Automatic Visual Inspection of Tunnels (AVIT) Meeting - Dec... · 2010. 7. 1. · Automatic Visual...

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Automatic Visual Inspection of Tunnels (AVIT): Image Mosaicing via Robust Quadric Surface Estimation

Transcript of Automatic Visual Inspection of Tunnels (AVIT) Meeting - Dec... · 2010. 7. 1. · Automatic Visual...

  • Automatic Visual Inspection of Tunnels (AVIT):

    Image Mosaicing via Robust Quadric Surface Estimation

  • M ti tiMotivation

    U t i t k i i f t t• Urgent maintenance works: aging infrastructure

    • Current visual inspection method is ineffective in time and costsCurrent visual inspection method is ineffective in time and costs

    • Urgent need for an automatic system to detect anomalies

    • Advancement in Computer Vision technology

  • System Outline

  • Homography-based MosaicingHomography based Mosaicing

    Di erging parallel lines MisalignmentObtained from the ‘Autopano’ software

    • More distortion when mosaicing in the ‘along’ direction

    Diverging parallel lines Misalignment

    g g

    • Algorithm works well when a camera undergoes pure rotation

  • Homography-based MosaicingHomography based Mosaicing

    MisalignmentDi i ll l li

    Obtained from the Microsoft `Image Composite Editor software

    • More distortion when mosaicing in the ‘along’ direction

    Diverging parallel lines

    g g

    • Algorithm works well when a camera undergoes pure rotation

  • Aldwych tunnel data setAldwych tunnel data set• Good pairwise reconstruction

    • Sufficient 3D informationTunnel liningsy x

    • Reconstruction of the entire sequence possible

    z

    3-1-2

    3-1-1

    2-1-2Overlap 40%-50%

    Camera Overlap

    1-1-12-1-1

    2-1-21-1-2Camera 1

    Overlap 40-50%

    Tunnel linings

  • Reconstruction after RefinementReconstruction before Refinement

  • Reconstruction after RefinementSurface EstimationSVM classifier

    Curvature due to incorrect surfaceincorrect surface

  • SVM classifier

  • Texture mappingSVM classifierpp g

  • Mosaics on Curved SurfacesMosaics on Curved Surfaces

    Parallelism is preserved Local misalignment can be refined

    Blending algorithm to smooth colour at the overlapping region can be refined

  • Mosaics on Curved SurfacesMosaics on Curved Surfaces

    Microsoft Image Composite Editor on prewarped images

  • More ResultsMore Results

  • More ResultsMore Results

    Local misalignment due to 3D oca sa g e due o 3structures

  • ProblemProblem

  • ProblemProblem

  • ProblemProblem

    • Ransac algorithm for 3D goutlier removal

    C d l i f• Correspondence solving for more accurate registration and reconstruction

  • C t S tCurrent System

  • Outline of the future systemOutline of the future systemVideo Based

    ReconstructionVideo Capture

    System

    Surface Estimation with

    Priors

    Multiple View Reconstruction

    Image warping and

    Final MosaicImage

    Retrieval

    Labelled SVM LearningImage Dataset

    SVM Learning

    Registration

    and

    Change Detection

    Correspondence

    Solving Change Detectiong

  • • Database can be created from the initial set of labelled images

  • F t kFuture work• Correspondence solving with the aid• Correspondence solving with the aid

    of 1) crack and deterioration patterns, 2) regions (tunnel linings, pipes), 3) Fourier transform (good for

    2003 2007

    cracks), 4) photometric changes (color, illumination)・・ 5) structure removal

    • RF classifier (key point tracking),tree structure for multiple hypotheses (david lowe’s)(david lowe s)

    • Applications: Image registration and change (crack) detectiong ( )

    ・ Several tens of crack and anomalies images, prototype of the above

    Image from Sinha et. al. (2006)

  • Acknowledgement

    Supervisor : Prof. Kenichi Soga and p gProf. Roberto Cipolla

    Collaborator : Fabio Viola and Dr. Taekyun Kim

    G t EPSRC COT d Ch i t’ d tGrants : EPSRC, COT, and Christ’s graduate award

  • Thank You

  • F t kFuture works• Image registration and extending the sequence• Image registration and extending the sequence

    • Automatic crack detection

    • Change detection

    Image from Sinha et. al. (2006)2003 2007

  • 2003 2007

    C• Change detection by accurate geometrical registration

    • Semantic Texton Forests for ImageSemantic Texton Forests for Image Categorization and Segmentation (Shotton et. al. 2008)

    • Systematic database collection