Face alignment with Dlib and OpenCV
This is my first trial at using Jupyter notebook to write a post, hope it makes sense.
I've recently taught a class on generative models: http://hi.cs.stonybrook.edu/teaching/cdt450
In class we've manipulated face images with neural networks.
One important thing I found that helped is to align the images so the facial features overlap.
It helps the nets learn the variance in faces better, rather than waste their "representation power" on the shift between faces.
The following is some code to align face images using the excellent Dlib (python bindings) http://dlib.net. First I'm just using a standard face detector, and then using the facial fatures extractor I'm using that information for a complete alignment of the face.
After the alignment - I'm just having fun with the aligned dataset 🙂
Continue reading "Aligning faces with py opencv-dlib combo"
OpenCV is by far my favorite CV/Image processing library. When I found an OpenCV port to the iPhone, and even someone tried to get it to do face detection, I just had to try it for myself.
In this post I'll try to run through the steps I took in order to get OpenCV running on the iPhone, and then how to get OpenCV's face detection play nice with iPhoneOS's image buffers and video feed (not yet OS 3.0!). Then i'll talk a little about optimization
Update: Apple officially supports camera video pixel buffers in iOS 4.x using AVFoundation, here's sample code from Apple developer.
Update: I do not have the xcodeproj file for this project, please don't ask for it. Please see here for compiling OpenCV for the iPhone SDK 4.3.
Continue reading "Near realtime face detection on the iPhone w/ OpenCV port [w/code,video]"
As my search for the best platform to roll-out my new face detection concept continues, I decided to give ol' Qt framework a go.
I like Qt. It's cross-platform, a clear a nice API, straightforward, and remindes me somewhat of Apple's Cocoa.
My intention is to get some serious face detection going on mobile devices. So that means either the iPhone, which so far did a crummy job performance-wise, or some other mobile device, preferably linux-based.
This led me to the decision to go with Qt. I believe you can get it to work on any linux-ish platform (limo, moblin, android), and since Nokia baught Trolltech - it's gonna work on Nokia phones soon, awesome!
Lets get to the details, shall we?
Continue reading "Qt & OpenCV combined for face detecting QWidgets"