Multiple Face Detection and Recognization

Topics: Facial recognition system, Eigenface, Principal component analysis Pages: 2 (385 words) Published: April 12, 2013
Introduction

The facial recognition has been a problem very worked around the world for many persons; this problem has emerged in multiple fields and sciences, especially in computer science, others fields that are very interested In this technology are: Mechatronic, Robotic, criminalistics, etc. In this article I work in this interesting topic using EmguCV cross platform .Net wrapper to the Intel OpenCV image processing library and C# .Net, these library’s allow me capture and process image of a capture device in real time. The main goal of this article is show and explains the easiest way how implement a face detector and recognizer in real time for multiple persons using Principal Component Analysis (PCA) with eigenface for implement it in multiple fields. Background

facial recognition is a computer application composes for complex algorithms that use mathematical and matricial techniques, these get the image in raster mode(digital format) and then process and compare pixel by pixel using different methods for obtain a faster and reliable results, obviously these results depend of the machine use to process this due to the huge computational power that these algorithms, functions and routines requires, these are the most popular techniques used for solve this modern problem:

TECHNIQUES:

Traditional

Some facial recognition algorithms identify faces by extracting landmarks, or features, from an image of the subject's face. For example, an algorithm may analyze the relative position, size, and/or shape of the eyes, nose, cheekbones, and jaw. These features are then used to search for other images with matching features. Other algorithms normalize a gallery of face images and then compress the face data, only saving the data in the image that is useful for face detection. A probe image is then compared with the face data. One of the earliest successful systems is based on template matching techniques applied to a set of salient facial features,...
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