Biometric recognition refers to the automated recognition of individuals based on their
biological and behavioral characteristics such as fingerprint, face, iris, and voice. The first …

Automatic identity recognition from ear images represents an active field of research within
the biometric community. The ability to capture ear images from a distance and in a covert …

Information fusion is a key step in multimodal biometric systems. The fusion of information
can occur at different levels of a recognition system, ie, at the feature level, matching-score …

Privacy is one of the most important social and political issues in our information society,
characterized by a growing range of enabling and supporting technologies and services …

Three-dimensional morphable models (3DMMs) are powerful statistical tools for
representing the 3D shapes and textures of an object class. Here we present the most …

The possibility of identifying people by the shape of their outer ear was first discovered by
the French criminologist Bertillon, and refined by the American police officer Iannarelli, who …

Identity recognition using local features extracted from ear images has recently attracted a
great deal of attention in the intelligent biometric systems community. The rich and reliable …

Human recognition with biometrics is a rapidly emerging area of computer vision. Compared
to other well-known biometric features such as the face, fingerprint, iris, and palmprint, the …

A completely revised and updated edition that teaches the essentials of forensic biology,
with increased coverage of molecular biological techniques and new information on wildlife …

A face-swap deep fake replaces a person's face--from eyebrows to chin--with another face.
A lip-sync deep fake replaces a person's mouth region to be consistent with an …