Curve finder combining perceptual grouping and a Kalman like fitting
GUICHARD ; TAREL
Type de document
COMMUNICATION AVEC ACTES INTERNATIONAL (ACTI)
Langue
anglais
Auteur
GUICHARD ; TAREL
Résumé / Abstract
We present an algorithm that extracts curves from a set of edges within a specific class in a decreasing order of their 'length'. The algorithm inherits the perceptual grouping approaches. But instead of using only local cues, a global constraint is imposed to each extracted subset of edgels, that the underlying curve belongs to a specific class. In order to reduce the complexity of the solution, we work with a lineary parametrized class of curves, function of one image coordinate. This allows first to use a recursive Kalman based fitting and second, to cas the problem as an optimal path search in a directed graph. Experiments on finding lane-markings on roads demonstrate that real-time processing is achievable.
