I have scoured the net for resources on BPM detection for iOS, tried to implement various techniques and link to various libraries etc. but I just have issues either with build errors or with bpm detection not working.
What are the viable options for basic BPM detection on iOS? It doesn't have to be highly accurate with onset positions, but rather just detect the BPM for a series of audio buffers.
I tried VAMP but cannot get it to run on iOS, Ive tried various c++ options but none of them work.
Are there any MIT licensed BPM detection algorithms that integrate easily with iOS, or any commercial options that don't cost loads because its for a full audio library. I would like to detect BPM from a file not through the microphone.
I would just like a BPM detector class as I don't have the time to learn and implement one myself at this point in time.
Any help will be greatly appreciated.
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I want to implement Structur from Motion (SfM) / Simultaneous Localization and mapping algorithms using my webcam. I am very new on this topic so I need advices from experts in the internet. I could now able to build OpenCV opencv sfm tutorial for this purpose and I looked OpenSFM but it seems like just a GUI. What other open libraries/programs that I can use for this task? any suggestions/advices/tutorials are appreciated.
I'm a Software Engineering student in my last year in a 4-year bachelor degree program, I'm required to work on a graduation project of my own choice.
we are trying to find a way to notify the user of any thing the gets on his/her way while walking, this will be implemented as an android application so we have the ability to use the camera, we thought of Image processing and computer vision but neither me or any of my group members have any Image processing background, we searched a little bit and we found out about OpenCv.
So my question is do I need any special background to deal with OpenCv? and is it a good choice for the objective of my project to use computer vision, if not what alternatives do u advise me to use?
I appreciate your help.. thanks in advance!
At the first glance I would use 2 standard cameras to find depth image - stereo vision (similar to MS Kinect depth sensor)
from that it would be easy to fix a threshold to some distance.
Those algorithms are very CPU hungry so I do not think it will work on Android (although I have zero experience).
I you must use Android, I would look for some depth sensor (to avoid extracting depth data from 2 images)
For prototyping I would use MATLAB (or Octave), then I would switch to OpenCV (pointers, mem. allocations, blah...)
I'm trying to create a lightweight diphone speech synthesizer. Everything seems pretty straightforward because my native language has pretty simple pronunciation and text processing rules. The only problem I've stumbled upon is pitch control.
As far as I understand, to control the pitch of the voice, most speech synthesizers are using LPC (linear predictive coding), which essentially separates the pitch information away from the recorded voice samples, and then during synthesis I can supply my own pitch as needed.
The problem is that I'm not a DSP specialist. I have used a Ooura FFT library to extract AFR information, I know a little bit about using Hann and Hamming windows (have implemented C++ code myself), but mostly I treat DSP algorithms as black boxes.
I hoped to find some open-source library which is just bare LPC code with usage examples, but I couldn't find anything. Most of the available code (like Festival engine) is tightly integrated in to the synth and it would be pretty hard task to separate it and learn how to use it.
Is there any C/C++/C#/Java open source DSP library with a "black box" style LPC algorithm and usage examples, so I can just throw a PCM sample data at it and get the LPC coded output, and then throw the coded data and synthesize the decoded speech data?
it's not exactly what you're looking for, but maybe you get some ideas from this quite sophisticated toolbox: Praat
I'm new to video processing and I'm wondering what libraries I can use to do things like detecting letters, drawing boxes around them and so on. If you can name me a couple of good ones, I'd appreciate it very much!
OpenCV: (Open Source Computer Vision) is a cross-platform library of programming functions for real time computer vision.
It provides interfaces for both C and C++ programming laguages.
As for detecting the text region and drawing boxes around it, you can take a look at this article, which explains how to do this stuff using OpenCV. For better OCR capabilities I think that tesseract is the best open source tool available right now.
I've worked on a similar project some time ago and used OpenCV to detect the text region and then tesseract to do proper text recognition.
I'd like to programatically do some signal processing on a live sound feed.
Specifically I'd like to be able to isolate certain bands of frequencies and play around with phase shifting.
I've not worked in this area before from a purely software perspective and a quick google search turned up very little useful information.
Does anyone know of any good information resources for this topic area?
Matlab is a good starting point. It has the necessary toolboxes and functions that will allow you to capture audio signals, run different kind of filters over them and write them to wav files. The UI is easy to navigate through and it's simple enough to generate plots and visualize results.
http://www.mathworks.com/products/signal/
If, however, you're looking to develop real-world applications, then Python can come in handy. They have toolkits like SciPy, Numpy, Audiolab that offer the same functions as Matlab does.
http://www.scipy.org
Link
http://scikits.appspot.com/audiolab
In a nutshell, Matlab is good for testing ideas and prototyping, Python is good for testing as well as real-world application development. And Python is free. Matlab might cost you if you're not a student anymore.
http://www.dspguide.com/
This is a super excellent reference on digital signal processing techniques in general. It's not a programming guide, per se, but covers the techniques and the theory clearly and simply, and provides pseudocode and examples so that you can implement in the language of your choice. You'll be hard up to find a more complete reference, and you can download it for free online!