期刊名称：International Journal of Advanced Research in Computer Engineering & Technology (IJARCET)
印刷版ISSN：2278-1323
出版年度：2015
卷号：4
期号：5
页码：1754-1758
出版社：Shri Pannalal Research Institute of Technolgy
摘要：This paper proposes a robust face annotation technique by mining weakly labeled facial images. One challenging problem for face annotation scheme is how to effectively perform annotation by exploiting the list of most similar facial images and their weak labels that are often noisy and incomplete. To tackle this problem, we propose an effective face annotation method for refining the labels of web facial images using machine learning techniques. On a training set of images with annotations, we compute feature vectors of image features which allow us to predict the probability of generating a word given the image regions. This may be used to automatically annotate and retrieve images given a word as a query. We formulate the learning problem as a convex optimization and develop effective optimization algorithms to solve the large scale learning task efficiently. To further speed up the proposed scheme, we also propose a clustering algorithm which can improve the scalability considerably.
