Course Content

ABSTRACT

Face detection is an interesting area in research application of computer vision and pattern recognition, especially during the past several years. It is also plays a vital role in surveillance systems which is the first steps in face recognition systems. The high degree of variation in the appearance of human faces causes the face detection as a complex problem in computer vision. The face detection systems aimed to decrease false positive rate and increase the accuracy of detecting face especially in complex background images. The main aim of this project is to present an up-to-date review of face detection methods including feature-based, appearance-based, and knowledge-based and template matching. Also, it presents the effect of applying Haar-like features along with neural networks.

1.1  INTRODUCTION

Face detection also refers to the psychological process by which humans locate and attend to faces in a visual scene. Face Detection is the first and essential step for face recognition, and it is used to detect faces in the images. Face detection technology can be applied to various fields including security, biometrics, law enforcement, entertainment and personal safety to provide surveillance and tracking of people in real time.

Face recognition has been a subject of intensive research due to increasing security demands and its potential in commercial and law enforcements.

Facial feature extraction is very much important for the initialization of processing techniques like face tracking, facial expression recognition or face recognition. We proposed a technique to detect different facial features like nose, mouth, jaw        , eyes, eyebrows of a person facing webcam using python and open cv with the help of Dlib package (library).

System Requirements:

A. Hardware Requirement:-

•      System            :         Pentium IV 2.4 GHz.    

•      Hard Disk       :         500 GB.

•      Ram                :         4 GB.

•      Any desktop / Laptop system with above configuration or higher level.

B. Software Requirements:-

•      Operating system               :         Windows XP / 7

•      Coding Language               :         Python

•      Interpreter                                    :         Pyhton 3.6

•      IDE                                                      :         Python IDE

•      ML APIS                           :         Sklearn, numpy, Open CV, Dlib

Conclusion:

The recognition of human faces plays an important role in many applications, for example in video surveillance and the management of facial image databases. Face detection and eyes extraction has an important role in many applications such as face recognition, facial expression analysis, security login etc. We proposed a technique to detect different facial features like nose, mouth ,jaw, eyes ,eyebrows of a person facing webcam using python and opencv with the help of dlib package (library).