Unconstrained face detection: a Deep learning and Machine learning combined approach

In uncontrolled environment the faces present multiple challenges. The primary challenges are occlusion, pose and illumination variation. In such cases it becomes difficult to detect faces for further processing. Convolutional Neural Network (CNN) is a bio-inspired network that learns the way human brain learns. CNN offers deep observation of features present in input image. This paper presents the combined approach to detect faces using deep features extracted by deep CNN and the classification by Cubic Support vector Machine. Area based approach is used for removal of distant faces and background pixels to reduce the processing time required per frame at detection stage.

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