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 …

Anomaly analysis is an important component of any surveillance system. In recent years, it
has drawn the attention of the computer vision and machine learning communities. In this …

We introduce a new benchmark" Humans Interacting with Common Objects"(HICO) for
recognizing human-object interactions (HOI). We demonstrate the key features of HICO: a …

Recently still image-based human action recognition has become an active research topic in
computer vision and pattern recognition. It focuses on identifying a person׳ s action or …

In the era of smart campus, unobtrusive methods for students' monitoring is a challenging
task. The monitoring system must have the ability to recognize and detect the actions …

Still image human action recognition (HAR) is a challenging problem owing to limited
sources of information and large intra-class and small inter-class variations which requires …

We propose in this paper to recognize human activities through an unsupervised learning of
finite multivariate generalized Gaussian mixture model. We address an important cue in …

Driver distraction has currently been a global issue causing the dramatic increase of road
accidents and casualties. However, recognizing distracted driving action remains a …

A key technical issue for human intention prediction from observed human actions is how to
discover and utilize the spatio-temporal patterns behind those actions. Inspired by the well …

Action recognition in still images is closely related to various other computer vision tasks like
pose estimation, object recognition, image retrieval, video action recognition and frame …