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2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
Improving RANSAC for fast landmark recognition
Anchorage, AK, USA
June 23-June 28
ISBN: 978-1-4244-2339-2
Pablo Marquez-Neila, Dep. Inteligencia Artificial Facultad Informática, Universidad Politécnica de Madrid, Spain
Jacobo Garcia Miro, Dep. Inteligencia Artificial Facultad Informática, Universidad Politécnica de Madrid, Spain
Jose M. Buenaposada, Dep. Ciencias de la Computación E.T.S.I. Informática Universidad Rey Juan Carlos, Spain
Luis Baumela, Dep. Inteligencia Artificial Facultad Informática, Universidad Politécnica de Madrid, Spain
We introduce a procedure for recognizing and locating planar landmarks for mobile robot navigation, based in the detection and recognition of a set of interest points. We use RANSAC for fitting a homography and locating the landmark. Our main contribution is the introduction of a geometrical constraint that reduces the number of RANSAC iterations by discarding minimal subsets. In the experiments conducted we conclude that this constraint increases RANSAC performance by reducing in about 35% and 75% the number of iterations for affine and projective cameras, respectively.
Citation:
Pablo Marquez-Neila, Jacobo Garcia Miro, Jose M. Buenaposada, Luis Baumela, "Improving RANSAC for fast landmark recognition," cvprw, pp.1-8, 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, 2008
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