Metric Reconstruction with Missing Data
This project addresses the problem of moving object reconstruction. (It is also called Structure from Motion.) Several methods have been published in the past 20 years including stereo reconstruction as well as multi-view factorization methods. In general, reconstruction algorithms compute the 3D structure of the object and the camera parameters in a non-optimal way and then a nonlinear and numerical optimization algorithm refines the reconstructed camera parameters and 3D coordinates. In this research, we have proposed adjustment methods which is the improved version of the well-known Tomasi-Kanade factorization method. The novelty, which yields the high speed of the algorithm, is that the core of the proposed method is an alternation and we give optimal solutions to all the subproblems of the alternation.
The Java implementation of the developed factorization methods can be downloaded from HERE. Three different Structure from Motion (SfM) algorithms are included for (i) affine, (ii) weak-perspective, and (iii) scaled orthographic camera models. The implementation can cope with missing data.
- Levente Hajder, Akos Pernek, and Csaba Kazo: Weak-perspective structure from motion by fast alternation, The Visual Computer, vol. 27. pp. 387-399, 2011.
- Akos Pernek, Levente Hajder, Csaba Kazo: Metric Reconstruction with Missing Data under Weak Perspective, Proc. British Machine Vision Conference (BMVC), vol. 2, pp.685-694, 2008.
For further information please contact Levente Hajder.