Design considerations for the processing system of a CNN-based automated surveillance system

Modern surveillance systems combine tens or even hundreds of cameras to ensure a wide area of coverage. With such a large amount of incoming video data, it is difficult for humans to effectively monitor each camera for potential threats. Recent advances in machine learning have brought forth great improvements in computer vision, which forms the key to automating surveillance systems. Previous works on the topic of automated surveillance systems...