29-03-2015, 11:01 AM
I want IEEE base paper on face recognisation for technical seminar
Ankita
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face recognition technology seminars topic in ieee format
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I want IEEE base paper on face recognisation for technical seminar
Ankita
30-03-2017, 03:18 PM
Humans are very good at recognizing faces and if complex computers patterns. Even a passage of time does not affect this ability and therefore would help to be as robust as humans in face recognition. Recognizing the machine's human faces for stills or video has attracted a great deal of attention in psychology, image processing, pattern recognition, neural science, computer security, and computer vision communities. Facial recognition is probably one of the most non-intrusive and easy-to-use biometric authentication methods currently available; A screen protector equipped with face recognition technology can automatically unlock the screen whenever the authorized user approaches the computer. The face is an important part of who we are and how they identify us. It can be said that it is the most singular physical characteristic of a person. While humans have had the innate ability to recognize and distinguish different faces for millions of years, computers are now catching up.
Facial recognition is attracting much attention in the society of access to the multimedia information in network. Areas such as network security, content indexing and retrieval, and video compression benefits from facial recognition technology because "people" are the focus of many video. Control of network access through face recognition not only makes hackers virtually impossible to steal your "password", but also increases the use of human-computer interaction. Indexing and / or retrieval of video data based on the appearances of particular individuals will be useful For users such as journalists, political scientists and spectators. For videophone and teleconferencing applications, the attendance of Facial recognition also provides a more efficient coding scheme.
Visionics, a New Jersey based company, is one of many developers of face recognition technology. The turn to your particular software, FaceIt, is that you 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. For Face Recognition Technology software to work, you need to know what a basic face is like. Face recognition software is designed to identify a face and measure its characteristics. Each face has certain distinguishable points of reference, which make up the different facial features. These points of reference are called nodal points. There are about 80 nodal points on a human face. Here are some of the nodal points that are measured by the software:
Distance between eyes
"Width of the nose
Depth of eye receptacles
Cheekbones
Jaw line
Chin
These nodal points are measured to create a numeric code, a string of numbers that represents the face in a database. This code is called faceprint. Only 14 to 22 nodal points are required for the FaceIt software to complete the recognition process.
Facial recognition is attracting much attention in the society of access to the multimedia information in network. Areas such as network security, content indexing and retrieval, and video compression benefits from facial recognition technology because "people" are the focus of many video. Control of network access through face recognition not only makes hackers virtually impossible to steal your "password", but also increases the use of human-computer interaction. Indexing and / or retrieval of video data based on the appearances of particular individuals will be useful For users such as journalists, political scientists and spectators. For videophone and teleconferencing applications, the attendance of Facial recognition also provides a more efficient coding scheme.
Visionics, a New Jersey based company, is one of many developers of face recognition technology. The turn to your particular software, FaceIt, is that you 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. For Face Recognition Technology software to work, you need to know what a basic face is like. Face recognition software is designed to identify a face and measure its characteristics. Each face has certain distinguishable points of reference, which make up the different facial features. These points of reference are called nodal points. There are about 80 nodal points on a human face. Here are some of the nodal points that are measured by the software:
Distance between eyes
"Width of the nose
Depth of eye receptacles
Cheekbones
Jaw line
Chin
These nodal points are measured to create a numeric code, a string of numbers that represents the face in a database. This code is called faceprint. Only 14 to 22 nodal points are required for the FaceIt software to complete the recognition process.
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