In this paper, we propose a novel technique for modelbased recognition of complex object motion trajectories using Gaussian Mixture Models (GMM). We build our models on Principal ...
Faisal I. Bashir, Ashfaq A. Khokhar, Dan Schonfeld
This paper studies the effect of covariance regularization for classific ation of high-dimensional data. This is done by fitting a mixture of Gaussians with a regularized covaria...
Daniel L. Elliott, Charles W. Anderson, Michael Ki...
In video surveillance, the sizes of face images are very small. However, few works have been done to investigate scalerobust face recognition. Our experiments on appearancebased m...
A new method for classification is proposed. This is based on kernel orthonormalized partial least squares (PLS) dimensionality reduction of the original data space followed by a ...
We study the use of kernel subspace methods for learning low-dimensional representations for classification. We propose a kernel pooled local discriminant subspace method and com...