Road scene segmentation is important in computer vision for different applications such as autonomous driving and pedestrian detection. Recovering the 3D structure of road scenes ...
Jose M. Alvarez, Theo Gevers, Yann LeCun, Antonio ...
—By using an onboard camera, it is possible to detect the free road surface ahead of the ego-vehicle. Road detection is of high relevance for autonomous driving, road departure w...
The Intelligent Systems Division of the National Institute of Standards and Technology has been engaged for several years in developing real-time systems for autonomous driving. A...
Abstract. Reliably extracting information from aerial imagery is a difficult problem with many practical applications. One specific case of this problem is the task of automatica...
Our previous work on road detection suggests the usage of prior knowledge in order to improve performance. In this paper we will explain our motivation for a novel approach, defin...
Vision-based road detection is important in different areas of
computer vision such as autonomous driving, car collision warning
and pedestrian crossing detection. However, curre...
Given a single image of an arbitrary road, that may not be well-paved, or have clearly delineated edges, or some a priori known color or texture distribution, is it possible for a ...
ROMA is a database of numerical images easily usable to evaluate in a systematic way the performance of road markings extraction algorithms. It comprises more than 100 original ima...
J.-P. Tarel, P. Nicolle, P. Charbonnier and T. Vei...
We present an algorithm that extracts the largest shape within a specificclass, starting from a set of image edgels. The algorithm inherits the Best-First Segmentation approach [jp...
Color is a powerful visual cue for many computer vision
applications such as image segmentation and object recognition.
However, most of the existing color models depend on the i...