Wiki: terms from 360°, scanning and surveying.

How a sequence of 360° captures becomes a walkable path on the map.

What a 360° photo is, how it is produced and what it is used for — explained briefly.

How 360° video works, what resolution it needs and where its limits lie.

What artificial intelligence refers to and how it is applied in image processing.

What bitrate describes and why it decides visible quality in 360° video.

What computer vision is and how it is used in image anonymization.

What dynamic range describes and why it is critical for 360° captures.

What edge computing means and why local processing makes the difference for data protection.

How Google Maps and the business profile connect — and what role 360° content plays.

What Street View is, how your own imagery gets there and what the blue lines mean.

How HDR works and why it is indispensable for interiors with windows.

What immersion means and which technical factors decide whether it occurs.

How infrared depth sensors capture rooms and why they struggle outdoors.

How a terrestrial laser scanner works and what it is used for in as-built capture.

How LiDAR measures distance with laser light and where the technology is applied.

What Matterport is, how capture works and which views a tour offers.

Why parallax causes stitching errors in 360° cameras and how to avoid it.

How overlapping photos become a 3D model and where the method reaches its limits.

What a point cloud is, how it is produced and how it becomes floor plans and BIM models.

Why sensor size tells you more about image quality than the megapixel count.

What happens during stitching, why seams appear and how to avoid them.

Which cameras are suitable for Street View contributions and what matters during capture.

How destinations and businesses use 360° content and what it is good for.

How the YOLO method detects objects in a single pass and what it is used for.