Face Recognition Technology . Even a passage of time doesn't affect this capability and therefore it would help become as robust as humans in face recognition. Machine recognition of human faces from still or video images has attracted a great deal of attention in the psychology, image processing, pattern recognition, neural science, computer security, and computer vision communities.
Face recognition is probably one of the most non- intrusive and user- friendly biometric authentication methods currently available; a screensaver equipped with face recognition technology can automatically unlock the screen whenever the authorized user approaches the computer. Face is an important part of who we are and how people identify us. It is arguably a person's most unique physical characteristic. While humans have had the innate ability to recognize and distinguish different faces for millions of years, computers are just now catching up. Visionics, a company based in New Jersey, is one of many developers of facial recognition technology.
Technology advancements have increased the overall accuracy of automated face recognition over the past few decades. According to the FBI, this technology can help law enforcement agencies identify criminals in their. This page contains Face Recognition Seminar and PPT with pdf report. Download Face Recognition complete documentation with ppt and pdf for free. Face Recognition is based on Face Biometric Templates. Face Biometric Template is
The twist to its particular software, Face. It, is that it can pick someone's face out of a crowd, extract that face from the rest of the scene and compare it to a database full of stored images.
In order for Face Recognition Technology software to work, it has to know what a basic face looks like. Facial recognition software is designed to pinpoint a face and measure its features. Each face has certain distinguishable landmarks, which make up the different facial features. These landmarks are referred to as nodal points.
There are about 8. Here are a few of the nodal points that are measured by the software: Distance between eyes . This code is called a faceprint. Only 1. 4 to 2. 2 nodal points are needed for the Face. It software to complete the recognition process.
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Software of Face Recognition Technology. Facial recognition software falls into a larger group of technologies known as biometrics.
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Biometrics uses biological information to verify identity. The basic idea behind biometrics is that our bodies contain unique properties that can be used to distinguish us from others. Besides facial recognition, biometric authentication methods also include: .
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Face Recognition Technology seminar report - Download as Word Doc (.doc), PDF File (.pdf), Text File (.txt) or read online. Home - Cognitec develops market-leading face recognition technology and applications for facial image database search, real-time video screening and analytics, biometric photo capturing and border control systems. IC Media Corporation [email protected] Abstract.
The basic processes used by the Face. It system to capture and compare images are: 1. Detection - When the system is attached to a video surveillance system, the recognition software searches the field of view of a video camera for faces.
If there is a face in the view, it is detected within a fraction of a second. A multi- scale algorithm is used to search for faces in low resolution. The system switches to a high- resolution search only after a head- like shape is detected. Alignment - Once a face is detected, the system determines the head's position, size and pose. A face needs to be turned at least 3. Normalization - The image of the head is scaled and rotated so that it can be registered and mapped into an appropriate size and pose. Normalization is performed regardless of the head's location and distance from the camera.
Light does not impact the normalization process. Representation - The system translates the facial data into a unique code. This coding process allows for easier comparison of the newly acquired facial data to stored facial data. Matching - The newly acquired facial data is compared to the stored data and (ideally) linked to at least one stored facial representation. More Seminar Topics: Next Generation Secure Computing Base,NGSCB,On- line Analytical Processing (OLAP),Parallel Virtual Machine,Param - 1. PHANTo. M,Pivot Vector Space Approach in Audio- Video Mixing,Real Time Application Interface,Reconfigurable Computing,Refactoring,Remote Administration Trojan's,Robotic Surgery,Rover Technology,Scientific Archive Management System (SAM),Satellite Radio,SATRACK,Self Defending Networks,Self Organizing Maps,Self- Managing Computing,Semantic Web.