2010 was a year full of visual experiments for me, I hope that you like what you see on this blog. In this post I’m making a little overview of all visual experiments created by me during this year. This is an opportunity to catch-up something you’ve missed! I’d like also to thanks some person that have been helping me too:

• Olafur Haraldsson: for creating the photogrammetry forum
• Josh Harle: for his videos tutorials and his nice blog
• You: for reading this

Visual experiments created in 2010:

During this year I have added some features to Ogre3D:

• ArToolKitPlus: augmented reality marker-based system
• Cuda: for beginner only (at least advanced user could grab some useful code)
• OpenCL: for beginner only (at least advanced user could grab some useful code)
• Html5 Canvas: implementation based on skia for graphics and V8 for javascript scripting
• Kinect: this is a very hacky solution, I’ll improve it later

I also have learned GPGPU programming by myself while coding a partial GPUSurf implementation based on Nico Cornelis paper. But this implementation is not complete and I’m willing to rewrite it with a GPGPU framework based on OpenGL and CG only (not Ogre3D). With such a framework writing Sift/Surf detector should be easier and more efficient.

I have created some visual experiments related to Augmented Reality:

• Remote AR prototype
• Outdoor 3D tracking using point cloud generated by structure from motion software
• Outdoor 2D tracking using panorama image

My outdoor 3D tracking algorithm for augmented reality needs an accurate point cloud: this is why I’m interested in structure from motion and I’ve created two SfM toolkit:

• SFMToolkit (SiftGPU -> Bundler -> CMVS -> PMVS2)
• PhotoSynthToolkit (PhotoSynth -> PMVS2)

Posts published in 2010:

• 2010/12/22: Outdoor tracking using panoramic image
• 2010/12/20: Structure from motion projects
• 2010/12/13: Augmented Reality outdoor tracking becoming reality
• 2010/11/20: Kinect experiment with Ogre3D
• 2010/11/19: PhotoSynthToolkit results
• 2010/11/09: PhotoSynth Toolkit updated
• 2010/11/05: Structure From Motion Toolkit released
• 2010/09/27: My 5 years old Quiksee competitor
• 2010/09/23: PMVS2 x64 and videos tutorials
• 2010/09/08: Introducing OpenSynther
• 2010/08/22: Dense point cloud created with PhotoSynth and PMVS2
• 2010/08/19: My PhotoSynth ToolKit
• 2010/07/12: Pose Estimation using SfM point cloud
• 2010/07/11: Remote Augmented Reality Prototype
• 2010/07/08: Structure From Motion Experiment
• 2010/06/25: GPU-Surf video demo
• 2010/06/23: GPUSurf and Ogre::GPGPU
• 2010/06/20: Ogre::Canvas, a 2D API for Ogre3D
• 2010/05/09: Ogre::OpenCL and Ogre::Canvas
• 2010/04/26: Cuda integration with Ogre3D
• 2010/04/09: Multitouch prototype done using Awesomium and Ogre3D
• 2010/03/05: ArToolKitPlus integration with Ogre3D
• 2010/02/20: Hello World !

So the idea is simple: the client uploads a video frame and the server does the pose estimation and send back the augmented rendering to the client. My first prototype is using ArToolKitPlus in almost real-time (15fps) but I’m also working on a markerless version that would be less interactive (< 1fps). The mobile client was an UMPC (Samsung Q1).

Thanks to Boost.Asio I’ve been able to produce a strong client/server very quickly. Then I have created two implementations of PoseEstimator :

class PoseEstimator
{
	public:
		bool computePose(const Ogre::PixelBox& videoFrame);
		Ogre::Vector3 getPosition() const;
		Ogre::Quaternion getOrientation() const;
}

• ArToolKitPoseEstimator (using ArToolKitPlus to get pose estimation)
• SfMPoseEstimator (using EPnP and a point cloud generated with Bundler -Structure from Motion tool- to get pose estimation)

ArToolKitPoseEstimator

There is nothing fancy about this pose estimator, I’ve just implemented this one as proof of concept and to check my server performance. In fact, ArToolKit pose estimation is not expensive and can run in real-time on a mobile.

SfMPoseEstimator

I’ll just introduce the concept of this pose estimator in this post. So the idea is simple, in augmented reality fake rolex you generally know the object you are looking at because you want to augment it. The idea was to create a point cloud of the object you want to augment (using Structure from Motion) and keep the link between the 3D points and theirs 2D descriptors. Thus when you take a shot of the scene you can compare the 2D descriptors of your shot with those of the point cloud and so create 2D/3D correspondence. Then the pose estimation can be estimated by solving the Perspective-n-Point camera calibration problem (using EPnP for example).

Performance

The server is very basic, it doesn’t handle client queuing yet (1 client = 1 thread), but it already does the off-screen rendering and send back the texture in raw RGB.

The version using ArToolKit is only Replica Handbag running at 15fps because I had trouble with the jpeg compression so I turn it off. So this version is only bandwidth limited. I didn’t investigate this issue that much because I know that the SfMPoseEstimator is going to be limited by the matching step. Furthermore I’m not sure that it’s a good idea to send highly compressed image to the server (compression artifact can add extra features).

My SfMPoseEstimator is also working but it’s very expensive (~1s using the GPU) and it’s not always accurate due to some flaws of my original implementation. I’ll explain how it works in my following post.

I have decided to release a sample demo showing how to integrate easily ArToolKitPlus with Ogre3D.

In this sample I have created a tiny webcam video capture class using OpenFramework ofVideoInput.

The resulting demo is showing a dancing Ogre over a marker :

You can download both binary and source code in the corresponding demos section.