For those of you using OpenCV that are looking to upgrade from OpenNI 1.x to the new OpenNI 2.x, here’s a bit of code to make life a tiny bit easier. It simply wraps the OpenNI 2.x APIs to expose a simple frame grabber for OpenCV.
I wanna share some code for 2D curve tracking with a particle filter, implementing the body of work of Tony Heap and David Hogg. These guys presented a relatively easy to implement method for tracking deformable curves through space and change in form using a Hierarchical Point Distribution Models (HPDM), which is another elegant way to store shape priors. Granted, it is not perfect, but for a simple 2D shape like a hand it works pretty good, and rather fast as well.
Let’s dive in then,
Sharing a bit of code I created for skin detection.
I wanna share some code I’ve been working on lately that implements smooth shape manipulation using Moving Least Squares. More specifically, the excellent simple and powerful method by Schaefer et al. from Texas A&M and Rice universities (great paper). The method was written for image deformation but very straightforward modifications made it work perfectly for 2D shapes and open curves.
Let’s get down to business
I’m so glad to be back to work on a graphics project (of which you will probably hear later), because it takes me back to reading papers and implementing work by talented people. I want share a little bit of utilities I’ve developed for working with 2D curves in OpenCV.
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.
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.
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…
To use it:
Go on this page,
Watch the short instruction video,
download the application (MacOSX-Intel-x64 Win32)
and make yourself a model!
It takes just a couple of minutes and it’s very simple…
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.