Ear-to-Ear Propagation Model Based on Geometrical Theory of Diffraction

Ear Biometrics Based on Geometrical Feature Extraction

Biometrics identification methods proved to be very efficient, more natural and easy for users than traditional methods of human identification. In fact, only biometrics methods truly identify humans, not keys and cards they posses or passwords they should remember. The future of biometrics will surely lead to systems based on image analysis as the data acquisition is very simple and requires o...

Ear Biometrics Based on Geometrical Method of Feature Extraction

Biometrics identification methods proved to be very efficient, more natural and easy for users than traditional methods of human identification. In fact, only biometrics methods truly identify humans, not keys and cards they posses or passwords they should remember. The future of biometrics leads to passive physiological methods based on images of such parts of human body as face and ear. The a...

Geometrical theory of diffraction.

Ear-to-ear Capture of Facial Intrinsics

We present a practical approach to capturing ear-to-ear face models comprising both 3D meshes and intrinsic textures (i.e. diffuse and specular albedo). Our approach is a hybrid of geometric and photometric methods and requires no geometric calibration. Photometric measurements made in a lightstage are used to estimate view dependent high resolution normal maps. We overcome the problem of havin...

Adopting level set theory based algorithms to segment human ear

Human identification has always been a topic that interested researchers around the world. Biometric methods are found to be more effective and much easier for the users than the traditional identification methods like keys, smart cards and passwords. Unlike with the traditional methods, with biometric methods the data acquisition is most of the times passive, which means the users do not take ...