Human activity recognition (HAR) is an important research area in the fields of human
perception and computer vision due to its wide range of applications. These applications …

Human action recognition targets recognising different actions from a sequence of
observations and different environmental conditions. A wide different applications is …

Derived from rapid advances in computer vision and machine learning, video analysis tasks
have been moving from inferring the present state to predicting the future state. Vision-based …

Humans navigate complex crowded environments based on social conventions: they
respect personal space, yielding right-of-way and avoid collisions. In our work, we propose a …

Ensuring human safety is one of the most important considerations within the field of human-
robot interaction (HRI). This does not simply involve preventing collisions between humans …

We propose a method to forecast a vehicle's ego-motion as a distribution over
spatiotemporal paths, conditioned on features (eg, from LIDAR and images) embedded in …

Egocentric action anticipation consists in understanding which objects the camera wearer
will interact with in the near future and which actions they will perform. We tackle the …

Intelligent systems are increasingly part of our everyday lives and have been integrated
seamlessly to the point where it is difficult to imagine a world without them. Physical …

In this paper, we present a method (Action-Fusion) for human action recognition from depth
maps and posture data using convolutional neural networks (CNNs). Two input descriptors …

In this paper, we tackle the problem of egocentric action anticipation, ie, predicting what
actions the camera wearer will perform in the near future and which objects they will interact …