Name
Abstract | ||
|---|---|---|
Recently, more and more computer vision researchers are paying attention to error analysis so as to fulfill various accuracy requirements arising from different applications. As a geometric invariant under projective transformations, cross-ratio is the basis of many recognition and reconstruction algorithms which are based on projective geometry. We propose an efficient way of analyzing localization error for computer vision systems which use cross-ratios in planar localization. By studying the inaccuracy associated with cross-ratio-based computations, we inspect the possibility of using linear transformation to approximate localization error due to 2-D noises of image extraction for reference points. Based on such a computationally efficient analysis, a practical way of choosing point features in an image so as to establish the probabilistically most accurate planar location system using crossratios is developed. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1007/978-3-540-77129-6_62 | PSIVT |
Keywords | Field | DocType |
cross-ratio-based planar localization,computer vision researcher,image extraction,accurate planar location system,projective geometry,computationally efficient analysis,computer vision system,error analysis,practical error analysis,planar localization,localization error,approximate localization error,linear transformation,computer vision,error ellipse,cross ratio | Computer vision,Projective geometry,Computer science,Cross-ratio,Planar,Artificial intelligence,Linear map,Invariant (mathematics),Image extraction,Location systems,Computation | Conference |
Volume | ISSN | ISBN |
4872 | 0302-9743 | 3-540-77128-X |
Citations | PageRank | References |
1 | 0.35 | 15 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jen-Hui Chuang | 1 | 363 | 42.28 |
| Jau Hong Kao | 2 | 34 | 4.81 |
| Horng-Horng Lin | 3 | 146 | 9.01 |
| Yu-Ting Chiu | 4 | 55 | 8.52 |