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Face Clustering Experiments on News Video Images

Subhradeep Kayal
Aalto University School of Science, Finland
Abstract—With the advent of the information age and an explosion in the availability of multimedia data, successful clustering of faces is absolutely essential for many applications such as video indexing and summarization, major cast detection, and even unsupervised face-database generation. This paper compares with each other, the combinations of existing approaches of dimensionality reduction and different methods of clustering on face images detected from a TV news broadcast clip. The real value of the paper is in providing future researchers an introductory overview of possible methods and recommend a method as a good starting point for face clustering from videos.

Index Terms—face clustering, dimensionality reduction, kernel PCA, GPLVM, tSNE, hierarchical clustering.

Cite: Subhradeep Kayal, "Face Clustering Experiments on News Video Images," Journal of Automation and Control Engineering, Vol.1, No.3, pp. 213-216, Sep. 2013. doi: 10.12720/joace.1.3.213-216
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