The supervised learning paradigm assumes in general that both training and test data are sampled from the same distribution. When this assumption is violated, we are in the setting...
We consider the problem of extracting features for multi-class recognition problems. The features are required to make fine distinction between similar classes, combined with tole...
— Image-based navigation paradigms have recently emerged as an interesting alternative to conventional modelbased methods in mobile robotics. In this paper, we augment the existi...
While realistic illumination significantly improves the visual quality and perception of rendered images, it is often very expensive to compute. In this paper, we propose a new al...
The focus of this work is on the problem of feature selection and classification for on-road vehicle detection. In particular, we propose using quantized Haar wavelet features an...