Previous work has shown that principal component analysis (PCA) of three-dimensional face models can be used to perform recognition to a high degree of accuracy. However, experimen...
In pattern recognition, statistical modeling, or regression, the amount of data is a critical factor affecting the performance. If the amount of data and computational resources ar...
Patrice Simard, Yann LeCun, John S. Denker, Bernar...
We propose a subspace learning algorithm for face recognition by directly optimizing recognition performance scores. Our approach is motivated by the following observations: 1) Di...
Face and facial feature detection plays an important role in various applications such as human computer interaction, video surveillance, face tracking, and face recognition. Effi...
Achieving high accuracy in the presence of expression variation remains one of the most challenging aspects of 3D face recognition. In this paper, we propose a novel recognition a...