Visualization of Scene Structure Uncertainty in a Multi-View Reconstruction Pipeline Shawn Recker 1, Mauricio Hess- Flores 1, Mark A. Duchaineau 2, and Kenneth I. Joy 1 1 University of California, Davis, USA, {strecker, mhessf, 2 Lawrence Livermore National Labs. Vision, Modeling, and Visualization (VMV) Workshop 2012 Magdeburg, Germany November
Multi-View Reconstruction 2 Bundle Adjustment ‘dinosaur’ dataset images from [1].
Structural Uncertainty Visualization 3
Volume Visualization Techniques Volume Rendering Contouring 4
Procedure … 5
Evaluated Test Cases Frame decimation simulation Feature matching inaccuracy Self calibration tests 6
Frame Decimation Graphs 7
Frame Decimation Results 30 cameras 15 cameras 10 cameras 8 cameras 4 cameras2 cameras 8
Feature Tracking Graphs 9
Feature Tracking Inaccuracy Results 10 0% Error 1% Error 2% Error 5% Error10% Error 20% Error
Self-Calibration Graphs 11
Self-Calibration Results 12 0%1% 2%5%10% 20% Principal Point Variation Focal Length Decrease
Conclusions and Future Work Presentation of a structural uncertainty visualization tool Continued visualization of computer vision Investigation of our cost function – Scene structure computation – Camera pose estimation 13
Acknowledgements This work was supported in part by Lawrence Livermore National Laboratory and the National Nuclear Security Agency through Contract No. DE-FG52-09NA
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Reprojection Error versus Angular Error 16 Reprojection Error Scalar Field Average Scalar Field