Associating faces and names in japanese photo news articles

We propose a system which extracts faces and person names from news articles with photos on the Web and associates them automatically. The system detects face images in news photos with a face detector and extracts person names from news text with a morphological analyzer. In addition, the bag-of-keypoints representation is applied to the extracted face images for filtering out non-face images. The system uses the eigenface representation as image features of the extracted faces, and associates them with the extracted names by the modified k-means clustering in the eigenface subspace. In the experiment, we obtained the 66% precision rate at most regarding association of faces and names. © 2010 National Institute of Informatics.