DocumentCode :
2178722
Title :
Recognising panoramas
Author :
Brown, M. ; Lowe, D.G.
Author_Institution :
Dept. of Comput. Sci., British Columbia Univ., Vancouver, BC, Canada
fYear :
2003
fDate :
13-16 Oct. 2003
Firstpage :
1218
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.
Keywords :
computer vision; feature extraction; image matching; image reconstruction; image sequences; object recognition; Leverberg-Marquardt algorithm; automatic panorama construction; automatic panorama stitching; camera matrix; digital cameras; feature extraction; feature matching; image illumination; image matching; image ordering; image orientation; image scale; image sequence; invariant local features; local intensity values; multiband blending; nonlinear least squares problem; normalised cross-correlation; object recognition techniques; panorama recognition; panoramic image geometry; panoramic image mosaicing; photographers; scale invariant feature transform; Computer vision;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Vision, 2003. Proceedings. Ninth IEEE International Conference on
Conference_Location :
Nice, France
Print_ISBN :
0-7695-1950-4
Type :
conf
DOI :
10.1109/ICCV.2003.1238630
Filename :
1238630
Link To Document :
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