Human activity recognition (HAR) is a highly prized application in the pattern recognition
and the computer vision fields. Up till now, deep neural networks have acquired big attention …

In recent years, human action recognition systems have been increasingly developed to
support a wide range of application areas, such as surveillance, behaviour analysis …

Abstract Analysis of human interaction is one important research topic of human motion
analysis. It has been studied either using first-person vision (FPV) or third-person vision …

In this paper, we propose to improve the traditional use of RNNs by employing a many to
many model for video classification. We analyze the importance of modeling spatial layout …

In this paper, we study how different skeleton extraction methods affect the performance of
action recognition. As shown in previous work skeleton information can be exploited for …

Abstract Activity Recognition from RGB-D videos is still an open problem due to the
presence of large varieties of actions. In this work, we propose a new architecture by mixing …

In this paper, we propose efficient method which combines skeleton information and
appearance features for daily-living action recognition. Many RGB methods focus only on …

We propose a novel unsupervised method that assesses the similarity of two videos on the
basis of the estimated relatedness of the objects and their behavior, and provides arguments …

The emergence of low-cost depth cameras creates potential for RGB-D based human action
recognition. However, most of the existing RGB-D based approaches simply concatenate …

Human action recognition is the process of labeling image sequences with action labels.
Robust solutions to this problem have applications in domains such as medical care, human …