Pedestrian detection and tracking have become an important field in the computer vision
research area. This growing interest, started in the last decades, might be explained by the …

Estimating count and density maps from crowd images has a wide range of applications
such as video surveillance, traffic monitoring, public safety and urban planning. In addition …

Automatic emotion recognition has become a trending research topic in the past decade.
While works based on facial expressions or speech abound, recognizing affect from body …

In real-world crowd counting applications, the crowd densities vary greatly in spatial and
temporal domains. A detection based counting method will estimate crowds accurately in …

This paper introduces VEDAI: Vehicle Detection in Aerial Imagery a new database of aerial
images provided as a tool to benchmark automatic target recognition algorithms in …

Paper-by-paper results make it easy to miss the forest for the trees. We analyse the
remarkable progress of the last decade by discussing the main ideas explored in the 40+ …

Face detection is one of the most studied topics in computer vision literature, not only
because of the challenging nature of face as an object, but also due to the countless …

Pedestrian detection is a key problem in computer vision, with several applications that have
the potential to positively impact quality of life. In recent years, the number of approaches to …

Feature extraction, deformation handling, occlusion handling, and classi? cation are four
important components in pedestrian detection. Existing methods learn or design these …

Multi-resolution image features may be approximated via extrapolation from nearby scales,
rather than being computed explicitly. This fundamental insight allows us to design object …