Viewing Kinect Data in the New Windows 8 UI
The Kinect SDK is not compatible with WinRT in the sense that software developed using the SDK cannot have a WinRT (Windows RunTime) UI. The reason is that the Kinect SDK is .Net software and you cannot run (full) managed code on the WinRT.
Nevertheless, I want to create software that can show Kinect data in a WinRT UI. For multiple reasons, one being that software written for the WinRT can run on a PC, a tablet, very large screens, now called a Surface, and a Windows Phone. A survey of other solutions, see below, reveals that solutions to this problem are based on networking. Networking allows us to deliver Kinect data anywhere. This then is another reason to work on separating the source of Kinect data from its presentation.
The general solution is to make a client-server system. The server lives in the classic Windows environment, the client is a WinRT app. Communication between client and server is realized using networking technology; preferably the fastest available. The server receives the data from the Kinect and does any processing that involves the Kinect SDK. The client prepares the data for presentation on the screen. If multiple servers are involved, it integrates and time-synchronizes data from several servers. Since I’m a C++, DirectX guy, the server and client are built on just these platforms
Several other solution already exist. Without pretending to be exhaustive, and in any order:
– The KinectMetro App by the WiseTeam
– ‘Using Kinect in a Windows 8 / Metro App’ by InterKnowlogy
– The Kinect Service from Coding4Fun
The KinectMetro App by the WiseTeam
The application by the WiseTeam is described in this blog post. The software is available at Codeplex. The software was written for the Windows 8 Consumer Preview as part of a MS Imagine Cup participation. I’ve downloaded the software, but couldn’t get it to run on the Windows 8 RTM version. The application is based on event aggregation, as found in PRISM, and on WebSockets.
‘Using Kinect in a Windows 8 / Metro App’ by InterKnowlogy
The approach InterKnowlogy took is blogged here. This is the entry point to several blog posts, some videos (Vimeo and Youtube), and a little bit of code. This solution is also written in C# .Net, using WebSockets.
The Kinect Service by Coding4Fun
This software is available from Codeplex. It is not aimed at the WinRT, it aims at distributing Kinect data to a wider spectrum of clients. Hence it can also be used as a base to target the WinRT. Apart from the server, it consists of a WPF client and a phone client. This looks like a high standards, well written solution. Neat! Data transport uses WinSockets (not WebSockets). The code is available in both C# and VB.
In theory, WebSockets are slower than WinSockets. There can be much discussion about what would be the fastest solution under which circumstances. I expect WinSockets to be the fastest solution, therefore I prefer WinSockets.
Also, in theory, a C++ program is faster, and smaller, than an equivalent C# program. There can be much discussion … , therefore I prefer a program written in C++.
Of course, we should do asynchronously, or in parallel, whatever can be done quicker in parallel.
So, what’s a smart way to develop a client server system to show Kinect color and depth data in a WinRT app? For one, we start from SDK samples:
– A sample from the Kinect SDK that elaborates processing depth and color data together.
– A sample the shows how to use WinSockets (in C++).
– A sample that show how to use the WinRT StreamSocket using PPL tasks (yes we will exploit parallelism extensively🙂 .
– Windows Service (optional, see below).
The use of a Windows service is an option for later use. To work with a service instead of a simple console application requires that the server is capable of handling all kinds of exceptional situations, if only by resetting itself. Consider e.g. the case that no Kinect is connected, or if the Kinect is malfunctioning? Etc.? And apart from that, I expect the Kinect SDK to be made available for WinRT applications in due time.
Server side architecture
The general software architecture looks like this:
The test application instantiates the KinectColorDepthServer DLL. The idea is that in case the DLL is run by a service, the DLL can be loaded and dropped easily / frequently so as to prevent problems that relate to long running processes. So every time the client closes the WinSock connection, the application (or service), drops the DLL and creates a new instance.
The KinectColorDepthServer has a simple interface; you can Run it, Stop it and Destroy it. The interface has this neutral character so we can use the same interface for other data sources, like a stereoscopic camera. The server instantiates a Kinect DataSource on a separate thread, and waits until the connection is closed. The Server also creates two WinSock servers and hands references of these servers to the Kinect DataSource. The WinSock servers are created at a relatively high level, so we can configure them at a high level in the call chain. Lifecycle management of the WinSock servers is in parallel.
The Kinect DataSource contains those parts of the Kinect sample that contain, or refer to Kinect SDK code (which cannot be run in the WinRT client). The Kinect DataSource sends pairs of a depth image and a color image in parallel to the client. The main method in the Kinect DataSource deals with mapping the color data to the depth data.
The WinSock server is just the basic WinSock server sample from the Windows SDK documentation.
Client Side Architecture
The WinRT UI application class manages the lifecycle of the application. The MainPage manages the state of the user interface.
