Document (#40695)

Author
Su, Z.
Li, D.
Li, H.
Luo, X.
Title
Boosting attribute recognition with latent topics by matrix factorization
Source
Journal of the Association for Information Science and Technology. 68(2017) no.7, S.1737-1750
Year
2017
Abstract
Attribute-based approaches have recently attracted much attention in visual recognition tasks. These approaches describe images by using semantic attributes as the mid-level feature. However, low recognition accuracy becomes the biggest barrier that limits their practical applications. In this paper, we propose a novel framework termed Boosting Attribute Recognition (BAR) for the image recognition task. Our framework stems from matrix factorization, and can explore latent relationships from the aspect of attribute and image simultaneously. Furthermore, to apply our framework in large-scale visual recognition tasks, we present both offline and online learning implementation of the proposed framework. Extensive experiments on 3 data sets demonstrate that our framework achieves a sound accuracy of attribute recognition.
Content
Vgl.: http://onlinelibrary.wiley.com/doi/10.1002/asi.23827/full.
Form
Bilder

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