Face recognition using image-set or video sequence as input tends to be more robust since image-set or video sequence provides much more information than single snapshot about the ...
Generative 3D face models are a powerful tool in computer vision. They provide pose and illumination invariance by modeling the space of 3D faces and the imaging process. The powe...
Pascal Paysan, Reinhard Knothe, Brian Amberg, Sami...
When asked to draw, many people are hesitant because they consider themselves unable to draw well. This paper describes the first system for a computer to provide direction and fe...
Matching near-infrared (NIR) face images to visible light (VIS) face images offers a robust approach to face recognition with unconstrained illumination. In this paper we propose ...
In this paper, we present a novel framework to address
the confounding effects of illumination variation in face
recognition. By augmenting the gallery set with realistically
re...
Software Engineer with 13 years of experience working as a Developer, Architect, and Project Manager. Looking for face recognition technology to address serious business opportunit...
A novel framework called 2D Fisher Discriminant Analysis
(2D-FDA) is proposed to deal with the Small Sample
Size (SSS) problem in conventional One-Dimensional Linear
Discriminan...
Hui Kong, Lei Wang, Eam Khwang Teoh, Jian-Gang Wan...
Facial image analysis is very useful in many applications such as video compression, talking heads, or biometrics. During the last few years, many algorithms have been proposed in ...
Face recognition from video has been extensively studied in recent years. Intuitively, video provides more information than a single image. But problems such as variation in pose ...