Traffic sign detection and tracking using robust 3D analysis

Marinas Mateos, Javier and Salgado Álvarez de Sotomayor, Luis and Arróspide Laborda, Jon and Camplani, Massimo (2012). Traffic sign detection and tracking using robust 3D analysis. In: "Third International Conference on Emerging Security Technologies (EST 2012)", 05/09/2012 - 07/09/2012, Lisbon, Portugal. pp. 78-81. https://doi.org/10.1109/EST.2012.17.

Description

Title: Traffic sign detection and tracking using robust 3D analysis
Author/s:
  • Marinas Mateos, Javier
  • Salgado Álvarez de Sotomayor, Luis
  • Arróspide Laborda, Jon
  • Camplani, Massimo
Item Type: Presentation at Congress or Conference (Article)
Event Title: Third International Conference on Emerging Security Technologies (EST 2012)
Event Dates: 05/09/2012 - 07/09/2012
Event Location: Lisbon, Portugal
Title of Book: Third International Conference on Emerging Security Technologies (EST 2012)
Date: 2012
Subjects:
Faculty: E.T.S.I. Telecomunicación (UPM)
Department: Señales, Sistemas y Radiocomunicaciones
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

In this paper we present an innovative technique to tackle the problem of automatic road sign detection and tracking using an on-board stereo camera. It involves a continuous 3D analysis of the road sign during the whole tracking process. Firstly, a color and appearance based model is applied to generate road sign candidates in both stereo images. A sparse disparity map between the left and right images is then created for each candidate by using contour-based and SURF-based matching in the far and short range, respectively. Once the map has been computed, the correspondences are back-projected to generate a cloud of 3D points, and the best-fit plane is computed through RANSAC, ensuring robustness to outliers. Temporal consistency is enforced by means of a Kalman filter, which exploits the intrinsic smoothness of the 3D camera motion in traffic environments. Additionally, the estimation of the plane allows to correct deformations due to perspective, thus easing further sign classification.

More information

Item ID: 30496
DC Identifier: http://oa.upm.es/30496/
OAI Identifier: oai:oa.upm.es:30496
DOI: 10.1109/EST.2012.17
Deposited by: Memoria Investigacion
Deposited on: 10 Aug 2014 09:55
Last Modified: 22 Apr 2016 00:46
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