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Hi Peter,<br>
<br>
I am working on project of face detection/recognition for Simon
since last few days. I have implement some part of it. I would like
to demonstrate that to you.<br>
<br>
As the major obstacle for command and control speech recognition
systems is to differentiate commands from background noise, We will
activate the recognition only when the user is actively looking at
the screen / robot and we will also detect whether the user is
speaking or not by recognizing mouth movements. <b>So now we
are not only detecting face, We are also detecting whether he is
speaking or not.</b> <b>We can also activate/deactivate the microphone on eye blinks. </b>For example, If the user blinks eyes continuously for two times, we can activate/deactivate the microphones. We will also allow user defined gestures to control it. This matches a natural "human to human"
communication.<br>
<p>I have uploaded the working video on Youtube.<br>
</p>
<p><a href="http://www.youtube.com/watch?v=wGI4lYXxlWg" target="_blank">http://www.youtube.com/watch?v=wGI4lYXxlWg</a></p>
<p><br>
I am able to detect:<br>
</p>
1. Face.<br>
2 .Eyes <br>
3. Mouth<br>
4. Whether the user is speaking or not.<br>
<br>
I am able to track the cropped image of the face accurately which
can be seen in the Cropped Window of the video. I am also able to
track the size of the face and also for tilted face. Also, The
processing of images hardly takes much CPU usages. We are checking
for users every 2 seconds which makes it fast and efficient.<br>
<br>
This is just the demonstration of how things will be done. We will
be using libKface library for efficient face detection. It was
developed by my friend Aditya Bhatt from my college in Gsoc 2010. I
will extend that for detecting mouth and other parts. It is not just
about 3 months of GSoC, We will keep linking Computer vision to
Simon even after that.<br><font color="#888888"> <br><br>
<pre cols="72">--
Regards,
Yash Shah</pre>
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