— We introduce a fast and robust subspace-based approach to appearance-based object tracking. The core of our approach is based on Fast Robust Correlation (FRC), a recently propo...
Stephan Liwicki, Stefanos Zafeiriou, Georgios Tzim...
—The approach presented in this paper tackles the active research problem of the fast automatic modeling of large-scale environments from videos with millions of frames and colle...
Jan-Michael Frahm, Marc Pollefeys, Svetlana Lazebn...
In this work, we present a technique for robust estimation, which by explicitly incorporating the inherent uncertainty of the estimation procedure, results in a more efficient rob...
For many applied problems in the context of clustering via mixture models, the estimates of the component means and covariance matrices can be affected by observations that are at...
Robust model fitting is important for computer vision tasks due to the occurrence of multiple model instances, and, unknown nature of noise. The linear errors-in-variables (EIV) m...
We carry out a longitudinal study of evolution of small-time scaling behavior of Internet traffic on the MAWI dataset spanning 8 years. MAWI dataset contains a number of anomalies ...
We propose a robust estimation method of gene networks based on microarray gene expression data. It is well-known that microarray data contain a large amount of noise and some outl...
Seiya Imoto, Tomoyuki Higuchi, SunYong Kim, Euna J...
— The goal of this paper is to present an overview of robust estimation techniques with a special focus on robotic vision applications. In this particular context, constraints du...
Finding correspondences between two (widely) separated views is essential for several computer vision tasks, such as structure and motion estimation and object recognition. In the...
The context of this work is lateral vehicle control using a camera as a sensor. A natural tool for controlling a vehicle is recursive filtering. The well-known Kalman fil...
Jean-Philippe Tarel, Sio-Song Ieng, Pierre Charbon...