Robot navigation in crowded public spaces is a complex task that requires addressing a
variety of engineering and human factors challenges. These challenges have motivated a …

When overpopulated cities face frequent crowded events like strikes, demonstrations,
parades or other sorts of people gatherings, they are confronted to multiple security issues …

Crowd behaviour analysis is an emerging research area. Due to its novelty, a proper
taxonomy to organise its different sub-tasks is still missing. This paper proposes a taxonomic …

Detection of groups of interacting people is a very interesting and useful task in many
modern technologies, with application fields spanning from video-surveillance to social …

Modern crowd theories agree that collective behavior is the result of the underlying
interactions among small groups of individuals. In this work, we propose a novel algorithm …

To obtain a more comprehensive activity understanding for a crowded scene, in this paper,
we propose a new problem of panoramic human activity recognition (PAR), which aims to …

We present an unsupervised approach for the automatic detection of static interactive
groups. The approach builds upon a novel multi-scale Hough voting policy, which …

We focus on the problem of planning the motion of a robot in a dynamic multiagent
environment such as a pedestrian scene. Enabling the robot to navigate safely and in a …

This paper proposes a multi–convolutional neural network (CNN)-based system for the
detection, tracking, and recognition of the emotions of dogs in surveillance videos. This …

Detecting groups is becoming of relevant interest as an important step for scene (and
especially activity) understanding. Differently from what is commonly assumed in the …