Abstract
Transformation of high-dimensional images to a low-dimensional feature space using Eigenimages is a well known technique in the field of face recognition. In this paper, we investigate the applicability of this method to the task of discriminating several types of robots by their appearance only. After calculating suitable Eigenimages for Middle Size robots and selecting the most useful ones, a Support Vector Machine is trained on the feature vectors to reliably recognize several types of robots. The computational demands and the integration into a real-time vision system have an important role throughout the discussion.
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Keywords
- Support Vector Machine
- Feature Space
- Computational Demand
- Sample Covariance Matrix
- Autonomous Mobile Robot
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Lange, S., Riedmiller, M. (2007). Appearance-Based Robot Discrimination Using Eigenimages. In: Lakemeyer, G., Sklar, E., Sorrenti, D.G., Takahashi, T. (eds) RoboCup 2006: Robot Soccer World Cup X. RoboCup 2006. Lecture Notes in Computer Science(), vol 4434. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74024-7_51
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DOI: https://doi.org/10.1007/978-3-540-74024-7_51
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