Name
Abstract | ||
|---|---|---|
For many years, various local descriptors that are insensitive to geometric changes such as viewpoint, rotation, and scale changes, have been attracting attention due to their promising performance. However, most existing local descriptors including the SIFT (Scale Invariant Feature Transform) are based on luminance information rather than color information thereby resulting in instability to photometric variations such as shadows, highlights, and illumination changes. In this paper, we propose a novel local descriptor, pi-SIFT that are invariant to both geometric and photometric variations. In order to achieve photometric invariance, we adopt photometric quasi-invariant features based on the dichromatic reflection model. The performance of the proposed descriptor is evaluated with SIFT |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1109/ICPR.2008.4761181 | 19TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, VOLS 1-6 |
DocType | ISSN | Citations |
Conference | 1051-4651 | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jae-Han Park | 1 | 31 | 8.60 |
| Kyungwook Park | 2 | 30 | 4.59 |
| Seung-Ho Baeg | 3 | 20 | 5.98 |
| Moonhong Baeg | 4 | 40 | 7.51 |