#Kaleidoscope images software#

We usually think of surveillance cameras as digital eyes, watching over us.

The operators may soon rely on data driven operation control centres which have вЂlearnedвЂ™ with AI to distinguish unusual situations that could represent risk, from normal ones such as technicians checking a rail switch.

Imagine one example: two fuzzy profiles appearing in the foggy night to dart across a rail track a few hundred meters from the train station. This is good news for railway safety and security, helping operators more easily spot crimes and accidents while offering a range of applications. In short, AI is giving surveillance cameras brains to match their eyes, letting them analyse live video and helping operators in the control room to increase their ability to make the right decision. Second, compared to what AI brings to Computer Vision, their detection capabilities are limited. First, VAвЂ™s traditional algorithms are skewed by their extreme sensitivity to the context of usage, including such factors as day/night, crowd, or illumination changes. In fact, this powerful technique is about to replace traditional Video Analytics for two reasons. It then applies that knowledge in interpreting automatically new data such as video-protection scenes(1).

This technique aims to learn from voluminous existing data. One of the key areas currently benefiting from AI is Computer Vision with the implementation of Deep Learning, which uses artificial neural networks to mimic the human brain.

#Kaleidoscope images software#

Transportation represents an area where Artificial Intelligence (AI) is contributing to major innovations such as the upcoming disruption of autonomous trains and cars.ДЄI refers to software systems that can make decisions that normally require a human level of expertise, such as understanding, judgment and intention.