Recent years have witnessed enormous progress in AI-related fields such as computer
vision, machine learning, and autonomous vehicles. As with any rapidly growing field, it …

Intelligent construction is an important construction trend. With the growing number of
intelligent autonomous systems implemented in the construction area, understanding and …

In this paper, we present a novel probabilistic generative model for multi-object traffic scene
understanding from movable platforms which reasons jointly about the 3D scene layout as …

Human motion and behaviour in crowded spaces is influenced by several factors, such as
the dynamics of other moving agents in the scene, as well as the static elements that might …

Pedestrian behavior modeling and analysis is important for crowd scene understanding and
has various applications in video surveillance. Stationary crowd groups are a key factor …

Groups are the primary entities that make up a crowd. Understanding group-level dynamics
and properties is thus scientifically important and practically useful in a wide range of …

In this paper, a deep neural network (Behavior-CNN) is proposed to model pedestrian
behaviors in crowded scenes, which has many applications in surveillance. A pedestrian …

We present a hierarchical model for human activity recognition in entire multi-person
scenes. Our model describes human behaviour at multiple levels of detail, ranging from low …

Compared to other anomalous video event detection approaches that analyze object
trajectories only, we propose a context-aware method to detect anomalies. By tracking all …

Recent measurement based studies reveal that most of the Internet connections are short in
terms of the amount of traffic they carry (mice), while a small fraction of the connections are …