We present a novel online face recognition approach for video stream in this paper. Our method includes two stages:
pre-training and online training. In the pre-training phase, our method observes interactions, collects batches of input
data, and attempts to estimate their distributions (Box-Cox transformation is adopted here to normalize rough estimates).
In the online training phase, our method incrementally improves classifiers' knowledge of the face space and updates it
continuously with incremental eigenspace analysis. The performance achieved by our method shows its great potential in
video stream processing.
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