computer vision

Open source Structure-from-Motion and Multi-View Stereo tools with C++

Structure-from-Motion (SFM) is genuinely an interesting topic in computer vision, Basically making 3D structure from something 2D is absolutely mesmerizing 🙂 There two open source yet very robust tools for SFM, which sometimes compiling them might be complicated, here I will share my experience with you. 1)VisualSFM Prerequisite: 1)Glew Download the glew from SF at http://glew.sourceforge.net/. Do NOT get it from Github as

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Stitching image using SIFT and Homography

This Matlab tutorial I use SIFT, RANSAC, and homography to find corresponding points between two images. Here I have used vlfeat to find SIFT features. Full code is available at my GitHub repository Major steps are: 0.Adding vlfeat to your Matlab workspace:

  1.Detect key points and extract descriptors. In the image below you can see some SIFT key

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Lucas–Kanade method optical flow with MATLAB

In this tutorial, I will show you how to estimate optical flow based on Lucas–Kanade method.  This project has the following scripts: Optical_flow_estimation, myFlow, myWarp, computeColor, flowToColor. The myFlow does the main job, it gets two images and a window length (patch length) and a threshold for accepting the optical flow.  In the following, you see the myFlow.  You can uncomment figure function calls

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6DOF pose estimation with Aruco marker and ROS

ArUco is a simple yet great library for augmented reality applications. In this tutorial, I’m gonna show you how to track ArUco marker and estimate their 6DOF pose with ROS. For this tutorial, you only need a USB camera. You need to calibrate your camera before first. If you don’ know how to that just follow my other tutorial

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