License
When quoting this document, please refer to the following
URN: urn:nbn:de:0030-drops-18613
URL: http://drops.dagstuhl.de/opus/volltexte/2009/1861/
Go to the corresponding Portal


Rodner, Erik ; Denzler, Joachim

Theory of Learning with Few Examples and Object Localization

pdf-format:
Document 1.pdf (114 KB)


Abstract

Visual object localization and categorization is still a big challenge for current research and gets even more difficult when confronted with few training examples. Therefore we will present a Bayesian concept to enhance state-of-the-art machine learning techniques even when dealing with just a single view of an object category. Furthermore an object localization approach is presented, which can serve as a baseline for researchers within the area of object localization.

BibTeX - Entry

@InProceedings{rodner_et_al:DSP:2009:1861,
  author =	{Erik Rodner and Joachim Denzler},
  title =	{Theory of Learning with Few Examples and Object Localization},
  booktitle =	{Computer Vision in Camera Networks for Analyzing Complex Dynamic Natural  Scenes},
  year =	{2009},
  editor =	{Joachim Denzler and Michael Koch},
  publisher =	{Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik, Germany},
  address =	{Dagstuhl, Germany},
  URL =		{http://drops.dagstuhl.de/opus/volltexte/2009/1861},
  annote =	{Keywords: Object detection, one-shot learning, knowledge transfer},
}

Keywords: Object detection, one-shot learning, knowledge transfer
Seminar: 08422 - Klausurtagung Lehrstuhl Joachim Denzler
Issue Date: 2009
Date of publication: 29.01.2009


DROPS-Home | Fulltext Search | Imprint Published by LZI