@inproceedings{8f00f965899840a6ad01d7d253753b4f,
title = "Egomotion estimation as an appearance-based classification problem",
abstract = "In this paper a probabilistic approach is considered to develop a methodology to solve the problem of estimation of the position of the observer. The base of this methodology is the appearance vision with which an environment map is constructed using Kernel PCA. For the experiments an image set is acquired in unknown locations in the same environment. The performance of Kernel PCA technique was tested according to the optimum dimension of the environment model and the quantity of images correctly classified using a Bayesian algorithm. To validate the results obtained with Kernel PCA the same experiments were performed with PCA and APEX techniques, then the results were compared showing that Kernel PCA has better performance than PCA and APEX.",
keywords = "Egomotion estimation, Kernel PCA, Probabilistic approach",
author = "Pedro S{\'a}nchez and Cornelio Y{\'a}{\~n}ez and Jonathan Pecero and Apolinar Ram{\'i}rez",
year = "2006",
doi = "10.1007/11892755_77",
language = "Ingl{\'e}s",
isbn = "3540465561",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "743--752",
booktitle = "Progress in Pattern Recognition, Image Analysis and Applications - 11th Iberoamerican Congress in Pattern Recognition, CIARP 2006, Proceedings",
address = "Alemania",
note = "11th Iberoamerican Congress in Pattern Recognition, CIARP 2006 ; Conference date: 14-11-2006 Through 17-11-2006",
}