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Cited by 934

The DOI matches its Crossref record; 16 of the 16 references it cites were found in a registry or an index.

Recognising panoramas

Brown, Lowe·2003·Proceedings Ninth IEEE International Conference on Computer Vision

Abstract

The problem considered in this paper is the fully automatic construction of panoramas. Fundamentally, this problem requires recognition, as we need to know which parts of the panorama join up. Previous approaches have used human input or restrictions on the image sequence for the matching step. In this work we use object recognition techniques based on invariant local features to select matching images, and a probabilistic model for verification. Because of this our method is insensitive to the ordering, orientation, scale and illumination of the images. It is also insensitive to 'noise' images which are not part of the panorama at all, that is, it recognises panoramas. This suggests a useful application for photographers: the system takes as input the images on an entire flash card or film, recognises images that form part of a panorama, and stitches them with no user input whatsoever.

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Metadata

Authors
Brown, & Lowe
Venue
Proceedings Ninth IEEE International Conference on Computer Vision
Publisher
IEEE
Published
2003
Pages
1218-1225 vol.2
OpenAlex
W3152336969
Cited by
934
References
16
FWCI
21.71
Type
conference paper
Language
en
Open access
closed

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CoChat. (2026). Citation check: Recognising panoramas. https://app.cochat.ai/papers/10.1109/iccv.2003.1238630
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Brown, & Lowe. (2003). Recognising panoramas. Proceedings Ninth IEEE International Conference on Computer Vision. https://doi.org/10.1109/iccv.2003.1238630

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.