With augmented reality (AR), digital content is added to a live camera feed to give the impression that it is a real component of the environment.
In actuality, this may mean anything from giving you a giraffe-like appearance to superimposing digital directions over the actual streets nearby. You may use augmented reality to play a digital board game on a cereal box or visualise how furnishings would look in your living room. In order for the AR system to add appropriate digital content at the proper location, it is necessary in all of these scenarios to interpret the physical environment from the camera feed. This distinguishes AR from VR, where users are transported into entirely virtual worlds, and it is accomplished utilising computer vision.Table of Content:
How does augmented reality work?
Now that you are aware of what Augmented Reality Technology is, how does it operate? First, computer vision interprets the camera feed’s material to determine what is in the user’s environment. This enables it to display online material pertinent to what the user is viewing.Rendering is the process of displaying digital stuff realistically so that it appears to be a component of the real environment. Let’s use a specific example to help make this obvious before going into more detail. Think of using a real cereal box as the physical support for playing an augmented reality board game, as seen in the illustration below.
First, the cereal box is identified by computer vision after processing the camera’s raw image. That starts the game. The graphics module adds the AR game to the original frame while carefully ensuring that it overlaps the cereal box. It does this by using the computer vision-determined 3D position and orientation of the box.
Since augmented reality is real-time, everything mentioned above must occur each time a new frame is received from the camera. We only have 30 milliseconds to do all of this because most current phones operate at a frame rate of 30 per second. The AR feed that you view through the camera is frequently delayed by about 50 milliseconds to accommodate for all of this, yet our brains do not notice!
Why does AR need computer vision?
Even if computers still have a very tough time comprehending visuals, the human brain is still incredibly adept at it. Computer vision is a major area of computer science that is devoted to it. Understanding the environment surrounding the user in terms of both semantics and 3D geometry is necessary for augmented reality.Semantics provides a solution to the “what” query, such as identifying the cereal box or the presence of a face in the image. Geometry provides a solution to the query “where?” and deduces the location and orientation of objects in 3D space, such as cereal boxes and faces. Geometry is necessary for AR content to be displayed at the proper location and angle, which is crucial for making it appear to be a part of the real environment. For each domain, we frequently need to create new techniques. For instance, computer vision techniques that are effective for a cereal box are very different from those that are effective for a face.
World semantics and geometry. Traditionally, these two characteristics have been understood using very distinct computer vision techniques. Thanks to Deep Learning, which typically determines what is in an image without worrying about its 3D shape, we have made significant progress in the semantics area.
It allows for the simplest kinds of AR on its own. For instance, if computer vision identifies an object, we may show pertinent data floating on the screen, but it won’t appear to be attached to the actual object. The geometric component of computer vision, which draws on projective geometry notions, would be needed to accomplish this2. To properly anchor the AR game when we display it, we need to know the location and orientation of the cereal box in relation to the camera.
How does AR display digital content?
Every augmented reality experience needs some kind of predetermined logic. The digital content that should be triggered when something is recognised is specified here. The rendering module of the live AR system, which is the last stage of the AR pipeline, shows the pertinent content onto the camera feed after recognition.It’s incredibly difficult to make this quick and realistic, especially for wearable displays like glasses (another very active area of research). Consider computer vision as inverse rendering for another approach to understanding how AR functions. Computer vision intuitively recognises and comprehends the 3D environment from a 2D image (that a face exists and where it is in the 3D world), allowing us to add digital material (a 3D giraffe mask anchored to the face) that is then projected onto the 2D phone screen.
Since AR is a very active field, we anticipate seeing a lot of fascinating new breakthroughs in the future. AR experiences will advance in their level of immersion and excitement as computer vision becomes increasingly adept at comprehending the world around us. Furthermore, although it can occur on any device with a camera, augmented reality is currently most prevalent on smartphones. We anticipate that this technology will make augmented reality (AR) popular and improve how we live, work, shop, and play when adequate processing power is accessible on AR glasses.
Digitalfren is known for being one of the few Augmented Reality companies in Malaysia where along with developing AR Apps we also develop custom system for companies.
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