org/10.1007/s00138-007-0105-z
    191 rdf:type schema:CreativeWork
    192 sg:pub.10.1007/s11263-005-3848-x schema:sameAs https://app.dimensions.ai/details/publication/pub.1043375253
    193 https://doi.org/10.1007/s11263-005-3848-x
    194 rdf:type schema:CreativeWork
    195 sg:pub.10.1007/s11263-007-0086-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1015440148
    196 https://doi.org/10.1007/s11263-007-0086-4
    197 rdf:type schema:CreativeWork
    198 sg:pub.10.1023/a:1008109111715 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040628467
    199 https://doi.org/10.1023/a:1008109111715
    200 rdf:type schema:CreativeWork
    201 sg:pub.10.1023/a:1014803327923 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004926552
    202 https://doi.org/10.1023/a:1014803327923
    203 rdf:type schema:CreativeWork
    204 sg:pub.10.1023/b:visi.0000025798.50602.3a schema:sameAs https://app.dimensions.ai/details/publication/pub.1036329061
    205 https://doi.org/10.1023/b:visi.0000025798.50602.3a
    206 rdf:type schema:CreativeWork
    207 sg:pub.10.1023/b:visi.0000027787.82851.b6 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028136757
    208 https://doi.org/10.1023/b:visi.0000027787.82851.b6
    209 rdf:type schema:CreativeWork
    210 sg:pub.10.1023/b:visi.0000029664.99615.94 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052687286
    211 https://doi.org/10.1023/b:visi.0000029664.99615.94
    212 rdf:type schema:CreativeWork
    213 https://app.dimensions.ai/details/publication/pub.1108568702 schema:CreativeWork
    214 https://doi.org/10.1002/rob.20103 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029949011
    215 rdf:type schema:CreativeWork
    216 https://doi.org/10.1006/cviu.1997.0547 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040876905
    217 rdf:type schema:CreativeWork
    218 https://doi.org/10.1016/j.rti.2005.04.002 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028006314
    219 rdf:type schema:CreativeWork
    220 https://doi.org/10.1109/34.888718 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061157189
    221 rdf:type schema:CreativeWork
    222 https://doi.org/10.1109/cvpr.1994.323794 schema:sameAs https://app.dimensions.ai/details/publication/pub.1093488775
    223 rdf:type schema:CreativeWork
    224 https://doi.org/10.1109/cvpr.2003.1211356 schema:sameAs https://app.dimensions.ai/details/publication/pub.1094136495
    225 rdf:type schema:CreativeWork
    226 https://doi.org/10.1109/cvpr.2005.342 schema:sameAs https://app.dimensions.ai/details/publication/pub.1093695806
    227 rdf:type schema:CreativeWork
    228 https://doi.org/10.1109/cvpr.2006.118 schema:sameAs https://app.dimensions.ai/details/publication/pub.1095567965
    229 rdf:type schema:CreativeWork
    230 https://doi.org/10.1109/cvpr.2006.264 schema:sameAs https://app.dimensions.ai/details/publication/pub.1093301542
    231 rdf:type schema:CreativeWork
    232 https://doi.org/10.1109/cvpr.2007.383245 schema:sameAs https://app.dimensions.ai/details/publication/pub.1094603113
    233 rdf:type schema:CreativeWork
    234 https://doi.org/10.1109/cvpr.2008.4587501 schema:sameAs https://app.dimensions.ai/details/publication/pub.1094017793
    235 rdf:type schema:CreativeWork
    236 https://doi.org/10.1109/cvpr.2008.4587671 schema:sameAs https://app.dimensions.ai/details/publication/pub.1094610702
    237 rdf:type schema:CreativeWork
    238 https://doi.org/10.1109/cvpr.2008.4587676 schema:sameAs https://app.dimensions.ai/details/publication/pub.1093728357
    239 rdf:type schema:CreativeWork
    240 https://doi.org/10.1109/cvprw.2008.4563037 schema:sameAs https://app.dimensions.ai/details/publication/pub.1093271581
