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ICCV
2011
IEEE

iGroup : Weakly supervised image and video grouping

12 years 11 months ago
iGroup : Weakly supervised image and video grouping
We present a generic, efficient and iterative algorithm for interactively clustering classes of images and videos. The approach moves away from the use of large hand labelled training datasets, instead allowing the user to find natural groups of similar content based upon a handful of ”seed” examples. Two efficient data mining tools originally developed for text analysis; min-Hash and APriori are used and extended to achieve both speed and scalability on large image and video datasets. Inspired by the Bag-of-Words (BoW) architecture, the idea of an image signature is introduced as a simple descriptor on which nearest neighbour classification can be performed. The image signature is then dynamically expanded to identify common features amongst samples of the same class. The iterative approach uses APriori to identify common and distinctive elements of a small set of labelled true and false positive signatures. These elements are then accentuated in the signature to increase sim...
Andrew Gilbert, Richard Bowden
Added 11 Dec 2011
Updated 11 Dec 2011
Type Journal
Year 2011
Where ICCV
Authors Andrew Gilbert, Richard Bowden
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