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
Link To Document