— In this paper, we present a new approach for automatic car detection from aerial images. The system exploits a robust machine learning method known as boosting for efficient c...
Thuy Thi Nguyen, Helmut Grabner, Horst Bischof, B....
The interpretation of aerial images is difficult, especially for low-resolution images. Although solutions have been worked on for many years, performance of these systems is sti...
Abstract. In this paper we present an efficient technique to obtain accurate semantic classification on the pixel level capable of integrating various modalities, such as color, ed...
Stefan Kluckner, Thomas Mauthner, Peter M. Roth, H...
In times of disaster acquiring aerial images is challenging. Runways may be crippled thus denying conventional aircraft in the area from taking off. Also the time required to sch...
Over the past decades, considerable progress had been made in developing automatic image interpretation tools for remote sensing. There is, however, still a gap between the require...
Abstract— Road network information (RNI) simplifies autonomous driving by providing strong priors about driving environments. Its usefulness has been demonstrated in the DARPA U...
We propose an automatic approach to tree detection from aerial imagery. First a pixel-level classifier is trained to assign a {tree, non-tree} label to each pixel in an aerial im...
Airborne LiDAR technology draws increasing interest in
large-scale 3D urban modeling in recent years. 3D Li-
DAR data typically has no texture information. To generate
photo-rea...