Jet-Based Local Image Descriptors

Publication: Research - peer-reviewArticle in proceedings – Annual report year: 2012

View graph of relations

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
TitleComputer Vision – ECCV 2012 : Workshops and Demonstrations, Part III
PublisherSpringer
Publication date2012
Pages638-650
ISBN (print)978-3-642-33711-6
ISBN (electronic)978-3-642-33712-3
DOIs
StatePublished

Conference

Conference12th European Conference on Computer Vision (ECCV 2012)
CountryItaly
CityFlorence
Period07/10/1213/10/12
Internet addresshttp://eccv2012.unifi.it/
NameLecture Notes in Computer Science
Volume7584
ISSN (Print)0302-9743
CitationsWeb of Science® Times Cited: No match on DOI
Download as:
Download as PDF
Select render style:
APAAuthorCBEHarvardMLAStandardVancouverShortLong
PDF
Download as HTML
Select render style:
APAAuthorCBEHarvardMLAStandardVancouverShortLong
HTML
Download as Word
Select render style:
APAAuthorCBEHarvardMLAStandardVancouverShortLong
Word

ID: 12618892