    241 rdf:type schema:CreativeWork
    242 https://doi.org/10.1109/cvprw.2008.4563089 schema:sameAs https://app.dimensions.ai/details/publication/pub.1095439034
    243 rdf:type schema:CreativeWork
    244 https://doi.org/10.1109/iccv.2003.1238399 schema:sameAs https://app.dimensions.ai/details/publication/pub.1095401302
    245 rdf:type schema:CreativeWork
    246 https://doi.org/10.1109/iccv.2005.158 schema:sameAs https://app.dimensions.ai/details/publication/pub.1093209623
    247 rdf:type schema:CreativeWork
    248 https://doi.org/10.1109/iccv.2007.4408945 schema:sameAs https://app.dimensions.ai/details/publication/pub.1094864184
    249 rdf:type schema:CreativeWork
    250 https://doi.org/10.1109/iccv.2007.4408983 schema:sameAs https://app.dimensions.ai/details/publication/pub.1095358515
    251 rdf:type schema:CreativeWork
    252 https://doi.org/10.1109/iccv.2007.4408997 schema:sameAs https://app.dimensions.ai/details/publication/pub.1094269460
    253 rdf:type schema:CreativeWork
    254 https://doi.org/10.1109/iccv.2007.4409218 schema:sameAs https://app.dimensions.ai/details/publication/pub.1095132002
    255 rdf:type schema:CreativeWork
    256 https://doi.org/10.1109/iccv.2009.5459148 schema:sameAs https://app.dimensions.ai/details/publication/pub.1093885278
    257 rdf:type schema:CreativeWork
    258 https://doi.org/10.1109/iccv.2009.5459294 schema:sameAs https://app.dimensions.ai/details/publication/pub.1094264799
    259 rdf:type schema:CreativeWork
    260 https://doi.org/10.1109/iccv.2009.5459337 schema:sameAs https://app.dimensions.ai/details/publication/pub.1094940684
    261 rdf:type schema:CreativeWork
    262 https://doi.org/10.1109/iccv.2009.5459387 schema:sameAs https://app.dimensions.ai/details/publication/pub.1094202115
    263 rdf:type schema:CreativeWork
    264 https://doi.org/10.1109/iccv.2009.5459456 schema:sameAs https://app.dimensions.ai/details/publication/pub.1095543505
    265 rdf:type schema:CreativeWork
    266 https://doi.org/10.1109/jra.1987.1087109 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061308670
    267 rdf:type schema:CreativeWork
    268 https://doi.org/10.1109/tpami.2004.17 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061742704
    269 rdf:type schema:CreativeWork
    270 https://doi.org/10.1109/tpami.2007.70732 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061743375
    271 rdf:type schema:CreativeWork
    272 https://doi.org/10.1109/wacv.2008.4544011 schema:sameAs https://app.dimensions.ai/details/publication/pub.1093926822
    273 rdf:type schema:CreativeWork
    274 https://doi.org/10.1109/wacv.2009.5403054 schema:sameAs https://app.dimensions.ai/details/publication/pub.1093747807
    275 rdf:type schema:CreativeWork
    276 https://doi.org/10.1145/1457515.1409112 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029206453
    277 rdf:type schema:CreativeWork
    278 https://doi.org/10.1145/1618452.1618460 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033840513
    279 rdf:type schema:CreativeWork
    280 https://doi.org/10.1145/358669.358692 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033921345
    281 rdf:type schema:CreativeWork
    282 https://doi.org/10.1177/0278364908090961 schema:sameAs https://app.dimensions.ai/details/publication/pub.1042650840
    283 rdf:type schema:CreativeWork
    284 https://www.grid.ac/institutes/grid.10698.36 schema:alternateName University of North Carolina at Chapel Hill
    285 schema:name Dept. of Computer Science, University of North Carolina at Chapel Hill
    286 rdf:type schema:Organization
     




    Preview window. Press ESC to close (or click here)


    ...