This paper deals with automatically learning the spatial distribution of a set of images. That is, given a sequence of images acquired from well-separated locations, how can they ...
This paper considers a robot with multiple sensors navigating an unknown, heterogeneous environment. In these cases sensor errors may produce an unsuitable model of the world. For...
cal maps provide a useful abstraction for robotic navigation and planning. Although stochastic mapscan theoreticallybe learned using the Baum-Welch algorithm,without strong prior ...
Bio-inspired vision sensors are particularly appropriate candidates for navigation of vehicles or mobile robots due to their computational simplicity, allowing compact hardware im...
Hongying Meng, Kofi Appiah, Shigang Yue, Andrew Hu...
To recover depth from images, the human visual system uses many monocular depth cues, which vision research has only begun to explore. Because a given image can have many possible...