LQ-bundle adjustment


In this paper we propose a method to solve for an L<sub>q</sub> solution of bundle adjustment, a non-linear parameter estimation problem. Given a set of images of a scene, bundle adjustment simultaneously estimates camera parameters and 3D structure of the scene. Generally, a least squares criterion is minimized by using the Levenberg-Marquardt (LM) method, a non-linear least squares optimization method. It is known that the least squares methods are not robust to outliers, even a single outlier can deviate the solution from its true value. Therefore, we propose a method to minimize an L<sub>q</sub> cost function, for 1 &#x2264; q &lt;; 2. The L<sub>q</sub> cost function minimizes the sum of the q-th power of errors. The proposed method has an advantage of using the Levenberg-Marquardt (LM) method to find a robust solution of the problem. Our experimental results confirm that the proposed method is more robust to outliers than the standard least squares method.

DOI: 10.1109/ICIP.2015.7351005

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@article{Aftab2015LQbundleA, title={LQ-bundle adjustment}, author={Khurrum Aftab and Richard I. Hartley}, journal={2015 IEEE International Conference on Image Processing (ICIP)}, year={2015}, pages={1275-1279} }