2D Image Mapping and 3D Distance Computation

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Resource Overview

Humans perceive depth by observing the three-dimensional world from different viewpoints. This program simulates depth perception by mapping 2D images to 3D space and calculating corresponding distances, implementing stereo vision algorithms through pixel coordinate transformation and triangulation methods.

Detailed Documentation

Human depth perception originates from observing objects in three-dimensional space from multiple perspectives. This program simulates this capability by mapping 2D images into 3D coordinate systems and computing spatial distances. The implementation involves key computer vision techniques: camera calibration for intrinsic parameters, feature point extraction using algorithms like SIFT or ORB, and stereo matching to establish correspondence between image points. Distance calculation employs triangulation principles based on parallax differences, with depth values derived through geometric transformations between pixel coordinates and real-world measurements. The core function utilizes OpenCV's perspective transformation modules and custom distance calculation algorithms to convert 2D image features into quantifiable 3D spatial relationships.

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