Authors:
Jorge Beltrán
;
Carlos Jaraquemada
;
Basam Musleh
;
Arturo De La Escalera
and
Jose María Armingol
Affiliation:
University Carlos III of Madrid (UC3M), Spain
Keyword(s):
Dense Labelling, Semantic Labelling, Stereo Vision, Off-road Navigation, ROS.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Computer Vision, Visualization and Computer Graphics
;
Motion, Tracking and Stereo Vision
;
Pattern Recognition
;
Robotics
;
Software Engineering
;
Stereo Vision and Structure from Motion
Abstract:
Interest on autonomous vehicles has rapidly increased in the last few years, due to recent advances in the
field and the appearance of semi-autonomous solutions in the market. In order to reach fully autonomous
navigation, a precise understanding of the vehicle surroundings is required. This paper presents a novel ROS-based
architecture for stereo-vision-based semantic scene labelling. The objective is to provide the necessary
information to a path planner in order to perform autonomous navigation around the university campus. The
output of the algorithm contains the classification of the obstacles in the scene into four different categories:
traversable areas, garden, static obstacles, and pedestrians. Validation of the labelling method is accomplished
by means of a hand-labelled ground truth, generated from a stereo sequence captured in the university campus.
The experimental results show the high performance of the proposed approach.