Author:
Toon Goedemé
Affiliation:
De Nayer Instituut, Belgium
Keyword(s):
Traffic sign recognition, local features, SURF, embedded.
Related
Ontology
Subjects/Areas/Topics:
Image Processing
;
Informatics in Control, Automation and Robotics
;
Robotics and Automation
;
Vision, Recognition and Reconstruction
Abstract:
In this paper, we present a method for fast and robust object recognition. As an example, the method is applied to traffic sign recognition from a forward-looking camera in a car. To facilitate and optimise the implementation of this algorithm on an embedded platform containing parallel hardware, we developed a voting scheme for constellations of visual words, i.e. clustered local features (SURF in this case). On top of easy implementation and robust and fast performance, even with large databases, an extra advantage is that this method can handle multiple identical visual features in one model.