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10 May 2012 Fundamental matrix and planar homographies in stereo vision
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Abstract
We describe the epipolar constraint that specifies the geometry of stereo vision. We consider the 3D structure reconstruction from multiple views through the new perspective of basing the reconstruction from directly estimated planar homographies instead of using techniques that are based on matched point pairs. Planar homography parameters can more accurately extract scene planar surfaces and directly solve for the 3D structure and camera motion parameters. The new method has the advantage that it integrates larger amount of information because the homography parameters are estimated directly from the intensities and not from an abstracted descriptor of the neighborhood. Because it does not rely on a transformation of an entire image region, the method is efficient.
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Qiang He and Chee-Hung Henry Chu "Fundamental matrix and planar homographies in stereo vision", Proc. SPIE 8401, Independent Component Analyses, Compressive Sampling, Wavelets, Neural Net, Biosystems, and Nanoengineering X, 84011B (10 May 2012); https://doi.org/10.1117/12.919709
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