Dynamic texture and scene classification are two fundamental problems in understanding
natural video content. Extracting robust and effective features is a crucial step towards …

Objective: The goal of this paper is to automatically digitize craniomaxillofacial (CMF)
landmarks efficiently and accurately from cone-beam computed tomography (CBCT) …

Representing dynamic textures (DTs) plays an important role in many real implementations
in the computer vision community. Due to the turbulent and non-directional motions of DTs …

Local binary descriptors, such as local binary pattern (LBP) and its various variants, have
been studied extensively in texture and dynamic texture analysis due to their outstanding …

This work addresses dynamic texture representation and recognition via a convolutional
multilayer architecture. The proposed method considers an image sequence as a …

Understanding the chaotic motions of dynamic textures (DTs) is a challenging problem of
video representation for different tasks in computer vision. This paper presents a new …

In recent years, dynamic texture classification has become an important task for computer
vision. This is a challenging task due to the unknown spatial and temporal nature of dynamic …

Illumination, noise, and changes of environments, scales negatively impact on encoding
chaotic motions for dynamic texture (DT) representation. This paper proposes a new method …

Standard subspace algorithms learn Linear Dynamical Systems (LDSs) from time series with
the least-square method, where the stability of the system is not naturally guaranteed. In this …

Dynamic texture (DT) and scene descriptions are challenging problems in video
understanding that play crucial role in different important applications of computer vision. An …