R@H selected Journal articles

[1] M. Vincze, S. Olufs, P. Einramhof, H. Wildenauer: "Roboternavigation in Büros und Wohnungen"; Elektrotechnik und Informationstechnik (e&i), 1-2 (2008), 1-2; S. 25 - 32.
[external Springer - Link]
[2] Scaramuzza, D., Martinelli, A., Siegwart, R. (2009) A Robust Descriptor for Tracking Vertical Lines in Omnidirectional Images and its Use in Mobile Robotics, International Journal on Robotics Research, Vol. 28, Nr. 2, February, 2009.[.pdf]
[3] Vasudevan,S., Siegwart,R., Bayesian space conceptualization and place classification for semantic maps in mobile robotics, Robotics and Autonomous Systems, 2008.
[external ScienceDirect - Link]
[4] K. Ambrosch, W. Kubinger, M. Humenberger, and A. Steininger, Flexible Hardware-Based Stereo Matching, EURASIP Journal on Embedded Systems, vol. 2008, Article ID 386059, 12 pages, 2008
[external Hindawi - Link]
[5] D. Kragic and M. Vincze. Vision for Robotics, Foundations and Trends® in Robotics, Vol. 1, No. 1, 2010.
[external Nowpublishers - Link]
[6] D. Scaramuzza, F. Fraundorfer, and M. Pollefeys. Closing the loop in appearance-guided omnidirectional visual odometry by using vocabulary trees, Robotics and Autonomous System Journal, 2010.
[7] M. Humenberger, C. Zinner, M. Weber, W. Kubinger, and M. Vincze. A Fast Stereo Matching Algorithm Suitable for Embedded Real-Time Systems. To appear in Journal on Computer Vision and Image Understanding, Elsevier.
[External ScienceDirect - Link]
[8] D. Scaramuzza and R. Siegwart. Appearance-guided monocular omnidirectional visual odometry for outdoor ground vehicles. IEEE Transactions on Robotics, Special Issue on Visual SLAM, 24(5), October 2008.
[9] Scaramuzza, D., and Siegwart, R. A Robust descriptor for vertical line matching in omnidirectional images, submitted to the International Journal on Computer Vision and Image Understanding, under review.
[10] Davide Scaramuzza and Roland Siegwart. Fast relative pose estimation with one point correspondence by exploiting nonholonomic constraints. International Journal of Computer Vision, 2010. to appear.