Visual learning is expected to be a continuous and robust process, which treats input images and pixels selectively. In this paper we present a method for subspace learning, which...
Most existing subspace analysis-based tracking algorithms utilize a flattened vector to represent a target, resulting in a high dimensional data learning problem. Recently, subspa...
Xi Li, Weiming Hu, Zhongfei Zhang, Xiaoqin Zhang, ...
A reliable system for visual learning and recognition should enable a selective treatment of individual parts of input data and should successfully deal with noise and occlusions....
In this paper, we introduce a novel incremental subspace based object tracking algorithm. The two major contributions of our work are the Robust PCA based occlusion handling scheme...
Most existing appearance models for visual tracking usually construct a pixel-based representation of object appearance so that they are incapable of fully capturing both global an...