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
fDate :
11/1/1999 12:00:00 AM
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;
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on