Visual Place Recognition with Repetitive Structures

Akihiko Torii (1) , Josef Sivic (2, 3) , Tomas Pajdla (4) , Masatoshi Okutomi (1)

1 TITECH - Tokyo Institute of Technology [Tokyo]
2 WILLOW - Models of visual object recognition and scene understanding
3 LIENS - Laboratoire d'informatique de l'école normale supérieure
4 Department of Cybernetics [Prague]

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.

Domaines: Vision par ordinateur et reconnaissance de formes [cs.CV]

Akihiko Torii, Josef Sivic, Tomas Pajdla, Masatoshi Okutomi. Visual Place Recognition with Repetitive Structures. CVPR 2013 - 26th IEEE Conference on Computer Vision and Pattern Recognition, Jun 2013, Portland, United States. ⟨hal-00934288⟩