Appearance-Based Robot Discrimination Using Eigenimages

Authors:
Sascha Lange;Martin Riedmiller
Affiliations:
Neuroinformatics Group, Institute for Computer Science and Institute for Cognitive Science, University of Osnabrück, 49069 Osnabrück, Germany;Neuroinformatics Group, Institute for Computer Science and Institute for Cognitive Science, University of Osnabrück, 49069 Osnabrück, Germany
Venue:
RoboCup 2006: Robot Soccer World Cup X
Year:
2006

Citing 5
Cited 2

Application of the Karhunen-Loeve Procedure for the Characterization of Human Faces

IEEE Transactions on Pattern Analysis and Machine Intelligence
Visual learning and recognition of 3-D objects from appearance

International Journal of Computer Vision
Support-Vector Networks

Machine Learning
Pairwise classification and support vector machines

Advances in kernel methods
Eigenfaces for recognition

Journal of Cognitive Neuroscience

Optical Flow Based Detection in Mixed Human Robot Environments

ISVC '09 Proceedings of the 5th International Symposium on Advances in Visual Computing: Part I
Learning visual obstacle detection using color histogram features

Robot Soccer World Cup XV

Quantified Score

Hi-index	0.00

Visualization

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.