The capacity to recognize faces under varied poses is a fundamental human ability that
presents a unique challenge for computer vision systems. Compared to frontal face …

One of the major challenges encountered by current face recognition techniques lies in the
difficulties of handling varying poses, ie, recognition of faces in arbitrary in-depth rotations …

In order to overcome the difficulty of password management and improve the usability of
authentication systems, biometric authentication has been widely studied and has attracted …

Various factors, such as identities, views (poses), and illuminations, are coupled in face
images. Disentangling the identity and view representations is a major challenge in face …

Most existing pose robust methods are too computational complex to meet practical
applications and their performance under unconstrained environments are rarely evaluated …

Pose-invariant face recognition (PIFR) refers to the ability that recognizes face images with
arbitrary pose variations. Among existing PIFR algorithms, pose normalization has been …

The field of Automatic Facial Expression Analysis has grown rapidly in recent years.
However, despite progress in new approaches as well as benchmarking efforts, most …

Laughter is clearly an audiovisual event, consisting of the laughter vocalization and of facial
activity, mainly around the mouth and sometimes in the upper face. A major obstacle in …

Feature extraction has always been an important step in face recognition, the quality of
which directly determines recognition result. Based on making full use of advantages of …

The paper addresses the problem of pose-invariant recognition of faces via an MRF
matching model. Unlike previous costly matching approaches, the proposed algorithm …