Just sharing some code and ideas for matching 2D curves. I was working for a while on matching 2D curves to discover shapes in images, but it didn't work out, what did succeed is this 2D curve matcher that seems to be very robust for certain applications. It's based on ideas from the Heat Kernel Signature and the CSS Image (that I introduced in my latest post), all around inspecting curves under different level of smoothing.
Continue reading "2D curve matching in OpenCV [w/ code]"
So I was contacted earlier by someone asking about the Head Pose Estimation work I put up a while back. And I remembered that I needed to go back to that work and fix some things, so it was a great opportunity.
I ended up making it a bit nicer, and it's also a good chance for us to review some OpenCV-OpenGL interoperation stuff. Things like getting a projection matrix in OpenCV and translating it to an OpenGL ModelView matrix, are very handy.
Let's get down to the code.
Continue reading "Head Pose Estimation with OpenCV & OpenGL Revisited [w/ code]"
Sorry for the bombardment of posts, but I want to share some stuff I've been working on lately, so when I find time I just shoot the posts out.
So this time I'll talk shortly about how to get an estimation of a rigid transformation between two clouds, that potentially are also of different scale. You will end up with a rigid transformation (Rotation Translation) and a scale factor, son in fact it will be a Similarity Transformation. We will first find the right scale, and then find the right transformation, given there is one (but we will find the best transformation there is).
Continue reading "Registering point clouds rigidly with scale using PCL [w/code]"
I've been working feverishly to straighten up the Structure from Motion Toy Library, and make it more robust. During my experiments with different methods I wanted to test out a different method for decomposing the Essential matrix to rotation R and translation t, other than that of Hartley and Zisserman using SVD. That's when I came upon this paper: here by Berthold Horn from 1990, that traces the steps of Longuet-Higgins who came up with the derivation for the Essential matrix. It has a closed form solution that works pretty well, and here it is implemented with the Eigen math library (a very good library to get to know).
Continue reading "Decomposing the Essential matrix using Horn and Eigen [w/code]"
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.
Let's get down to business...
Continue reading "Structure from Motion and 3D reconstruction on the easy in OpenCV 2.3+ [w/ code]"
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.
I've been working on implementing a face image relighting algorithm using spherical harmonics, one of the most elegant methods I've seen lately.
I start up by aligning a face model with OpenGL to automatically get the canonical face normals, which brushed up my knowledge of GLSL. Then I continue to estimating real faces "spharmonics", and relighting.
I would like to present something I have been working on recently, a work that immensely affect what I wrote in the blog in the past two years...
This work is an academic research project, Please please, take the time to fill out the survey! It is very short..
The results of the survey (the survey alone, no photos of your work) will possibly be published in an academic paper.
Note: No information is sent anywhere in any way outside of your machine (you may even unplug the network). All results are saved locally on your computer, and no inputs are recorded or transmitted. The application contains no malware. The source is available here.
Note II: All stock photos of models used in the application are released under Creative Commons By-NC-SA 2.0 license. Creator: http://www.flickr.com/photos/kk/. If you wish to distribute your results, they should also be released under a CC-By-NC-SA 2.0 license.
Just wanted to share of some code I've been writing.
So I wanted to create a food classifier, for a cool project down in the Media Lab called FoodCam. It's basically a camera that people put free food under, and they can send an email alert to the entire building to come eat (by pushing a huge button marked "Dinner Bell"). Really a cool thing.
OK let's get down to business.
Continue reading "A simple object classifier with Bag-of-Words using OpenCV 2.3 [w/ code]"
I wanted to put up a quick note on how to use Kalman Filters in OpenCV 2.2 with the C++ API, because all I could find online was using the old C API. Plus the kalman.cpp example that ships with OpenCV is kind of crappy and really doesn't explain how to use the Kalman Filter.
I'm no expert on Kalman filters though, this is just a quick hack I got going as a test for a project. It worked, so I'm posting the results.
Continue reading "Simple Kalman filter for tracking using OpenCV 2.2 [w/ code]"