3D Data Processing Visualization and Transmission, International Symposium on (2006)
University of North Carolina, Chapel Hill, USA
June 14, 2006 to June 16, 2006
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/3DPVT.2006.18
Justin Domke , University of Maryland, College Park, USA
Yiannis Aloimonos , University of Maryland, College Park, USA
We present a probabilistic framework for correspondence and egomotion. First, we suggest computing probability distributions of correspondence. This has the advantage of being robust to points subject to the aperture effect and repetitive structure, while giving up no information at feature points. Additionally, correspondence probability distributions can be computed for every point in the scene. Next, we generate a probability distribution over the motions, from these correspondence probability distributions, through a probabilistic notion of the epipolar constraint. Finding the maximum in this distribution is shown to be a generalization of least-squared epipolar minimization. We will show that because our technique allows so much correspondence information to be extracted, more accurate egomotion estimation is possible.
J. Domke and Y. Aloimonos, "A Probabilistic Notion of Correspondence and the Epipolar Constraint," 3D Data Processing Visualization and Transmission, International Symposium on(3DPVT), University of North Carolina, Chapel Hill, USA, 2006, pp. 41-48.