| ECVision indexed and annotated bibliography of cognitive computer vision publications This bibliography was created by Hilary Buxton and Benoit Gaillard, University of Sussex, as part of ECVision Specific Action 8-1 The complete text version of this BibTeX file is available here: ECVision_bibliography.bib
P. Duygulu and K. Barnard and N. De Freitas and D. Forsyth
ABSTRACT
We describe a model of object recognition as machine trans- lation. In this model, recognition is a process of annotating image regions with words. Firstly, images are segmented into regions, which are clas- si ed into region types using a variety of features. A mapping between region types and keywords supplied with the images, is then learned, us- ing a method based around EM. This process is analogous with learning a lexicon from an aligned bitext. For the implementation we describe, these words are nouns taken from a large vocabulary. On a large test set, the method can predict numerous words with high accuracy. Simple methods identify words that cannot be predicted well. We show how to cluster words that individually are diĘcult to predict into clusters that can be predicted well | for example, we cannot predict the distinction between train and locomotive using the current set of features, but we can predict the underlying concept. The method is trained on a sub- stantial collection of images. Extensive experimental results illustrate the strengths and weaknesses of the approach. |
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