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 general-purpose 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.