Reliable 3D tracking is still a difficult task. Most parametrized 3D deformable models rely on the accurate extraction of image features for updating their parameters, and are pro...
Christian Vogler, Zhiguo Li, Atul Kanaujia, Siome ...
The performance of face recognition systems that use twodimensional (2D) images is dependent on consistent conditions such as lighting, pose and facial expression. We are developi...
Researchers have been working on human face recognition for decades. Face recognition is hard due to different types of variations in face images, such as pose, illumination and e...
Two-dimensional principal component analysis (2DPCA) is based on the 2D images rather than 1D vectorized images like PCA, which is a classical feature extraction technique in face...
The distribution of the apparent 3D shape of human faces across the view-sphere is complex, owing to factors such as variations in identity, facial expression, minor occlusions an...