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.
Unsupervised face recognition from image sequences based on clustering with attraction and repulsion
01.01.2001
668239 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Unsupervised Face Recognition from Image Sequences Based on Clustering with Attraction and Repulsion
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