Abstract
We present a general novel image descriptor based on higherorder differential geometry and investigate the effect of common descriptor choices. Our investigation is twofold in that we develop a jet-based descriptor and perform a comparative evaluation with current state-of-the-art descriptors on the recently released DTU Robot dataset. We demonstrate how the use of higher-order image structures enables us to reduce the descriptor dimensionality while still achieving very good performance. The descriptors are tested in a variety of scenarios including large changes in scale, viewing angle and lighting. We show that the proposed jet-based descriptor is superior to state-of-the-art for DoG interest points and show competitive performance for the other tested interest points.
Original language | English |
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Title of host publication | Computer Vision – ECCV 2012 : 12th European Conference on Computer Vision, Florence, Italy, October 7-13, 2012, Proceedings, Part III |
Editors | Andrew Fitzgibbon, Svetlana Lazebnik, Pietro Perona, Yoichi Sato, Cardelia Schmid |
Number of pages | 13 |
Publisher | Springer |
Publication date | 2012 |
Pages | 638-650 |
ISBN (Print) | 978-3-642-33711-6 |
ISBN (Electronic) | 978-3-642-33712-3 |
DOIs | |
Publication status | Published - 2012 |
Event | 12th European Conference on Computer Vision - Florence, Italy Duration: 7 Oct 2012 → 13 Oct 2012 Conference number: 12 |
Conference
Conference | 12th European Conference on Computer Vision |
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Number | 12 |
Country/Territory | Italy |
City | Florence |
Period | 07/10/2012 → 13/10/2012 |
Series | Lecture notes in computer science |
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Volume | 7574 |
ISSN | 0302-9743 |
Keywords
- Faculty of Science