Photometric Invariant Projevtive Registration by using ECC Maximization

Georgios Evangelidis 1 Emmanouil Psarakis 2
1 PERCEPTION - Interpretation and Modelling of Images and Videos
Inria Grenoble - Rhône-Alpes, LJK - Laboratoire Jean Kuntzmann, INPG - Institut National Polytechnique de Grenoble
Abstract : The ability of an algorithm to accurately estimate the parameters of the geometric transformation which aligns two image profiles even in the presence of photometric distortions can be considered as a basic requirement in many computer vision applications. Projective transformations constitute a general class which includes as special cases the affine, as well as the metric subclasses of transformations. In this paper the applicability of a recently proposed iterative algorithm, which uses the Enhanced Correlation Coefficient as a performance criterion, in the projective image registration problem is investigated. The main theoretical results concerning the iterative algorithm and an efficient approximation that leads to an optimal closed form solution (per iteration) are presented. Furthermore, the performance of the iterative algorithm in the presence of nonlinear photometric distortions is compared against the leading Lucas-Kanade algorithm by performing numerous simulations. In all cases the proposed algorithm outperforms the Lucas-Kanade algorithm in convergence speed and robustness against photometric distortions under ideal and noisy conditions.
Type de document :
Communication dans un congrès
ICTAI - 19th IEEE International Conference on Tools with Artificial Intelligence, Oct 2007, Patras, Greece. IEEE, 1, pp.522-528, 2007, 〈10.1109/ICTAI.2007.158〉
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https://hal.inria.fr/hal-00864391
Contributeur : Team Perception <>
Soumis le : samedi 21 septembre 2013 - 11:46:09
Dernière modification le : jeudi 11 janvier 2018 - 06:22:00

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Georgios Evangelidis, Emmanouil Psarakis. Photometric Invariant Projevtive Registration by using ECC Maximization. ICTAI - 19th IEEE International Conference on Tools with Artificial Intelligence, Oct 2007, Patras, Greece. IEEE, 1, pp.522-528, 2007, 〈10.1109/ICTAI.2007.158〉. 〈hal-00864391〉

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