A fuzzy-logic classifier for estimating the reliability of the self calibration of an embedded stereovision system

Author

Kramm, Sebastien ; Miché, Pierre ; Bensrhair, Abdelaziz

Author_Institution

LITIS, INSA Rouen, Rouen

fYear

2008

fDate

12-15 Oct. 2008

Firstpage

669

Lastpage

674

Abstract

Estimation of epipolar geometry can be done automatically in on-board stereovision systems, using interest points that are detected and matched. However, image disturbance that can happen in real-life situations can considerably lower the performance. A reliability score computing method is proposed, based on a fuzzy logic classifier. Its input is the data extracted from the estimation process. The classifier is trained with artificial image disturbance, using a set of typical image pairs. Results show that the computed score is indeed related to the performance of estimation.

Keywords

automobiles; calibration; fuzzy logic; image classification; object detection; reliability; stereo image processing; traffic engineering computing; artificial image disturbance; embedded stereovision system; epipolar geometry; fuzzy-logic classifier; on-board stereovision systems; real-time obstacle detection systems; reliability estimation; reliability score computing method; self calibration; Calibration; Cameras; Covariance matrix; Data mining; Face detection; Image motion analysis; Intelligent transportation systems; Optical computing; Transmission line matrix methods; Uncertainty;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Transportation Systems, 2008. ITSC 2008. 11th International IEEE Conference on

Conference_Location

Beijing

Print_ISBN

978-1-4244-2111-4

Electronic_ISBN

978-1-4244-2112-1

Type

conf

DOI

10.1109/ITSC.2008.4732707

Filename

4732707