Abstract
This paper proposes a novel cluster-based face image retrieval algorithm.By using normalized cuts(NCuts)to cluster faces in each time span into optimal partitions,various face images of the same character can be grouped together. A face recognition classifier learned by real AdaBoost is used for measuring similarity between two faces,and a similarity measure for the query face and the face cluster is further proposed for retrieval.To further improve the performance,we design an online step,in which users can interactively label false positives and missing retrieval,so that some constraints are involved to revise the clustering results.The algorithm is integrated into an automatic retrieval system,and the experiment on a family album containing over a thousand face images confirms its effectiveness in comparison to other alternative algorithms.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
