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Proceedings Paper

Photo-collection representation based on viewpoint clustering
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Paper Abstract

The users of digital cameras often take multiple photographs of the same scene. Such multiple shots usually have a special meaning to the photographer, and require further actions, e.g. selection of the best exposure/composition/portrait or stitching several images into a panorama or composite image. We present a method of fast retrieval of all groups of shots taken from the same viewpoint. This task is different from the recently emerged near-duplicate detection problem because, in our case, the multiple shots differ not only by photometric and simple geometric transformations; they can have a little or no overlap, and large variations of objects may be presented. Therefore, we solve a general multiple image registration problem by extracting local image descriptors, their matching, and recovering geometric transformation between images. Initially, the photo-collection is divided in time-based clusters, which are then refined by extracting connected components from the global image registration graph. The method has been applied to real consumer photo-collections, and we show that depending on individual camera usage styles, user collections contain from 15% to 90% of photos requiring further attention. The presented system automates the otherwise manual work of selecting a series of similar images.

Paper Details

Date Published: 28 November 2007
PDF: 12 pages
Proc. SPIE 6833, Electronic Imaging and Multimedia Technology V, 683302 (28 November 2007); doi: 10.1117/12.756602
Show Author Affiliations
Alexander Sibiryakov, Mitsubishi Electric ITE B.V. (United Kingdom)

Published in SPIE Proceedings Vol. 6833:
Electronic Imaging and Multimedia Technology V
Liwei Zhou; Chung-Sheng Li; Minerva M. Yeung, Editor(s)

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