Dimensionality reduction is an important issue when facing high-dimensional data. For supervised dimensionality reduction, Linear Discriminant Analysis (LDA) is one of the most po...
Feiping Nie, Shiming Xiang, Yangqiu Song, Changshu...
Appearance Models (AM) are commonly used to model appearance and shape variation of objects in images. In particular, they have proven useful to detection, tracking, and synthesis...
Fernando De la Torre, Alvaro Collet, Manuel Quero,...
Linear Discriminant Analysis (LDA), which works by maximizing the within-class similarity and minimizing the between-class similarity simultaneously, is a popular dimensionality r...
Linear Discriminant Analysis (LDA) has been a popular method for extracting features which preserve class separability. The projection vectors are commonly obtained by maximizing ...
Linear discriminant analysis (LDA) has been an active topic of research during the last century. However, the existing algorithms have several limitations when applied to visual d...