When scanning, we recommend the following for best results.
How to Scan
Imagine your iPhone/iPad is a digital spray can, and the captured points are paint
- Try to get a smooth, even coat of paint over the entire area you would like to scan, and make sure you get in all the nooks and crannies!
- Avoid jerky movements while scanning and limit large left<->right rotations.
When possible, keep your device between 3 - 12 feet (1 - 4 meters) away from the things that you are scanning.
Where/When to Scan
Avoid scanning outdoors or in direct sunlight.
- If you need to scan outdoors, wait for an overcast day, and plan to scan during the morning or late afternoon when the sun is lower in the sky.
Make sure your iPhone/iPad does not get too hot.
- If the ambient temperature is over 75°F (24°C) or you are making multiple scans in a row, try to let the back of your device cool as much as possible before starting a new scan.
- If the device gets too hot, it will throttle the CPU, drastically reducing scan performance.
- Removing your device's case and turning on Airplane Mode can help keep it cool.
Make sure your iPhone/iPad has at least 50% battery.
What to Scan
Try to always keep feature-rich objects (ie. things with clear details or sharp edges) in the frame while scanning.
- Looking only at homogeneous objects, like blank walls or the sky, for more than a couple of seconds can cause the iPhone/iPad’s tracking to drift, which will miss-align points.
Understanding Feature Detection (For Advanced Users)
Feature detection, in simple terms, is the process by which a computer vision algorithm identifies and locates important points, edges, or regions in an image. These important points are called features. By finding and tracking these features, the algorithm can better understand the content of the image and recognize objects, patterns, or structures within it. This process is crucial for 3D scanning systems like SiteScape.
To help you understand how different scenes or objects can affect feature detection, let's use a mental model called the "texture spectrum." Imagine a spectrum with two ends: on one end, we have a completely uniform surface (like a white wall), and on the other end, we have a highly textured surface (like a brick wall).
Feature detection works best when there's a good amount of texture in the scene because it can identify unique features to track. So, a brick wall would be great for feature detection, while a plain white wall would be challenging. When analyzing a scene or object, consider where it falls on the "texture spectrum." The more texture and distinctive patterns it has, the easier it will be for feature detection to work creating a high-quality scan.