%0 Journal Article %1 Tuytelaars:2008:LIF:1391081.1391082 %A Tuytelaars, Tinne %A Mikolajczyk, Krystian %C Hanover, MA, USA %D 2008 %I Now Publishers Inc. %J Found. Trends. Comput. Graph. Vis. %K detector feature invariant %N 3 %P 177--280 %R 10.1561/0600000017 %T Local invariant feature detectors: a survey %U http://dx.doi.org/10.1561/0600000017 %V 3 %X In this survey, we give an overview of invariant interest point detectors, how they evolvd over time, how they work, and what their respective strengths and weaknesses are. We begin with defining the properties of the ideal local feature detector. This is followed by an overview of the literature over the past four decades organized in different categories of feature extraction methods. We then provide a more detailed analysis of a selection of methods which had a particularly significant impact on the research field. We conclude with a summary and promising future research directions.

@article{Tuytelaars:2008:LIF:1391081.1391082, abstract = {In this survey, we give an overview of invariant interest point detectors, how they evolvd over time, how they work, and what their respective strengths and weaknesses are. We begin with defining the properties of the ideal local feature detector. This is followed by an overview of the literature over the past four decades organized in different categories of feature extraction methods. We then provide a more detailed analysis of a selection of methods which had a particularly significant impact on the research field. We conclude with a summary and promising future research directions.}, acmid = {1391082}, added-at = {2012-10-14T15:57:31.000+0200}, address = {Hanover, MA, USA}, author = {Tuytelaars, Tinne and Mikolajczyk, Krystian}, biburl = {https://www.bibsonomy.org/bibtex/2cd0299a6029c14a5238fedf2ceb1c1f5/daill}, description = {Local invariant feature detectors}, doi = {10.1561/0600000017}, interhash = {4a1af64db0d54fbff37c3593b947b010}, intrahash = {cd0299a6029c14a5238fedf2ceb1c1f5}, issn = {1572-2740}, issue_date = {January 2008}, journal = {Found. Trends. Comput. Graph. Vis.}, keywords = {detector feature invariant}, month = jul, number = 3, numpages = {104}, pages = {177--280}, publisher = {Now Publishers Inc.}, timestamp = {2012-10-14T15:57:31.000+0200}, title = {Local invariant feature detectors: a survey}, url = {http://dx.doi.org/10.1561/0600000017}, volume = 3, year = 2008 }