Visual Place Recognition with Repetitive Structures

Akihiko Torii, Josef Sivic, Tomas Pajdla, Masatoshi Okutomi; The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2013, pp. 883-890

Abstract


Repeated structures such as building facades, fences or road markings often represent a significant challenge for place recognition. Repeated structures are notoriously hard for establishing correspondences using multi-view geometry. Even more importantly, they violate the feature independence assumed in the bag-of-visual-words representation which often leads to over-counting evidence and significant degradation of retrieval performance. In this work we show that repeated structures are not a nuisance but, when appropriately represented, they form an important distinguishing feature for many places. We describe a representation of repeated structures suitable for scalable retrieval. It is based on robust detection of repeated image structures and a simple modification of weights in the bag-of-visual-word model. Place recognition results are shown on datasets of street-level imagery from Pittsburgh and San Francisco demonstrating significant gains in recognition performance compared to the standard bag-of-visual-words baseline and more recently proposed burstiness weighting.

Related Material


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[bibtex]
@InProceedings{Torii_2013_CVPR,
author = {Torii, Akihiko and Sivic, Josef and Pajdla, Tomas and Okutomi, Masatoshi},
title = {Visual Place Recognition with Repetitive Structures},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2013}
}