Face Detection Techniques - Review Writing - IT Assignment Help

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Abstract With the marvelous increase in video and image database there is an incredible need of automatic understanding and examination of information by the intelligent systems as manually it is getting to be plainly distant. Face plays a major role in social intercourse for conveying identity and feelings of a person. Human beings have not tremendous ability to identify different faces than machines. So, automatic face detection system plays an important role in face recognition, facial expression recognition, head-pose estimation, human–computer interaction etc. Face detection is a computer technology that determines the location and size of a human face in a digital image. Face detection has been a standout amongst topics in the computer vision literature. This paper presents a comprehensive survey of various techniques explored for face detection in digital images. Different challenges and applications of face detection are also presented in this paper. At the end, different standard databases for face detection are also given with their features. Furthermore, we organize special discussions on the practical aspects towards the development of a robust face detection system and conclude this paper with several promising directions for future research. Keywords Face detection · Eigen faces · PCA · Feature analysis

Introduction With the rapid increase of computational powers and accessibility of innovative sensing, analysis and rendering equipment and technologies, computers are becoming more and more intelligent. Many research projects and commercial products have demonstrated the capability of a computer to interact with humans in a natural way by looking at people through cameras, listening to people through microphones, understanding these inputs, and reacting to people in a friendly manner. One of the fundamental techniques that enable such natural Human–Computer Interaction (HCI) is face detection. Face detection is the step stone to all facial analysis algorithms, including the face alignment, face modelling, face relighting, face recognition, face verification/authentication, head pose tracking, facial expression tracking/recognition, gender/age recognition, and many more. So, computers can understand face clearly, after that they begin to truly understand people’s thoughts and intentions. Given a digital image, the primary goal of face detection is to determine whether or not there are any faces in the image. This appears as a trivial task for human beings, but it is a very challenging task for computers, and has been one of the top studied research topics in the past few decades. The difficulty associated with face detection can be attributed to many variations in scale, location, orientation (in-plane rotation), pose (out-of-plane rotation), facial expression, lighting conditions, occlusions, etc. A lot of reports are available for face detection in the literature. The field of face detection has made considerable progress in the past decade.

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