Discover concepts, features, and best practices for building great AR experiences.
The basic requirement for any AR experience—and the defining feature of ARKit—is the ability to create and track a correspondence between the real-world space the user inhabits and a virtual space where you can model visual content. When your app displays that content together with a live camera image, the user experiences augmented reality: the illusion that your virtual content is part of the real world.
How World Tracking Works
To create a correspondence between real and virtual spaces, ARKit uses a technique called visual-inertial odometry. This process combines information from the iOS device’s motion sensing hardware with computer vision analysis of the scene visible to the device’s camera. ARKit recognizes notable features in the scene image, tracks differences in the positions of those features across video frames, and compares that information with motion sensing data. The result is a high-precision model of the device’s position and motion.
World tracking also analyzes and understands the contents of a scene. Use hit-testing methods (see the
ARHit class) to find real-world surfaces corresponding to a point in the camera image. If you enable the
plane setting in your session configuration, ARKit detects flat surfaces in the camera image and reports their position and sizes. You can use hit-test results or detected planes to place or interact with virtual content in your scene.
Best Practices and Limitations
World tracking is an inexact science. This process can often produce impressive accuracy, leading to realistic AR experiences. However, it relies on details of the device’s physical environment that are not always consistent or are difficult to measure in real time without some degree of error. To build high-quality AR experiences, be aware of these caveats and tips.
Design AR experiences for predictable lighting conditions. World tracking involves image analysis, which requires a clear image. Tracking quality is reduced when the camera can’t see details, such as when the camera is pointed at a blank wall or the scene is too dark.
Use tracking quality information to provide user feedback. World tracking correlates image analysis with device motion. ARKit develops a better understanding of the scene if the device is moving, even if the device moves only subtly. Excessive motion—too far, too fast, or shaking too vigorously—results in a blurred image or too much distance for tracking features between video frames, reducing tracking quality. The
ARCamera class provides tracking state reason information, which you can use to develop UI that tells a user how to resolve low-quality tracking situations.
Allow time for plane detection to produce clear results, and disable plane detection when you have the results you need. Plane detection results vary over time—when a plane is first detected, its position and extent may be inaccurate. As the plane remains in the scene over time, ARKit refines its estimate of position and extent. When a large flat surface is in the scene, ARKit may continue changing the plane anchor’s position, extent, and transform after you’ve already used the plane to place content.