• DocumentCode
    690454
  • Title

    OffRoadScene: An Open Database for Unstructured Road Detection Algorithms

  • Author

    Erke Shang ; Haiyang Zhao ; Jian Li ; Xiangjing An ; Tao Wu

  • Author_Institution
    Coll. of Mechatron. & Autom., Nat. Univ. of Defense Technol., Changsha, China
  • fYear
    2013
  • fDate
    14-15 Dec. 2013
  • Firstpage
    779
  • Lastpage
    783
  • Abstract
    We address the problem of unstructured road detection. This paper tries to build a database named OffRoadScene, which addresses the need for experimental data to quantitatively evaluate the performance of different unstructured road detection algorithms. OffRoadScene is comprised of two level of databases. In the first level, each frame document consists of not only image information, but also information of GPS (Global Position System), IMU (Inertial Measurement Unit) and laser scanner. In the second level, original images and corresponding benchmarks are offered. 550 series unstructured road images and 120 various scenarios of images are included currently. In addition, 13 video segments are in video segments file. In support of expanding OffRoadScene, we present a custom-made labeling software for assisting users who wish to add their own images. Finally, we explain how to use this database by evaluating some state-of-the-art unstructured road detection algorithms.
  • Keywords
    Global Positioning System; inertial systems; object detection; roads; traffic engineering computing; visual databases; GPS; Global Position System; IMU; OffRoadScene; custom-made labeling software; inertial measurement unit; laser scanner; open database; unstructured road detection algorithms; Benchmark testing; Conferences; Databases; Detection algorithms; Feature extraction; Roads; Support vector machines; database; ground truth; label software; unstructured road detection algorithm;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Sciences and Applications (CSA), 2013 International Conference on
  • Conference_Location
    Wuhan
  • Type

    conf

  • DOI
    10.1109/CSA.2013.186
  • Filename
    6835712