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Learn Stereo Computer Vision Tutorial, validate concepts with Stereo Computer Vision MCQ Questions, and prepare interviews through Stereo Computer Vision Interview Questions and Answers.
Stereo Vision MCQ
Correspondence, rectified scanlines, disparity maps, and turning two images into metric or relative depth.
Two views
Baseline
Disparity
Pixel shift
Matching
Cost volume
Depth map
Z(x,y)
Stereo vision in practice
Given two calibrated views, find pixel correspondences along epipolar lines (often after rectification), compute disparity, and recover depth via triangulation. Local methods (block matching, SAD/SSD) and global or learning-based matchers trade accuracy, speed, and occlusion handling.
Rectification
Warp both images so epipolar lines are horizontal scanlines—turns 2D search into 1D along rows.
Key ideas
Correspondence
For each pixel in the reference view, find the matching pixel in the second view.
Disparity
Horizontal shift d = x_left − x_right after rectification (sign convention varies).
Cost volume
Stores matching costs over disparities; winner-take-all or optimization (e.g. SGM).
Occlusions
Regions visible in only one image break uniqueness; often detected via consistency checks.
Stereo pipeline
Calibrate → rectify → match → disparity → depth → optional filtering / fusion