Given a sequence of observable features of a linear dynamical system (LDS), we propose the problem of finding a representation of the LDS which is sparse in terms of a given dict...
Online learned tracking is widely used for it’s adaptive ability to handle appearance changes. However, it introduces potential drifting problems due to the accumulation of erro...
Local coordinate coding has recently been introduced to learning visual feature dictionary and achieved top level performance for object recognition. However, the computational co...
Top-down visual saliency facilities object localization by providing a discriminative representation of target objects and a probability map for reducing the search space. In this...
Linear subspace learning (LSL) is a popular approach to image recognition and it aims to reveal the essential features of high dimensional data, e.g., facial images, in a lower di...