Abstract
In this paper, we discuss and analyze two different paradigm of techniques for face detection in images containing human. We discuss the formulation for both the methods, i.e., using hand-crafted features followed by training a simple classifier and an entirely modern approach of learning features from data using neural network. We discussed the theoretical advantages of the special kind of neural network we used, i.e., Convolutional Neural Network. Lastly we ran both the methods to FDDB face detection dataset and provided some qualitative results.
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