FACIAL RECOGNITION SYSTEM
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seminar projects crazy
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30-01-2009, 11:58 PM


Facial recognition systems are used for identification solutions, by translating the characteristics of a face into a unique set of numbers. Facial recognition technology introduces a new era of internet and e-commerce security. Using this it has been able to move to the forefront in using new modern security solutions for prisons. This technology has been used by Tampa police department, which allows snapshots of faces from the crowd to be compared to a database of criminal mug shots. People have an amazing ability to recognize and remember thousands of faces; in this edition you?ll learn how computers are turning your face into computer code so it can be compared to thousands, if not millions, of other faces. We'll also look at how facial recognition software is being used in elections, criminal investigations and to secure your personal computers.
Use Search at http://topicideas.net/search.php wisely To Get Information About Project Topic and Seminar ideas with report/source code along pdf and ppt presenaion
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pprachi
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28-01-2011, 11:52 AM

i want a project and implimentation report and ppt for same topic..
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seminar surveyer
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29-01-2011, 10:49 AM

to get information about the topic face recognition technology full report ppt, and related topics refer the link bellow

topicideashow-to-face-recognition-technology-a-seminar and presentation-report

topicideashow-to-face-recognition-technology-a-seminar and presentation-report?page=4

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topicideashow-to-FACE-RECOGNITION-TECHNOLOGY-SEMINAR-REPORT--28533

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topicideashow-to-face-recognition-technology-a-seminar and presentation-report?page=5

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topicideashow-to-face-recognition-technology-a-seminar and presentation-report?page=3

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topicideashow-to-face-recognition-using-neural-networks-download-seminar and presentation-report

topicideashow-to-face-recognition-using-the-techniques-base-on-principal-component-analysis-pca
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priyankadongari
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#4
12-03-2011, 03:04 PM

can u mail me dis ppt....... dis is my id priyanka.d6390@gmail.com
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seminar-database
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20-05-2011, 09:39 PM

Hi priyanka,
the report can be downloaded from the link given above. We would ask you to download it from here rather than mailing the report to individuals Smile
topicideashow-to-face-recognition-technology-a-seminar and presentation-report
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seminar flower
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05-07-2012, 10:48 AM

FACIAL RECOGNITION SYSTEM


.docx   FACIAL RECOGNITION SYSTEM.docx (Size: 321.28 KB / Downloads: 26)
ABSTRACT

Facial recognition system is a computer application for automatically identifying or verifying a person from a digital image or a video frame from a video source. One of the ways to do this is by comparing selected facial features from the image and a facial database. It is typically used in security systems and can be compared to other biometrics such as fingerprint or eye iris recognition systems.
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, providing a sort of compressed face representation.

INTRODUCTION

General

Recognizing faces is something that people usually do effortlessly and without much conscious thought, yet it has remained a diff icult problem in the area of computer vision, where some 20 years of research is just beginning to yield useful technological solutions. As a biometric technology, automated face recognition has a number of desirable properties that are driving research in to practical techniques.
The problem of face recognition can be stated as ‘identifying an individual From images of the face’ and encompasses a number of variations other than the most familiar application of mug shot identification. One notable aspect of face recognition is the broad interdisciplinary nature of the interest in it: within computer recognition and pattern recognition; biometrics and security; multimedia processing; psychology and neuroscience. It is a field of research notable for the necessity and the richness of interaction between computer scientists and psychologists.

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, providing a sort of compressed face representation.

Privacy Issues

Many citizens express concern that their privacy is being compromised by the use of surveillance technologies by corporations and the state. Some fear that it could lead to a “total surveillance society,” with the government and other authorities having the ability to know the whereabouts and activities of all citizens around the clock. This knowledge has, is and could continue to be deployed to prevent the lawful exercise of rights of citizens to criticize those in office, specific government policies or corporate practices. Many centralized power structures with such surveillance capabilities have abused their privileged access to maintain control of the political and economic apparatus and curtail populist reforms.

Recent Improvements

In 2006, the performance of the latest face recognition algorithms were evaluated in the Face Recognition Grand Challenge (FRGC). High-resolution face images, 3-D face scans, and iris images were used in the tests. The results indicated that the new algorithms are 10 times more accurate than the face recognition algorithms of 2002 and 100 times more accurate than those of 1995. Some of the algorithms were able to outperform human participants in recognizing faces and could uniquely identify identical twins.
U.S. Government-sponsored evaluations and challenge problems have helped spur over two orders-of-magnitude improvement in face-recognition system performance. Since 1993, the error rate of automatic face-recognition systems has decreased by a factor of 272. The reduction applies to systems that match people with face images captured in studio or mugshot environments. In Moore's law terms, the error rate decreased by one-half every two years.

Face as a Biometric

Face recognition for recent survey has a number of strengths to recommend it over other biometric modalities in certain circumstances, and corresponding weaknesses that make it an inappropriate choice of biometric for other applications. Face recognition as a biometric derive a number of advantages from being the primary biometric that humans use to recognize
one another. Some of the earliest identification tokens, i.e. portraits, use thisbiometric as an authentication pattern. Furthermore it is well-accepted andeasily understood by people, and it is easy for a human operator to arbitrate machine decisions — in fact face images are often used as a human-verifiable backup to automated fingerprint recognition systems.
Because of its prevalence as an institutionalized and accepted guarantor of identity since the advent of photography, there are large legacy systems based on face images—such as police records, passports and driving licences that are currently being automated. Video indexing is another example of legacy data for which face recognition, in conjunction with speaker identification ,is a valuable tool.
Face recognition has the advantage of ubiquity and of being universal over the major biometrics, in that everyone has a face and everyone readily displays the face (Whereas, for instance, fingerprints are captured with much more difficulty and a significant proportion of the population has fingerprints that cannot be captured with quality sufficient for recognition.) Uniqueness, another redesirable characteristic for a biometric, is hard to claim at current levels of Achievements and Challenges in Fingerprint Recognition accuracy. Since face shape, especially when young, is heavily influenced bygenotype, identical twins are very hard to tell apart with this technology.

Imaging changes

lighting variation; camera variations; channel characteristics (especially in broadcast, or compressed images).
Sample variations of a single face: in pose, facial appearance, age, lighting and expression. No current system can claim to handle all of these problems well. In particular there has been little research on making face recognition robust to the effects of aging the faces. In general, constraints on the application scenario and capture situation are used to limit the amount of invariance of face image sample that needs to be afforded algorithmically. The main challenges of face recognition today are handling rotation in depth and broad lighting changes, together with personal appearance changes. Even under good conditions, however, accuracy needs to be improved.





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