We propose a new method for unsupervised face recognition from time-varying sequences of face images obtained in real-world environments. Two types of forces, attraction and repulsion, operate across the spatio-temporal facial manifolds, to autonomously organize the data without relying on any category-specific information provided in advance. Experiments with real-world data gathered over a period of several months and including both frontal and side-view faces were used to evaluate the method and encouraging results were obtained The proposed method can be used in video surveillance systems or for content-based information retrieval.


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    Title :

    Unsupervised face recognition from image sequences based on clustering with attraction and repulsion


    Contributors:
    Raytchev, B. (author) / Murase, H. (author)


    Publication date :

    2001-01-01


    Size :

    668239 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Unsupervised Face Recognition from Image Sequences Based on Clustering with Attraction and Repulsion

    Raytchev, B. / Murase, H. / IEEE | British Library Conference Proceedings | 2001




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