Qualitative image based localization in indoors environments
Kosecka, J.; Liang Zhou; Barber, P.; Duric, Z.
Computer Vision and Pattern Recognition, 2003. Proceedings. 2003 IEEE Computer Society Conference on
Volume 2, Issue , 18-20 June 2003 Page(s): II-3 - II-8 vol.2
Digital Object Identifier
Summary: Man made indoor environments possess regularities, which can be efficiently exploited in automated model acquisition by means of visual sensing. In this context we propose an approach for inferring a topological model of an environment from images or the video stream captured by a mobile robot during exploration. The proposed model consists of a set of locations and neighborhood relationships between them. Initially each location in the model is represented by a collection of similar, temporally adjacent views, with the similarity defined according to a simple appearance based distance measure. The sparser representation is obtained in a subsequent learning stage by means of learning vector quantization (LVQ). The quality of the model is tested in the context of qualitative localization scheme by means of location recognition: given a new view, the most likely location where that view came from is determined.
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