Jet-based local image descriptors

Anders Boesen Lindbo Larsen, Sune Darkner, Anders Lindbjerg Dahl, Kim Steenstrup Pedersen

9 Citations (Scopus)
3877 Downloads (Pure)

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 languageEnglish
Title of host publicationComputer Vision – ECCV 2012 : 12th European Conference on Computer Vision, Florence, Italy, October 7-13, 2012, Proceedings, Part III
EditorsAndrew Fitzgibbon, Svetlana Lazebnik, Pietro Perona, Yoichi Sato, Cardelia Schmid
Number of pages13
PublisherSpringer
Publication date2012
Pages638-650
ISBN (Print)978-3-642-33711-6
ISBN (Electronic)978-3-642-33712-3
DOIs
Publication statusPublished - 2012
Event12th European Conference on Computer Vision - Florence, Italy
Duration: 7 Oct 201213 Oct 2012
Conference number: 12

Conference

Conference12th European Conference on Computer Vision
Number12
Country/TerritoryItaly
CityFlorence
Period07/10/201213/10/2012
SeriesLecture notes in computer science
Volume7574
ISSN0302-9743

Keywords

  • Faculty of Science

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