I don't have hololens yet so i'm planning to use the hololens emulator. Problem is, i don't see any documentations for making your own room in the emulator. I just need a table and some kind of plate to be recognized by the hololens.
Is it possible ?
The HoloLens emulator comes with 5 premade rooms that it can emulate for developing against. Here is a screeenshot of where you configure it and where it is available:
There are tables and beds in numerous of these scenes already. You can create your own rooms but you need a HoloLens to do it, or you would need to take an existing mesh and modify it in a 3d modeling tool.
Related
A-Frame's immersive-ar functionality will work on some Android devices I've tested with, but I haven't had success with iOS.
It is possible to use an A-Frame scene for markerless AR on iOS using a commercial external library. Example: this demo from Zapworks using their A-Frame SDK. https://zappar-xr.github.io/aframe-example-instant-tracking-3d-model/
The tracking seems to be no where near as good as A-Frame's hit test demo (https://github.com/stspanho/aframe-hit-test), but it does seem to work on virtually any device and browser I've tried, and it is good enough for the intended purpose.
I would be more than happy to fallback to lower quality AR mode in order to have AR at all in devices that don't support immersive-ar in browser. I have not been able to find an A-Frame compatible solution for using only free/open source components for doing this, only commercial products like Zapworks and 8th Wall.
Is there a free / open source plugin for A-Frame that allows a scene to be rendered with markerless AR across a very broad range of devices, similar to Zapworks?
I ended up rolling my own solution which wasn't complete, but good enough for the project. Strictly speaking, there's three problems to overcome with getting a markerless AR experience on mobile without relying on WebXR:
Webcam display
Orientation
Position
Webcam display is fairly trivial to implement in HTML5 without any libraries.
Orientation is already handled nicely by A-FRAME's "magic window" functionality, including on iOS.
Position was tricky and I wasn't able to solve it. I attempted to use the FULLTILT library's accelerometer functions, and even using the readings with gravity filtered out I wasn't able to get a high enough level of accuracy. (It happened that this particular project did not need it)
I'd like to know how to create a target for architectural large scale AR on a real site.In other words, I need that Google superimposed my 3d model on a specific place.
I have tried Google tango Area Learning tutorials (https://developers.google.com/tango/apis/unity/unity-codelab-area-learning), but after showing the message WALK AROUND TO RELOCALIZE the tablet does nothing, although I walk around to detect the real space, then after few minutes the message Unity project has stopped appears on the Google Tango tablet screen.
Could ADF file used instead of relocalizing the environment?
I've detected some interior scenes by Tango explorer and saved them,but I'm not able to use them for environment recognition purpose
I work on Unity and Google Tango tablet.
Thank you in advance for your response.
For anyone else facing this problem - the likely cause is not having a recent ADF file already on the device.
You need to first create a Area Description file (ADF) by scanning, and then you can separately Localise to that ADF - so you cannot "use an ADF instead of relocalising."
The tutorial you link above needs you to have separately created an ADF for your location - it simply chooses the most recent one you have.
You can use the Area Learning example to create your ADFs, and try localising to them. It also shows superimposing 3D models.
Also, look at the augmented reality one to see how to have objects load already in a specific place.
I'm developing this project where I'm trying to create a distributed version of Tensorflow (the actual open source version is single node) and where the cluster is entirely composed by mobile devices (e.g. smartphones).
In your opinion, what is a possible application or use case where this could be useful? Can you give me some example please?
I know that this is not a "standard" Stack Overflow question, but I didn't know where to post it (if you know a better place where to post it, please let me know it). Thanks so much for your help!
http://www.google.com.hk/search?q=teonsoflow+android
TensorFlow can be used for image identification and there is an example using the camera for Android.
There could be many distributed uses for this. Face recognition, 3D space construction from 2D images.
TensorFlow can be used for a chat bot. I am working towards using it for a personal assistant. The Ai on one phone could communicate with the Ai on other phones.
It could use vision and GPS to 'reserve' a lane for you on the road. Intelligent crowd planned roads and intersections would be safer.
I am also interested in using it for distributed mobile. Please contact me with my user name at gmail or Skype.
https://boinc.berkeley.edu
I think all my answers could run on individual phones with communication between them. If you want them to act like a cluster as #Yaroslav pointed out there is Seti#home and other projects running in the BOINC client.
TensorFlow could be combined with a game engine. You could have a proceduraly generated Ai learning augumented reality game generating the story as multiple players interact with it. I have seen research papers for each of these components.
I have been working Augmented Reality for quite a few months. I have used third party tools like Unity/Vuforia to create augmented reality applications for android.
I would like to create my own framework in which I will create my own AR apps. Can someone guide me to right tutorials/links to achieve my target. On a higher level, my plan is to create an application which can recognize multiple markers and match it with cloud stored models.
That seems like a massive undertaking: model recognition is not an easy task. I recommend looking at OpenCV (which has some standard algorithms you can use as a starting point) and then looking at a good computer vision book (e.g., Richard Szeliski's book or Hartley and Zisserman).
But you are going to run into a host of practical problems. Consider that systems like Vuforia provide camera calibration data for most Android devices, and it's hard to do computer vision without it. Then, of course, there's efficiently managing the whole pipeline which (again) companies like Qualcomm and Metaio invest huge amounts of $$ in.
I'm working on a project that does framemarker tracking and I've started exporting bits of it out to a project I'm calling OpenAR. Right now I'm in the process of pulling out unpublishable pieces and making Vuforia and the OpenCV versions of marker tracking interchangeable. You're certainly welcome to check out the work as it progresses. You can see videos of some of the early work on my YouTube channel.
The hard work is improving performance to be as good as Vuforia.
I am using an XBox Kinect with the Kinect for Windows SDK. I want to make an application that will augment a 3D mask (a 3D model of a mask made in 3DS Max) onto the face of anyone using the application. The application will be used in an exhibit locally. I have not tried much because I don't know where to start. So what I want to know is, is it currently possible to augment a 3DS Max model onto a live video stream using the facial recognition and skeletal tracking features in the newest Kinect for Windows SDK, and if so, how/where should I start trying to do/implement this? Any point in the right direction would be great. Thank you! PS And yes, I have read the UI guidelines and the facial documentation. My problem is one of not knowing where to start programming, not one of not understanding the fundamental concepts. Thanks!
If you are serious about getting into developing for the Kinect I would recommend getting this book:
http://www.amazon.com/Programming-Kinect-Windows-Software-Development/dp/0735666814
This goes through developing with the Kinect for Windows SDK from the ground up. There is a face tracking and an augmented reality example so I'm pretty sure you will be able to achieve your goal quite easily.
All the code from the book is here:
http://kinecttoolbox.codeplex.com/
Alternatively, there is an example here which pretty much is what you want to achieve:
http://www.codeproject.com/Articles/213034/Kinect-Getting-Started-Become-The-Incredible-Hulk
It is developed using the Beta version of the SDK, but the same priciples apply.
You can also check out the quick start videos here:
http://channel9.msdn.com/Series/KinectQuickstart
In summary, based on my own experience, I would spend some time going through the beginner examples either in the vides or the book (I found the book very good) just to get familiar with how to setup a simple Kinect project and how the different parts of the SDK work.
When you have developed some throwaway apps with the Kinect, I would then try tackling your project (although, the Incredible Hulk project above should get you most the way there!)
Best of luck with your project