Fisher linear discriminant analysis (FDA) and its kernel extension--kernel discriminant analysis (KDA)--are well known methods that consider dimensionality reduction and classific...
Zhihua Zhang, Guang Dai, Congfu Xu, Michael I. Jor...
Linear and affine subspaces are commonly used to describe appearance of objects under different lighting, viewpoint, articulation, and identity. A natural problem arising from the...
Many clustering algorithms fail when dealing with high dimensional data. Principal component analysis (PCA) is a popular dimensionality reduction algorithm. However, it assumes a ...
We present a method that automatically detects chewing events in surveillance video of a subject. Firstly, an Active Appearance Model (AAM) is used to track a subject’s face acr...
Isomap is an exemplar of a set of data driven nonlinear dimensionality reduction techniques that have shown promise for the analysis of images and video. These methods parameteriz...