Abstract— We present a learning-based approach for longrange vision that is able to accurately classify complex terrain at distances up to the horizon, thus allowing high-level s...
Raia Hadsell, Ayse Erkan, Pierre Sermanet, Marco S...
The necessity and utility of visual attention are discussed in the context of stereo vision in machines and primates. Specific problems that arise in this domain including binocul...
— In this paper we predict the amount of slip an exploration rover would experience using stereo imagery by learning from previous examples of traversing similar terrain. To do t...
Anelia Angelova, Larry Matthies, Daniel M. Helmick...
This paper describes maximum likelihood estimation techniques for performing rover localization in natural terrain by matching range maps. An occupancy map of the local terrain is...
Abstract. This paper presents a new multi-pass hierarchical stereo-matching approach for generation of digital terrain models (DTMs) from two overlapping aerial images. Our method ...