• DocumentCode
    1278077
  • Title

    Reliable determination of object pose from line features by hypothesis testing

  • Author

    Chang, Chin-Chun ; Tsai, Wen-Hsiang

  • Author_Institution
    Dept. of Comput. & Inf. Sci., Nat. Chiao Tung Univ., Hsinchu, Taiwan
  • Volume
    21
  • Issue
    11
  • fYear
    1999
  • fDate
    11/1/1999 12:00:00 AM
  • Firstpage
    1235
  • Lastpage
    1241
  • Abstract
    To develop a reliable computer vision system, the employed algorithm must guarantee good output quality. In this study, to ensure the quality of the pose estimated from line features, two simple test functions based on statistical hypothesis testing are defined. First, an error function based on the relation between the line features and some quality thresholds is defined. By using the first test function defined by a lower bound of the error function, poor input can be detected before estimating the pose. After pose estimation, the second test function can be used to decide if the estimated result is sufficiently accurate. Experimental results show that the first test function can detect input with low qualities or erroneous line correspondences and that the overall proposed method yields reliable estimated results
  • Keywords
    attitude measurement; computer vision; image recognition; statistical analysis; computer vision system; erroneous line correspondences; error function; line features; lower bound; object pose determination; quality thresholds; statistical hypothesis testing; Application software; Calibration; Cameras; Computer errors; Computer vision; Poles and towers; Robot vision systems; Senior members; System testing; Yield estimation;
  • fLanguage
    English
  • Journal_Title
    Pattern Analysis and Machine Intelligence, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0162-8828
  • Type

    jour

  • DOI
    10.1109/34.809118
  • Filename
    809118