takes a look into the automated generation of adaptive training samples a 3D morphable face model. Using statistical insights, the tailored training data guarantees full data variability and is enriched by arbitrary facial attributes such as age or body weight. Moreover, it can automatically adapt to environmental constraints, such as illumination or viewing angle of recorded video footage surveillance cameras. We use the tailored imagery to train a new many-core implementation of Viola Jones’ AdaBoost object detection framework. The new implementation is not only faster but also enables the use of multiple feature channels such as color features at training time.

Fast Face Detector Training Using Tailored Views-Scherbaum_2013_ICCV_paper.pdf

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