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.
Tag: augmented reality
You already know I love libQGLViewer. So here a snippet on how to do AR in a QGLViewer widget. It only requires a couple of tweaks/overloads to the plain vanilla widget setup (using the matrices properly, disable the mouse binding) and it works.
The major problems I recognize with getting a working AR from OpenCV’s intrinsic and extrinsic camera parameters are their translation to OpenGL. I saw a whole lot of solutions online, and I contributed from my own experience a while back, so I want to reiterate here again in the context of libQGLViewer, with a couple extra tips.
Hi,
Just wanted to share a bit of code using OpenCV’s camera extrinsic parameters recovery, camera position and rotation – solvePnP (or it’s C counterpart cvFindExtrinsicCameraParams2). I wanted to get a simple planar object surface recovery for augmented reality, but without using any of the AR libraries, rather dig into some OpenCV and OpenGL code.
This can serve as a primer, or tutorial on how to use OpenCV with OpenGL for AR.
Update 2/16/2015: I wrote another post on OpenCV-OpenGL AR, this time using the fine QGLViewer – a very convenient Qt OpenGL widget.
The program is just a straightforward optical flow based tracking, fed manually with four points which are the planar object’s corners, and solving camera-pose every frame. Plain vanilla AR.
Well the whole cpp file is ~350 lines, but there will only be 20 or less interesting lines… Actually much less. Let’s see what’s up
Update: check out my new post about this https://www.morethantechnical.com/2012/10/17/head-pose-estimation-with-opencv-opengl-revisited-w-code/
Hi
Just wanted to share a small thing I did with OpenCV – Head Pose Estimation (sometimes known as Gaze Direction Estimation). Many people try to achieve this and there are a ton of papers covering it, including a recent overview of almost all known methods.
I implemented a very quick & dirty solution based on OpenCV’s internal methods that produced surprising results (I expected it to fail), so I decided to share. It is based on 3D-2D point correspondence and then fitting of the points to the 3D model. OpenCV provides a magical method – solvePnP – that does this, given some calibration parameters that I completely disregarded.
Here’s how it’s done
Hi
Been working hard at a project for school the past month, implementing one of the more interesting works I’ve seen in the AR arena: Parallel Tracking and Mapping (PTAM) [PDF]. This is a work by George Klein [homepage] and David Murray from Oxford university, presented in ISMAR 2007.
When I first saw it on youtube [link] I immediately saw the immense potential – mobile markerless augmented reality. I thought I should get to know this work a bit more closely, so I chose to implement it as a part of advanced computer vision course, given by Dr. Lior Wolf [link] at TAU.
The work is very extensive, and clearly is a result of deep research in the field, so I set to achieve a few selected features: Stereo initialization, Tracking, and small map upkeeping. I chose not to implement relocalization and full map handling.
This post is kind of a tutorial for 3D reconstruction with OpenCV 2.0. I will show practical use of the functions in cvtriangulation.cpp, which are not documented and in fact incomplete. Furthermore I’ll show how to easily combine OpenCV and OpenGL for 3D augmentations, a thing which is only briefly described in the docs or online.
Here are the step I took and things I learned in the process of implementing the work.
Update: A nice patch by yazor fixes the video mismatching – thanks! and also a nice application by Zentium called “iKat” is doing some kick-ass mobile markerless augmented reality.
Hi
I had very high hopes for iPhoneOS 3.1 in the AR arena. With all the hype about it, I naturally thought that with 3.1 developers will be able to bring marker-detection AR to the app-store – meaning, using legal and published APIs. A look around 3.1’s APIs I wasn’t able to find anything that will allow this.
Not all AR is banned. In fact AR apps like Layar will be very much possible, as they rely on compass & gyro to create the AR effect. These don’t require processing the live video feed from the camera, only overlaying data over it. This can be done easily with the new cameraOverlayView property of UIImagePickerController. All you need to do is create a transparent view with the required data, and it will be overlaid on the camera preview.
Sadly, to get marker-detection abilities developers must still hack the system (camera callback rerouting), or use very slow methods (UIGetScreenImage). I can only hope apple will see the potential of letting developers manipulate the live video feed.
Roy.
Hi
I saw the stats for the blog a while ago and it seems that the augmented reality topic is hot! 400 clicks/day, that’s awesome!
So I wanted to share with you my latest development in this field – cross compiling the AR app to the iPhone. A job that proved easier than I originally thought, although it took a while to get it working smoothly.
Basically all I did was take NyARToolkit, compile it for armv6 arch, combine it with Norio Namura’s iPhone camera video feed code, slap on some simple OpenGL ES rendering, and bam – Augmented Reality on the iPhone.
Update: Apple officially supports camera video pixel buffers in iOS 4.x using AVFoundation, here’s sample code from Apple developer.
This is how I did it…
Hi
I have been playing around with NyARToolkit’s CPP implementation in the last week, and I got some nice results. I tried to keep it as “casual” as I could and not get into the crevices of every library, instead, I wanted to get results and fast.
First, NyARToolkit is a derivative of the wonderful ARToolkit by the talented people @ HIT Lab NZ & HIT Lab Uni of Washington. NyARToolkit however was ported to many other different platforms, like Java, C# and even Flash (Papervision3D?), and in the process making it object oriented, instead of ARToolkit procedural approach. NyARToolkit have made a great job, so I decided to build from there.
NyART don’t provide any video capturing, and no 3D rendering in their CPP implementation (they do in the other ports), so I set out to build it on my own. OpenCV is like a second language to me, so I decided to take its video grabbing mechanism wrapper for Win32. For 3D rendering I used the straightforward GLUT library which does an excellent job ridding the programmer from all the Win#@$#@ API mumbo-jumbo-CreateWindowEx crap.
So let’s dive in….