Within the context of assistive robotics we develop an intelligent interface that provides
multimodal sensory processing capabilities for human action recognition. Human action is …

Over the years, a large number of methods have been proposed to analyze human pose
and motion information from images, videos, and recently from depth data. Most methods …

Human activity recognition is crucial for intuitive cooperation between humans and robots.
We present an approach for activity recognition for applications in the context of human …

Human action and activity recognition from videos has attracted an increasing number of
researchers in recent years. However, most of the works aim at multimedia retrieval and …

A complete prototype for multi-modal interaction between humans and multi-robot systems is
described. The application focus is on search and rescue missions. From the human-side …

In this work, we present a human-centered robot application in the scope of daily activity
recognition towards robot-assisted living. Our approach consists of a probabilistic ensemble …

The recognition of continuous natural gestures is a complex and challenging problem due to
the multi-modal nature of involved visual cues (eg fingers and lips movements, subtle facial …

We present a two-stage framework that deal with the problem of automatically extract human
activities from videos. First, for action recognition we employ an unsupervised state-of-the-art …

We organized a Grand Challenge and Workshop on Multi-Modal Gesture Recognition. The
MMGR Grand Challenge focused on the recognition of continuous natural gestures from …

In this paper, we propose a method to recognize human body movements and we combine it
with the contextual knowledge of human-robot collaboration scenarios provided by an object …