PicSOM experiments in ImageCLEF robot vision

Authors:
Mats Sjöberg;Markus Koskela;Ville Viitaniemi;Jorma Laaksonen
Affiliations:
Adaptive Informatics Research Centre, Aalto University School of Science and Technology, Aalto, Finland;Adaptive Informatics Research Centre, Aalto University School of Science and Technology, Aalto, Finland;Adaptive Informatics Research Centre, Aalto University School of Science and Technology, Aalto, Finland;Adaptive Informatics Research Centre, Aalto University School of Science and Technology, Aalto, Finland
Venue:
ICPR'10 Proceedings of the 20th International conference on Recognizing patterns in signals, speech, images, and videos
Year:
2010

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Abstract

The PicSOM multimedia analysis and retrieval system has previously been successfully applied to supervised concept detection in image and video databases. Such concepts include locations and events and objects of a particular type. In this paper we apply the generalpurpose visual category recognition algorithm in PicSOM to the recognition of indoor locations in the ImageCLEF/ICPR RobotVision 2010 contest. The algorithm uses bag-of-visual-words and other visual features with fusion of SVM classifiers. The results show that given a large enough training set, a purely appearance-based method can perform very well - ranked first for one of the contest's training sets.