This paper presents an overview of state-of-the-art methods in activity recognition using
semantic features. Unlike low-level features, semantic features describe inherent …

Accident detection and public traffic safety is a crucial aspect of safe and better community.
Monitoring traffic flow in smart cities using different surveillance cameras plays a crucial role …

Automatic age and gender classification has been widely used in a large amount of
applications, particularly in human-computer interaction, biometrics, visual surveillance …

Human action analytics has attracted a lot of attention for decades in computer vision. It is
important to extract discriminative spatio-temporal features to model the spatial and temporal …

Designing discriminative powerful texture features robust to realistic imaging conditions is a
challenging computer vision problem with many applications, including material recognition …

Conventional representation based classifiers, ranging from the classical nearest neighbor
classifier and nearest subspace classifier to the recently developed sparse representation …

Action visual tempo characterizes the dynamics and the temporal scale of an action, which is
helpful to distinguish human actions that share high similarities in visual dynamics and …

Recognizing human actions in dark videos is a useful yet challenging visual task in reality.
Existing augmentation-based methods separate action recognition and dark enhancement …

Still image-based human action recognition (HAR) is one of the most challenging research
problems in the field of computer vision. Some of the significant reasons to support this claim …

Collaborative representation is an effective way to design classifiers for many practical
applications. In this paper, we propose a novel classifier, called the prior knowledge-based …