{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 objectâs 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 |
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