Please use this identifier to cite or link to this item:
|Scopus||Web of Science®||Altmetric|
|Title:||Place recognition using uear and far visual information|
|Author:||Cadena Lerma, C.|
|Citation:||Proceedings of the 18th IFAC World Congress, 28th August - 2 September 2011 / Sergio Bittanti, Angelo Cenedese, Sandro Zampieri (eds.): pp.6822-6828|
|Publisher:||International Federation of Automatic Control|
|Conference Name:||IFAC World Congress (18th : 2011 : Milano, Italy)|
|Abstract:||In this paper we show how to carry out robust place recognition using both near and far information provided by a stereo camera. Visual appearance is known to be very useful in place recognition tasks. In recent years, it has been shown that taking geometric information also into account further improves system robustness. Stereo visual systems provide 3D information and texture of nearby regions, as well as an image of far regions. In order to make use of all this information, our system builds two probabilistic undirected graphs, each considering either near or far information. Inference is carried out in the framework of conditional random fields. We evaluate our algorithm in public indoor and outdoor datasets from the Rawseeds project and in an outdoor dataset obtained at the MIT campus. Results show that this combination of information is very useful to solve challenging cases of perceptual aliasing.|
|Appears in Collections:||Computer Science publications|
Files in This Item:
There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.