Robust Real Time Face detection automatically from video sequence based on Haar features

The automatic human face detection from sequences of video plays vital role in intelligent human computer interaction systems for video surveillance, face recognition, emotion recognition and face database management. This paper proposes an automatic and robust method to detect human faces from the background that is capable of processing images rapidly while achieving high detection rates from video sequences. Highlight of the face detection system is to identify and locate all faces regardless of their position, scale, orientation, lighting conditions, expressions etc. The field of work is the incorporation of a normalization technique based on local histograms to alleviate a common problem in conventional face detection methods such as: inconsistent performance due to sensitivity to variation illuminations such as local shadowing, noise and occlusion. Next the Haar-like rectangle features can be computed very rapidly using the integral image that is most suitable for face/non face classification. In the final step, the face region is detected through a cascade of classifier consisting of detectors with Adaboost algorithm. Experimental result is showing promising results by conducting the experiments on video sequence as against the existing work on images.