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Real-Time Estimation of Camera Orientation by Tracking Orthogonal Vanishing Points in Videos

Wael Elloumi,S. Treuillet,R. Leconge

Published 2013 in International Conference on Computer Vision Theory and Applications

ABSTRACT

In man-made urban environments, vanishing points are pertinent visual cues for navigation task. But estimating the orientation of an embedded camera relies on the ability to find a reliable triplet of orthogonal vanishing points in real-time. Based on previous works, we propose a pipeline to achieve an accurate estimation of the camera orientation while preserving a short processing time. Our algorithm pipeline relies on two contributions: a novel sampling strategy among finite and infinite vanishing points extracted with a RANSAC-based line clustering and a tracking along a video sequence to enforce the accuracy and the robustness by extracting the three most pertinent orthogonal directions. Experiments on real images and video sequences show that the proposed strategy for selecting the triplet of vanishing points is pertinent as our algorithm gives better results than the recently published RNS optimal method (Mirzaei, 2011), in particular for the yaw angle, which is actually essential for navigation task.

PUBLICATION RECORD

  • Publication year

    2013

  • Venue

    International Conference on Computer Vision Theory and Applications

  • Publication date

    Unknown publication date

  • Fields of study

    Computer Science

  • Identifiers
    DOI 10.5220/0004214102150222
  • External record

    Open on Semantic Scholar

  • Source metadata

    Semantic Scholar

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