We present a powerful solution to the problem of vector set classification, based on a novel
goodness-of-fit metric, referred to as signal subspace matching (SSM). Unlike the existing …

Subspace methods are popular for image set classification due to the excellent
representation ability of subspaces. Generalized difference subspace and orthogonal …

Manifold learning has been effectively used in computer vision applications for
dimensionality reduction that improves classification performance and reduces …

In this paper, we investigate the contribution of dynamic evolution of 3D faces to identity
recognition. To this end, we adopt a subspace representation of the flow of curvature-maps …

With the abundance of video data, the interest in more effective methods for recognizing
faces from surveillance videos has grown. However, most algorithms proposed in this field …

This paper presents a novel video-based face recognition algorithm by using a sequential
sampling and updating scheme, named sequential sample consensus. The proposed …

We develop a methodology for classifying defects based on their morphology and induced
mechanical response. The proposed approach is fairly general and relies on morphological …

Classification on Grassmann manifolds has found application in computer vision problems
because it yields improved accuracy and fast computation times. Grassmann manifolds map …

Computational performance associated with high-dimensional data is a common challenge
for real-world classification and recognition systems. Subspace learning has received …

Manifold learning has been effectively used in computer vision applications for
dimensionality reduction that improves classification performance and reduces …