is there any source (paper/report/code/etc) explaining the exact Visual-Inertial-Odometry (VIO) implementation that is being used in ARCore for tracking the user's motion? I would like to see how it compares to other State-of-the-Art approaches in this research field.
In https://github.com/google-ar/arcore-android-sdk/archive/v1.22.0.zip the file arcore_c_api.h has some links, but when I see any ::'s its rough reading...
Related
I understand so far that AKSampler was recently rewritten and this GitHub project seems to be the defacto guide on the new AKSampler. What I can gather is a move toward SFZ format. I am new to the sampling world but in my application I only need a handful of samples recorded from my piano in order for it to work. As I have looked around with existing SFZ formats and samples, I do not need all of the complexity and features that SFZ provides.
I am currently using AKSampler with a single piano sample which works perfectly, however it gets a bit weird once I play anything too far from the original source, so I just want to fill in the gaps with a few other samples (I only need to play around an octave and a half with my current app).
I do see according to the Docs a couple methods buildSimpleKeyMap() and buildKeyMap() however there is no implementation currently.
Do I have any additional options? I know that EXS format has been deprecated, as well as SoundFont. Is the only way to map multiple samples to AKSampler currently using SFZ?
Thanks for all your help <3
Edit: This readme on the AKSampler GitHub page provides the breakdown for samples. I still only see SFZ being considered. If anyone else is lost with my question or needs a reference, this seems to be the best resource. If the current AKSampler only offers SFZ as the primary way to map multiple samples, so be it, however it does look very challenging, I'm really hoping there is some simple middle ground between only using a single sample for the AKSampler vs. a full bore SFZ file.
Edit 2: Getting a solution to this, will update as soon as possible, thanks for your patience!
I have provided a simple explainer and sample file in the AudioKit docs. Hope this helps new users of AudioKit!
I have tried to implement the ellipse fitting algorithm descibed in the following paper: “ElliFit: An unconstrained, non-iterative, least squares
based geometric ellipse fitting method”, by Prasad, Leung, Quek. A free version can be downloaded online from http://azadproject.ir/wp-content/uploads/2014/07/2013-ElliFit-A-non-constrainednon-iterative-least-squares-based-geometric-Ellipse-Fitting-method.pdf
The authors did not provide any publicly available implementation.
I have implemented the algorithm in Mathematica, I believe I have implemented it correctly, yet it fails to correctly find the fit parameters. The PDF of the experiment can be downloaded here: http://zvrba.net/downloads/ElliFit-fail-example.pdf
Did somebody else try to implement this particular algorithm and, if yes, what is the key to get it working? Is there a "bug" in the paper? Can somebody take another look at my implementation and see whether there's a bug there?
I know it's been almost a year since this question, but it seems that the authors have now provided public source code for ElliFit, both a MATLAB version and an OpenCV version.
Both are available on the the author's homepage. In case the homepage goes offline for some reason, both source codes are shared on Google and are available here (MATLAB) and here (OpenCV).
At the time of writing, I have not personally tested their code, but am planning to use them for a project. I will post any updates here in the next few days.
EDIT:
I got around to test the code sooner than I expected. I gave the OpenCV code a try. It works pretty well, as demonstrated by the image below (ignore the "almost-closed-ellipses". It's an artifact caused by something else in my code).
As you can see, it works pretty well, most of the times. There are some failure cases too (the small ellipse on the spray bottle next to the cup).
This is a known area and OpenCV might well be involved, but still to start from the scratch.
How has something like Evernote's scannable app been developed. I mean, how does it automatically recognize a document using a camera and then extract it.
What are the UIKit frameworks involved here and what are the libraries that may have been used. Or any nice articles or blogs. How does one go about understanding this.
This tutorial is what you might be needing. Although, this tutorial is in Python but all these function are available in iOS bindings.
Here, are results you will get.
Once, you have the ROI i.e. the page, you should run OCR to detect the characters. For this you can use Tesseract and this tutorial might be helpful.
For anyone coming here now, there are better solutions now. CIDetector does precisely this. And to have it working on a live camera feed, you'd have to use it on live CIImages being generated by AVFoundation (rendered using Metal or OpenGL).
I'm searching for a face tracking system to use in an augmented reality project. I'm trying to find an open source and multi-platform application for it. The goal is to return the direction where the face is looking to interact with the virtual environment, (something like this video).
I've downloaded the sources of the above Johnny Lee's application and tried to use Free Track too, making my own headset (some kind of monster, hehe). But it's not good to be limited to infrared points in your head.
These days I've download FaceTrackNoIR, but when I launch the program I get "No DLL was found in the Waterfall procedure." that I'm actually trying to solve.
Anyone knows a good application, library, code, lecture, anything that could help me to find a good path for this?
Thank you all!
I'll try to post results someday :-)
I would take a look at OpenCV. It is a general purpose machine-learning and computer vision C++ library. One of the examples in the download is a real-time face tracker that connects to a video camera connected to your computer and draws squares around any faces in the camera view.
Samples are often distributed with SDKs to provide real world details on how to use the product. Some samples are complete applications, some are bare bones console applications and some are just plain text tutorials with code snippets.
How do you like SDK samples to be presented?
All of the examples you provided can be helpful to different people and/or at different times.
Personally, I like to see a lot of deep textual treatment of the relevant subjects and lots of small, focused code snippets demonstrating salient aspects of the SDK.
A 'toy' application used to demonstrate both the breadth and the depth of the SDK can be very useful as well.