Introduction to the Special Section on Deep Learning for Visual Surveillance

We are now living in an era of visual information where data is unceasingly generated and pushed into consumption at astounding rates. A remarkable portion of this sensory input comes in the form of videos streaming from large-scale surveillance infrastructures as well as consumer-grade monitoring systems. The sheer amount of ground-based, aerial and mobile video surveillance data demands fittingly competent, accurate, effective techniques to extract useful cues and provide assistance for detection, prevention, and intervention tasks in traffic, safety, security, defense, forensic, health, biology, ethology, and retail space management applications.