Depth Estimation

Depth estimation is a fundamental task in computer vision AI that involves estimating the distance of objects in a scene from a camera or sensor. The goal of depth estimation is to create a 3D representation of the scene, which is essential in applications such as autonomous driving, robotics, and virtual reality. Depth estimation can be performed using a variety of techniques, including stereo vision, time-of-flight sensors, and monocular depth estimation.

Stereo vision involves using two or more cameras to capture multiple views of a scene, which are then used to triangulate the depth information. Time-of-flight sensors use a laser or infrared light to measure the time it takes for the light to bounce back from objects in the scene, which provides an estimate of the distance. Monocular depth estimation uses a single camera and deep learning techniques to estimate depth from a single image, making it a more cost-effective solution. Overall, depth estimation is a critical component of computer vision AI, enabling machines to perceive and interact with the world in a more human-like way.