Object Detection is to locate the presence of objects and types or classes of the located objects in an image. Face detection is a particular case of Object Detection. The objective of face detection is to find and locate faces in an image. It is the first step in automatic face recognition applications. Face detection has been well studied for frontal and near frontal faces. There are many techniques in the field of face detection. For example, Viola-Jones face detector, (R-CNN), (YOLO), etc. Viola and Jone’s face detector is the most well-known face detection algorithm based on Haar-like features and cascade AdaBoost classifier.

** VIOLA JONES ALGORITHM**

Paul Viola and Michael Jones had proposed the algorithm in 2001. It is the first framework for object detection which gave viable results for real-time situations. It aims to target the problem of face detection and can be trained to detect different object classes. It’s implementation is available in OpenCV as cvHaarDetectObjects(). It is preferred for its robust nature and its fast detection of faces (full frontal upright faces)in practical situations.

It comprises of four stages namely:

• Haar Feature Selection.
• Creating an integral image.
• Adaboost Training.
• Cascading Amplifiers

Given an image, the algorithm looks at many smaller subregions. It tries to find a face by looking for specific features in each subregion

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