Human activity recognition is an active research area in the computer science because it is
widely used in the fields of the security monitoring, health assessment, human machine …

In this paper, we propose a framework for analyzing and understanding human behavior
from depth videos. The proposed solution first employs shape analysis of the human pose …

Personal assistive robots to be realized in the near future should have the ability to
seamlessly coexist with humans in unconstrained environments, with the robot's capability to …

Human activity recognition is a challenging high-level vision task, for which multiple factors,
such as subject, object, and their diverse interactions, have to be considered and modeled …

The visual recognition of transitive actions comprising human-object interactions is a key
component for artificial systems operating in natural environments. This challenging task …

For the effective operation of intelligent assistive systems working in real-world human
environments, it is important to be able to recognise human activities and their intentions. In …

Temporal redundancy and the sheer size of raw videos are the two most common
problematic issues related to video processing algorithms. Most of the existing methods …

Human activity, which usually consists of several actions (sub-activities), generally covers
interactions among persons and/or objects. In particular, human actions involve certain …

Depth information improves skeleton detection, thus skeleton based methods are the most
popular methods in RGB-D action recognition. But skeleton detection working range is …

In this paper we present our experiments with an echo state network (ESN) for the task of
classifying high-level human activities from video data. ESNs are recurrent neural networks …