3D Reconstruction Using Stereo Vision and Template Matching
Introduction In this post, I explain how I performed a 3D reconstruction from two images captured with a stereo system, using computer vision. The main idea is to detect pixels of interest in the left image, find their correspondences in the right image, and compute the 3D position of the real-world point based on the geometry of both cameras. 1. Image Preparation The first step is to enhance the images to facilitate the edge detection process. This is done by applying filters that remove noise without affecting important contours, allowing the detection of sharp, well-defined edges in the images. In this exercise, I used a bilateral filter, as recommended in the assignment, along with the Canny edge detector. The edges detected in the left image will serve as candidates for reconstruction. 2. Pixels of Interest Once the edges have been detected, their coordinates are selected as interest points, but only in the left image. These points represent areas in the image with relevant i...