[BibTeX] [RIS]
{Invariant Object Recognition with Slow Feature Analysis}
Type of publication: Inproceedings
Citation: Franzius2008
Booktitle: Proc. 18th Intl. Conf. on Artificial Neural Networks (ICANN'08).
Series: Lecture Notes in Computer Science
Volume: 5163
Year: 2008
Pages: 961--970
Publisher: Springer
Address: Prague
ISSN: 0302-9743
ISBN: 978-3-540-87535-2
URL: http://www.springerlink.com/co...
Abstract: Primates are very good at recognizing objects independently of viewing angle or retinal position and outperform existing computer vision systems by far. But invariant object recognition is only one pre- requisite for successful interaction with the environment. An animal also needs to assess an object’s position and relative rotational angle. We propose here a model that is able to extract object identity, position, and rotation angles, where each code is independent of all others. We demonstrate the model behavior on complex three-dimensional objects under translation and in-depth rotation on homogeneous backgrounds. A similar model has previously been shown to extract hippocampal spatial codes from quasi-natural videos. The rigorous mathematical analysis of this earlier application carries over to the scenario of invariant object recognition.
Userfields: bdsk-url-1={http://www.springerlink.com/content/239862780068tw81/}, date-added={2012-09-23 10:50:23 +0200}, date-modified={2012-09-23 10:50:23 +0200}, file={:home/jim/Desktop/sortedLiterature/sfa+invariances/Invariant Object Recognition with Slow Feature Analysis .pdf:pdf}, project={fremdliteratur},
Keywords: invariances, object localization, Object Recognition, Slow Feature Analysis
Authors Franzius, M
Wilbert, N
Wiskott, L
  • http://www.springerlink.com/co...