Efficient hybrid monocular-stereo approach to on-board, video-based traffic sign detection and tracking

Marinas Mateos, Javier and Salgado Álvarez de Sotomayor, Luis and Arróspide Laborda, Jon and Camplani, Massimo (2012). Efficient hybrid monocular-stereo approach to on-board, video-based traffic sign detection and tracking. In: "Intelligent Robots and Computer Vision XXIX: Algorithms and Techniques", 23/01/2012 - 24/01/2012, Burlingame, California, USA. pp. 1-15. https://doi.org/10.1117/12.908585.

Description

Title: Efficient hybrid monocular-stereo approach to on-board, video-based traffic sign detection and tracking
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: Intelligent Robots and Computer Vision XXIX: Algorithms and Techniques
Event Dates: 23/01/2012 - 24/01/2012
Event Location: Burlingame, California, USA
Title of Book: Intelligent Robots and Computer Vision XXIX: Algorithms and Techniques
Date: 2012
Volume: 830106
Subjects:
Freetext Keywords: Stereo processing, traffic sign detection and tracking, RANSAC, Kalman filter.
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 propose an innovative method for the automatic detection and tracking of road traffic signs using an onboard stereo camera. It involves a combination of monocular and stereo analysis strategies to increase the reliability of the detections such that it can boost the performance of any traffic sign recognition scheme. Firstly, an adaptive color and appearance based detection is applied at single camera level to generate a set of traffic sign hypotheses. In turn, stereo information allows for sparse 3D reconstruction of potential traffic signs through a SURF-based matching strategy. Namely, the plane that best fits the cloud of 3D points traced back from feature matches is estimated using a RANSAC based approach to improve robustness to outliers. Temporal consistency of the 3D information is ensured through a Kalman-based tracking stage. This also allows for the generation of a predicted 3D traffic sign model, which is in turn used to enhance the previously mentioned color-based detector through a feedback loop, thus improving detection accuracy. The proposed solution has been tested with real sequences under several illumination conditions and in both urban areas and highways, achieving very high detection rates in challenging environments, including rapid motion and significant perspective distortion

More information

Item ID: 30513
DC Identifier: http://oa.upm.es/30513/
OAI Identifier: oai:oa.upm.es:30513
DOI: 10.1117/12.908585
Deposited by: Memoria Investigacion
Deposited on: 13 Sep 2014 08:50
Last Modified: 22 Sep 2014 11:49
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