FaceReader, a software marketed by Noldus (www.noldus.com), is the only tool we are aware of with published validation work (den Uyl & van.
#FaceReaderAPI bindings for Python
In order to utilize these bindings, the python environment will need:
-Python 2.7.x 32-bit Environment (required for Python for .NET)
-Python for .NET installed, which entails adding the Python for .NET files 'clr.pyd' and 'Python.Runtime.dll' to the Python directory (e.g. C:Python27). Can be downloaded from: http://sourceforge.net/projects/pythonnet/files/. Home of Python for .NET is http://pythonnet.sourceforge.net/ with some documentation.
-Add the file 'FaceReaderAPI.dll' to the Python 'DLL' folder (e.g. C:Python27DLL)
The file Test.py is being used to test implementation of the FaceReaderBindCPython.py module (I hope to get that name down in size. Feel free to suggest some catchy names.)
I'm making the python file for python integration use in experimental research software such as OpenSesame and PsychoPy, not for use in standalone applications, but if you can think of a good use for this let me know and I'll whip something up.
Citation:Zosky, J. (2015). FaceReaderAPI bindings for Python. Retrieved November 10, 2015, from https://github.com/imnotamember/FaceReader-PythonBindings
We’ve come to an age where our computers have reached a truly advanced stage. Able to run multiple programs, some even running on the background, and their processing chips are becoming more powerful almost every year. There have even been wonderful achievements in robotics, where the machine is becoming more humanlike in appearance and speech.
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However, one of the best advancements for computers is its ability to read human emotions. Yes, you read that right. Computers can read emotional impulses and they’ve been doing so for quite some time now. An emotion recognition program, just like Facial Recognition Software, can tell if you’re happy or sad. We’ll talk about how the process is done below.
Kairos Emotion Analysis API
Face Reader by Noldus
Vokaturi
Face++
Emotion recognition software works in an intricate kind of way. Using Paul Ekman’s Facial Action Coding System and methods like the Bayesian networks, that’s how most of this software type reads human emotions. They are also quite visual too, relying on facial expressions to decipher the feeling behind it. Here are some of the key features that emotion recognition programs have:
- Range of Support
As humans, we recognize emotion automatically, whether we see on a video, a picture, or through the lens of a camera. This software is also capable of doing that. It can recognize emotion through various channels, be it in an image, video, etc., just like we humans do. - Numerous Facial Analytics
This software contains a lot of analytical results of facial expressions and the emotions linked to them. This is one of the ways that this software is able to recognize emotions. It uses those information and once it sees a new expression, it then begins to match the expressions and check if it is the right kind of emotion. - The Learning Never Stops
Computer programs like this tend to always evolve. Its learning process never stops and its emotion recognition abilities get better and better with every face it processes. This makes it more accurate and reliable as the days pass by. - Gender Recognition
Just like how it’s possible to identify someone’s age using a Voice Recognition Software, this kind of program can also recognize if the person is male or female. By using different types of analyzers, it can distinguish if the face that’s being examined is that of a girl or a boy.
OpenSMILE
Emotion AI
Microsoft Cognitive Services
OpenFace
EmoVu Desktop SDK – Most Popular Software
Giving the computer the ability to recognize emotion could prove to be beneficial for us humans. System reports from certain fields would be more accurate and it would be able to provide a glimpse of a person’s emotion. It would also give the computer a better understanding about humans and how our emotional system works.
Like how a Voice Transcription Software converts voice to text, computers would later on be able to translate an emotion. It would then have appropriate responses to it, based on the available information that has been analyzed. Ultimately, it would make the computer more aware of what the user feels.