Skip to Main content Skip to Navigation
New interface
Conference papers

Improving People Search Using Query Expansions: How Friends Help To Find People

Thomas Mensink 1 Jakob Verbeek 1 
1 LEAR - Learning and recognition in vision
Inria Grenoble - Rhône-Alpes, LJK - Laboratoire Jean Kuntzmann, Grenoble INP - Institut polytechnique de Grenoble - Grenoble Institute of Technology
Abstract : In this paper we are interested in finding images of people on the web, and more specifically within large databases of captioned news images. It has recently been shown that visual analysis of the faces in images returned on a text-based query over captions can significantly improve search results. The underlying idea to improve the text-based results is that although this initial result is imperfect, it will render the queried person to be relatively frequent as compared to other people, so we can search for a large group of highly similar faces. The performance of such methods depends strongly on this assumption: for people whose face appears in less than about 40% of the initial text-based result, the performance may be very poor. The contribution of this paper is to improve search results by exploiting faces of other people that co-occur frequently with the queried person. We refer to this process as 'query expansion'. In the face analysis we use the query expansion to provide a query-specific relevant set of 'negative' examples which should be separated from the potentially positive examples in the text-based result set. We apply this idea to a recently-proposed method which filters the initial result set using a Gaussian mixture model, and apply the same idea using a logistic discriminant model. We experimentally evaluate the methods using a set of 23 queries on a database of 15.000 captioned news stories from yahoonews. The results show that (i) query expansion improves both methods, (ii) that our discriminative models outperform the generative ones, and (iii) our best results surpass the state-of-the-art results by 10% precision on average.
Document type :
Conference papers
Complete list of metadata
Contributor : Jakob Verbeek Connect in order to contact the contributor
Submitted on : Monday, April 11, 2011 - 12:50:27 PM
Last modification on : Thursday, January 20, 2022 - 5:28:04 PM
Long-term archiving on: : Thursday, March 30, 2017 - 9:25:53 AM




Thomas Mensink, Jakob Verbeek. Improving People Search Using Query Expansions: How Friends Help To Find People. ECCV 2008 - 10th European Conference on Computer Vision, Oct 2008, Marseille, France. pp.86-99, ⟨10.1007/978-3-540-88688-4_7⟩. ⟨inria-00321045v2⟩



Record views


Files downloads