Details
| Originalsprache | Englisch |
|---|---|
| Titel des Sammelwerks | Computer Analysis of Images and Patterns |
| Untertitel | 15th International Conference, CAIP 2013 |
| Herausgeber (Verlag) | Springer Heidelberg |
| Seiten | 327-334 |
| Seitenumfang | 8 |
| ISBN (elektronisch) | 978-3-642-40261-6 |
| ISBN (Print) | 9783642402609 |
| Publikationsstatus | Veröffentlicht - 2013 |
| Veranstaltung | 15th International Conference on Computer Analysis of Images and Patterns, CAIP 2013 - York, Großbritannien / Vereinigtes Königreich Dauer: 27 Aug. 2013 → 29 Aug. 2013 |
Publikationsreihe
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Nummer | PART 1 |
| Band | 8047 LNCS |
| ISSN (Print) | 0302-9743 |
| ISSN (elektronisch) | 1611-3349 |
Abstract
Benchmark data sets consisting of image pairs and ground truth homographies are used for evaluating fundamental computer vision challenges, such as the detection of image features. The mostly used benchmark provides data with only low resolution images. This paper presents an evaluation benchmark consisting of high resolution images of up to 8 megapixels and highly accurate homographies. State of the art feature detection approaches are evaluated using the new benchmark data. It is shown that existing approaches perform differently on the high resolution data compared to the same images with lower resolution.
ASJC Scopus Sachgebiete
- Mathematik (insg.)
- Theoretische Informatik
- Informatik (insg.)
- Allgemeine Computerwissenschaft
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Computer Analysis of Images and Patterns : 15th International Conference, CAIP 2013. Springer Heidelberg, 2013. S. 327-334 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 8047 LNCS, Nr. PART 1).
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review
}
TY - GEN
T1 - High-Resolution Feature Evaluation Benchmark
AU - Cordes, Kai
AU - Rosenhahn, Bodo
AU - Ostermann, Jörn
PY - 2013
Y1 - 2013
N2 - Benchmark data sets consisting of image pairs and ground truth homographies are used for evaluating fundamental computer vision challenges, such as the detection of image features. The mostly used benchmark provides data with only low resolution images. This paper presents an evaluation benchmark consisting of high resolution images of up to 8 megapixels and highly accurate homographies. State of the art feature detection approaches are evaluated using the new benchmark data. It is shown that existing approaches perform differently on the high resolution data compared to the same images with lower resolution.
AB - Benchmark data sets consisting of image pairs and ground truth homographies are used for evaluating fundamental computer vision challenges, such as the detection of image features. The mostly used benchmark provides data with only low resolution images. This paper presents an evaluation benchmark consisting of high resolution images of up to 8 megapixels and highly accurate homographies. State of the art feature detection approaches are evaluated using the new benchmark data. It is shown that existing approaches perform differently on the high resolution data compared to the same images with lower resolution.
UR - http://www.scopus.com/inward/record.url?scp=84884490104&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-40261-6_39
DO - 10.1007/978-3-642-40261-6_39
M3 - Conference contribution
AN - SCOPUS:84884490104
SN - 9783642402609
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 327
EP - 334
BT - Computer Analysis of Images and Patterns
PB - Springer Heidelberg
T2 - 15th International Conference on Computer Analysis of Images and Patterns, CAIP 2013
Y2 - 27 August 2013 through 29 August 2013
ER -