Efficient Face Retrieval Based on Bag of Facial Features

Yuanjia Du, Ling Shao, Pierre Archambeau, Sébastien Erpicum, Michel Pirotton

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review


In this chapter, the authors present an efficient retrieval technique for human face images based on a bag of facial features. A visual vocabulary is built beforehand using an invariant descriptor computed on detected image regions. The vocabulary is refined in two ways to make the retrieval system more efficient. Firstly, the visual vocabulary is minimized by only using facial features selected on face regions which are detected by an accurate face detector. Secondly, three criteria, namely Inverted-Occurrence-Frequency Weights, Average Feature Location Distance and Reliable Nearest-Neighbors, are calculated in advance to make the on-line retrieval procedure more efficient and precise. The proposed system is experimented on the Caltech Human Face Database. The results show that this technique is very effective and efficient on face image retrieval.
Original languageEnglish
Title of host publicationAdvances in Face Image Analysis
EditorsYu-Jin Zhang
Place of PublicationHershey, PA
PublisherIGI Global
Number of pages404
ISBN (Print)9781615209910
Publication statusPublished - 2011


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