After a long hiatus I’m back with an update. Recently I’ve been upgrading the Structure-from-Motion Toy Library (https://github.com/royshil/SfM-Toy-Library/) to OpenCV 3.x from OpenCV 2.4.x.
Years ago I wanted to implement PTAM. I was young and naïve 🙂
Well I got a few moments to spare on a recent sleepless night, and I set out to implement the basic bootstrapping step of initializing a map with a planar object – no known markers needed, and then tracking it for augmented reality purposes.
This time I’ll discuss a basic implementation of a Structure from Motion method, following the steps Hartley and Zisserman show in “The Bible” book: “Multiple View Geometry”. I will show how simply their linear method can be implemented in OpenCV.
I treat this as a kind of tutorial, or a toy example, of how to perform Structure from Motion in OpenCV.
See related posts on using Qt instead of FLTK, triangulation and decomposing the essential matrix.
Update 2017: For a more in-depth tutorial see the new Mastering OpenCV book, chapter 3. Also see a recent post on upgrading to OpenCV3.
Let’s get down to business…
I sense that a lot of people are looking for a simple triangulation method with OpenCV, when they have two images and matching features.
While OpenCV contains the function cvTriangulatePoints in the triangulation.cpp file, it is not documented, and uses the arcane C API.
Luckily, Hartley and Zisserman describe in their excellent book “Multiple View Geometry” (in many cases considered to be “The Bible” of 3D reconstruction), a simple method for linear triangulation. This method is actually discussed earlier in Hartley’s article “Triangulation“.
I implemented it using the new OpenCV 2.3+ C++ API, which makes it super easy, and here it is before you.
Edit (4/25/2015): In a new post I am using OpenCV’s cv::triangulatePoints() function. The code is available online in a gist.
Edit (6/5/2014): See some of my more recent work on structure from motion in this post on SfM and that post on the recent Qt GUI and SfM library.
Update 2017: See the new Mastering OpenCV3 book with a deeper discussion, and a more recent post on the implications of using OpenCV3 for SfM.