The MainPage references the Scene1 class that inherits from the Scene class in My DirectX Framework. This framework organizes standard WinRT DirectX11.1 code in a structure that is similar to the XNA architecture. This latter architecture support easy creation and management of graphical components very well. So, it keeps my code clean and well organized under a growing number of components. I like that, because I like to have oversight.
The Scene1 class refers to the KinectColorDepthclient, which provides the data, and the KinectImage class which contains the DirectX code (a WinRT port) from the Kinect SDK sample, which it uses to display the Kinect data on the screen, using a SwapChainBackgroundPanel. The Scene1 class also references a Camera class (not shown in the diagram) that allows the user to navigate through the 3D scene.
The KinectColorDepthClient creates two StreamSockets, one for depth data, and one for color data. Reception of depth and color images is parallel, then synchronized so as to keep matching color and depth images together. The resulting data is handed over to the KinectImage.
One goal of this architecture is that the KinectColorDepthClient class can be easily replaced by another class, e.g. when Microsoft decides to release a version of the Kinect SDK that is compatible with WinRT. For this reason it has a limited and general interface.
Parallelism is coded making extensive use of PPL task parallelism. PPL Tasks is really a pleasure to use in code.
WinSock2 sockets cannot be used in the WinRT, as it turns out. The alternative at hand is the StreamSocket. However, the StreamSocket still contains a bug. Closing a StreamSocket is done in C++ by calling delete on a StreamSocket object. This however, raises an unhandled exception (that I did not succeed in catching, by the way). It does not only do this in my code, but also in the StreamSocket sample that can be downloaded from MSDN (12 October 2012). A bug report has been filed.
So, now that we have this nice software, just what is the performance, that is, how quick is it, and how large are the programs involved?
Dry testing the transmission speed
To gain an idea of the speed with which data can be transported from one process to another, I sent a 1Mbyte blob from a Winsock2 server to a Winsock2 client 10.000 times, and averaged the transmission time.
Clocking was done using the ‘QueryPerformanceCounter’ function, which is quite high res. The performance counter was queried just before the start of transmission at the server, and just after arrival of the last blob at the client. The difference between the tick counts is then divided by ‘QueryPerformanceFrequency’, which give you the result in seconds. So multiply by 1000 (ms) and divide by the number of cycles (10.000). This shows that transmission of 1Mbyte takes about 1.5 ms (release build).
Now, we are planning to send 640 x 480 pixels (4 bytes each), and an equal nr. of depth values (2 bytes each) over the line. This will take us about 1.5 * (1.843.200 / 1.048.576) = 2.6 ms (wow!). The conclusion is that there will be no noticeable latency.
Visual Studio Performance Analysis
This tool is about finding bottlenecks in your code, so you may remove them. In an analysis run of the server, 5595 samples were taken. The CPU was found executing code I wrote / copied myself in 21.4% of the samples, all in one method. It is possible to examine which lines of code take the most time in that method. I measured an average processing time of these lines of code, and they typically take 1.7 ms (release build, debugger attached) to execute. Well, what can I say? Although I suspect the 21.4% could be improved, we will just leave it as it is.
In a second analysis run, the client application was scrutinized. In this run 2357 samples were taken – I guess it turned out harder to take samples. As little as 2.64% of the samples were in ‘my code’ (that is: 58 samples). Another 8.10% is taken up by DirectX – running shaders for my program, I think. So, in all about 11%. Since the rest of the samples hit code that I cannot touch the source code of, and that we may assume is already well optimized, this is a very fine result.
And how about the size, the footprint? The release build shows a client that has a working set of around 40 Mbyte, and a server with a working set of about 95 Mbyte. Together about 135 Mbyte. Well, that’s not small, but what should we compare it to? The Kinect Service by Coding4Fun, of course!
I downloaded and ran the WPF sample (pre-built). It turns out that the server usually stays under 130Mb, and the client will stay under 67 Mb. Together slightly less than 200Mb.
In conclusion: the footprint of the C++ application is smaller. Its size is 2/3 of the .Net application size, but it is not dramatically smaller.
Below you’ll find a link (picture) to a video demonstrating the Kinect client-server system. First the server is started in a Windows desktop environment, then the user (me🙂 ) switches over to the Start window to start up the client. You can see the client connect to the server – watch the log window at the lower left – and then see the Kinect data on the screen. The stream is stopped and then restarted. That is, in fact, all. The video has been made using Microsoft Expression Encoder Screen Capture. The screen capture has been processed with Encoder, with which we also made the snapshot that serves as the hyperlink to the download site (SkyDrive – Cloud!).
The jitter in the picture is caused by the depth stream. The depth stream consists of depth measurements expressed as the distance from the camera along the normal emanating from the camera, in mm. These measurements are subject to a certain error, or uncertainty, which causes fluctuations in measurements, hence the jitter in the stream.
Filtering away the jitter is high on my agenda.