An efficient approach to onboard stereo vision system pose estimation

Angel Domingo Sappa, Fadi Dornaika, Daniel Ponsa, David Gerónimo, Antonio López

    Research output: Contribution to journalArticleResearchpeer-review

    51 Citations (Scopus)

    Abstract

    This paper presents an efficient technique for estimating the pose of an onboard stereo vision system relative to the environment's dominant surface area, which is supposed to be the road surface. Unlike previous approaches, it can be used either for urban or highway scenarios since it is not based on a specific visual traffic feature extraction but on 3-D raw data points. The whole process is performed in the Euclidean space and consists of two stages. Initially, a compact 2-D representation of the original 3-D data points is computed. Then, a RANdom SAmple Consensus (RANSAC) based least-squares approach is used to fit a plane to the road. Fast RANSAC fitting is obtained by selecting points according to a probability function that takes into account the density of points at a given depth. Finally, stereo camera height and pitch angle are computed related to the fitted road plane. The proposed technique is intended to be used in driverassistance systems for applications such as vehicle or pedestrian detection. Experimental results on urban environments, which are the most challenging scenarios (i.e., flat/uphill/downhill driving, speed bumps, and car's accelerations), are presented. These results are validated with manually annotated ground truth. Additionally, comparisons with previous works are presented to show the improvements in the central processing unit processing time, as well as in the accuracy of the obtained results. © 2008 IEEE.
    Original languageEnglish
    Article number4584202
    Pages (from-to)476-490
    JournalIEEE Transactions on Intelligent Transportation Systems
    Volume9
    DOIs
    Publication statusPublished - 1 Sep 2008

    Keywords

    • Camera extrinsic parameter estimation
    • Ground plane estimation
    • Onboard stereo vision system

    Fingerprint

    Dive into the research topics of 'An efficient approach to onboard stereo vision system pose estimation'. Together they form a unique fingerprint.

    Cite this