DagSemProc.08422.9.pdf
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Theory of Learning with Few Examples and Object Localization
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Dagstuhl Seminar Proceedings, Volume 8422
Series: Dagstuhl Seminar Proceedings (DagSemProc) - License:
Creative Commons Attribution 4.0 International license
- Publication Date: 2009-01-29
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Erik Rodner and Joachim Denzler. Theory of Learning with Few Examples and Object Localization. In Computer Vision in Camera Networks for Analyzing Complex Dynamic Natural Scenes. Dagstuhl Seminar Proceedings, Volume 8422, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2009)
https://doi.org/10.4230/DagSemProc.08422.9
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.
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Keywords
- Object detection
- one-shot learning
- knowledge transfer
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