Depth Estimation Algorithm for Images

The algorithm for determining image depth primarily employs stereo vision principles. Stereo vision, known as stereopsis, leverages binocular disparity to perceive depth by analyzing two slightly offset images. A practical implementation involves calculating a disparity map through pixel-wise comparison of stereo image pairs. Key steps include: 1) Stereo calibration to align camera parameters, 2) Feature matching using methods like SIFT or ORB to identify corresponding points, 3) Disparity computation through block matching or semi-global matching (SGM) algorithms. The resulting disparity values are inversely proportional to depth, following the formula: depth = (baseline × focal_length) / disparity. OpenCV implementations typically use functions like StereoBM or StereoSGBM for efficient disparity calculation, followed by depth map generation through triangulation. This approach provides quantitative depth measurements for objects in the scene, enabling applications in robotics, 3D reconstruction, and autonomous navigation.