Background subtraction, although being a very well-established field, has required
significant research efforts to tackle unsolved challenges and to accelerate the progress …

This paper proposes a novel bilateral counting network to estimate the accurate and robust
counting result for single-image object counting task. The proposed network is composed of …

As critical infrastructure such as transportation hubs continue to grow in complexity, greater
importance is placed on monitoring these facilities to ensure their secure and efficient …

In this paper, we aim to monitor the flow of people in large public infrastructures. We propose
an unsupervised methodology to cluster people flow patterns into the most typical and …

Background subtraction for foreground detection has been commonly applied for varying
usages to identify objects in motion within a scene, such as that in video surveillance. In fact …

This paper proposes a low-cost but indirect method for occupancy detection and occupant
counting purpose in current and future automotive systems. It can serve as either a way to …

Label imbalance and the insufficiency of labeled training samples are major obstacles in
most methods for counting people in images or videos. In this work, a sparse representation …

Understanding where people are located and how they are moving about in an environment
is critical for operators of large public spaces such as shopping centers, and large public …

Background subtraction for foreground detection has been commonly applied for varying
usages to identify objects in motion within a scene, such as that in video surveillance. In fact …

For many applications in buildings, such as heating, ventilation and air conditioning (HVAC),
lighting control under normal conditions and fast evacuation under emergency conditions …