Automatic camera calibration and scene reconstruction with scale-invariant features

Jun Liu, Roger Hubbold

    Research output: Chapter in Book/Report/Conference proceedingConference contribution


    The goal of our research is to robustly reconstruct general 3D scenes from 2D images, with application to automatic model generation in computer graphics and virtual reality. In this paper we aim at producing relatively dense and well-distributed 3D points which can subsequently be used to reconstruct the scene structure. We present novel camera calibration and scene reconstruction using scale-invariant feature points. A generic high-dimensional vector matching scheme is proposed to enhance the efficiency and reduce the computational cost while finding feature correspondences. A framework for structure and motion is also presented that better exploits the advantages of scale-invariant features. In this approach we solve the "phantom points" problem and this greatly reduces the possibility of error propagation. The whole process requires no information other than the input images. The results illustrate that our system is capable of producing accurate scene structure and realistic 3D models within a few minutes. © Springer-Verlag Berlin Heidelberg 2006.
    Original languageEnglish
    Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|Lect. Notes Comput. Sci.
    PublisherSpringer Nature
    Number of pages10
    ISBN (Print)3540486283, 9783540486282
    Publication statusPublished - 2006
    Event2nd International Symposium on Visual Computing, ISVC 2006 - Lake Tahoe, NV
    Duration: 1 Jul 2006 → …

    Publication series

    NameLecture Notes in Computer Science


    Conference2nd International Symposium on Visual Computing, ISVC 2006
    CityLake Tahoe, NV
    Period1/07/06 → …
    Internet address


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