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Visual Computing is a relatively new topic and fully connected to machine learning. The concept also is known as Computing Vision, is the area of science that develops theories and methods towards the automatic extraction of useful information contained in images. The goal of this science is to create and transmit that information to machines in an understandable way.
So that we understand better, let's imagine the following scene: you are playing soccer and you kick the goal. The goalkeeper defends. A simple context for humans but extremely complex for computers. The brain processes visual recognizes the ball, its trajectory, its size, probably its weight, and the goalkeeper drives in the correct direction and speed to make the defence. Teaching all this for a machine through combinations and mathematical formulas is very complicated. That is the role of Visual Computing.
We know that human visual works based on an analysis of the image that reaches the retina and is sent to the visual cortex. This will take the image with other images already classified in the brain to define the object, the approximate dimension, and what to do about it. All this happens in fractions of a second. Visual Computing is based on human visual and works with the process of modelling and replicating that visual using ultra-advanced software and hardware.
Applications of Visual Computing range from medicine to industrial robotics. In medicine, the processing of microscopy, radiography, angioplasty, ultrasonography, tomography, and magnetic resonance images, is expected to offer more precise diagnoses on patients.
On the other hand, in the industry, visual computing seeks to offer quality and position calculation and orientation of details for a robotic arm. Military applications are perhaps one of the largest in computer Visual, but only a small part of that work is available to the public. Basic examples include the detection of enemy units and/or homing missiles. More advanced systems send missiles towards an area instead of a specific objective, being that the selection of the objective is made in the processing of the image of the place, made by the missile itself.
Autonomous vehicles also make extensive use of this new technology. Because these must have a level of autonomy that ranges from total to partial, the latter is used only to assist in the task of driving in specific situations. In the case of full autonomy, navigation uses computer Visual to obtain the location, to produce contextual maps, and to detect obstacles. Meanwhile, this technology has not yet reached sufficient maturity to be on the market.
These tasks are applied to the Visual Computing process to carry out the total identification of the images in a wide way and without human effort. The main automation tasks are
Recognition;
ID;
Detection;
Movement;
Scene reconstruction;
Image restoration.
Until recently, the operation of this type of technology was impractical due to the immense amount of computing demanded. With advances in computing, we are seeing an explosion in the use of systems that still imitate those of the brain in an underdeveloped way, with the use of machine learning and artificial intelligence technologies. Advances in these areas are already noticeable, and the future of computer Visual is to integrate powerful and specific systems. It means that even in an initial state, visual computing is incredibly useful.
Visual computing allows you to see molecules magnified thousands of times their size, or three-dimensional representations of entire cities. It is also capable of making the Internet a more intuitive tool, easier for everyone, and is behind the effects of the most advanced movies and the realism of the latest video games. It seems real, but it is not.
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