Face recognition has become a significant challenge today since an increasing number of
individuals wear masks to avoid infection with the novel coronavirus or Covid-19. Due to its …

Activity recognition in video is dominated by low-and mid-level features, and while
demonstrably capable, by nature, these features carry little semantic meaning. Inspired by …

System theoretic approaches to action recognition model the dynamics of a scene with
linear dynamical systems (LDSs) and perform classification using metrics on the space of …

A novel method for crowd flow modeling and anomaly detection is proposed for both
coherent and incoherent scenes. The novelty is revealed in three aspects. First, it is a unique …

Much of the existing work on action recognition combines simple features with complex
classifiers or models to represent an action. Parameters of such models usually do not have …

In this paper, we propose an approach for recognizing human actions based on motion
sequence information in RGB-D video using deep learning. A new representation that gives …

A shape-motion prototype-based approach is introduced for action recognition. The
approach represents an action as a sequence of prototypes for efficient and flexible action …

Visual recognition of human actions in video clips has been an active field of research in
recent years. However, most published methods either analyse an entire video and assign it …

Slow Feature Analysis (SFA) extracts slowly varying features from a quickly varying input
signal [1]. It has been successfully applied to modeling the visual receptive fields of the …

This paper focuses on a classification problem for volatile time series. One of the most
popular approaches for time series classification is dynamic time warping and feature-based …