| Authors |
Klopschitz Manfred, Zach Christopher , Irschara Arnold , Schmalstieg Dieter |
| Appeared in |
Fourth International Symposium on 3D Data Processing, Visualization and Transmission |
| Publisher |
Georgia Institute of Technology, Atlanta, GA, USA , Georgia Institute of Technology, Atlanta, GA, USA |
| Organization |
Georgia Institute of Technology, Atlanta, GA, USA |
| Date |
June 2008 |
| Abstract |
In this work we present a method to detect overlaps in image
sequences, and use this information to integrate overlapping sparse
3D structure from video sequences. The additional temporal
information of these images is used to increase robustness over
single image pair matching. A scanline optimization problem
formulation is used to compute the best sequence alignment using
wide-baseline image matching techniques. Compared to a direct
dynamic programming approach, the scanline optimization formulation
increases the robustness of sequence alignment for general relative
motions. The proposed alignment method is employed to integrate
sparse 3D models reconstructed from separate video
sequences. In addition loop closures are detected. Consequently,
the 3D modeling process from sequential image data can be split into
fast sequence processing and subsequent global integration steps. |
| Link |
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