In this paper, we propose a novel approach to compute rotation-invariant features from
histograms of local noninvariant patterns. We apply this approach to both static and dynamic …

Texture analysis is a very important area in the field of computer vision and related fields.
There are a good number of databases developed by different research groups for various …

In this paper, a local spatiotemporal descriptor, namely, the volume local binary count
(VLBC), is proposed for the representation and recognition of dynamic texture. This …

Human activity recognition is central to many practical applications, ranging from visual
surveillance to gaming interfacing. Most approaches addressing this problem are based on …

In this paper, we propose a new texture descriptor for both static and dynamic textures. The
new descriptor is built on the wavelet-based spatial-frequency analysis of two …

The range space of dynamic textures spans spatiotemporal phenomena that vary along
three fundamental dimensions: spatial texture, spatial texture layout, and dynamics. By …

The dynamics of complex systems generally include high-dimensional, nonstationary, and
nonlinear behavior, all of which pose fundamental challenges to quantitative understanding …

Visual texture is a powerful cue for the semantic description of scene structures that exhibit a
high degree of similarity in their image intensity patterns. This paper describes a statistical …

Many researchers focus on the local feature-based description of the dynamic texture,
because of its stability and low dimensionality. Among the existing dynamic texture …

In this paper, we developed a novel tool called dynamic fractal analysis for dynamic texture
(DT) classification, which not only provides a rich description of DT but also has strong …