Face Features Detection System - with OpenCV

Face features detection performed with OpenCV library. System works on a standard webcam and detects a head position, mouth, nose, forehead, eyes regions, eyeballs, lids, brows, lips, mouth corners, teeth, nostrils edges and furrows - in real-time speed. Also can detect more than one face in the same time.

Note: I'm not sending any code of this application. Please don't ask.

Category:

Science & Technology

Tags:

• OpenCV
• Face
• Detection
• Emotion
• Recognition
• Rozpoznawanie
• Emocji
• Wykrywanie
• Twarzy

[heguner]

hi, how could you detect the eyebrows? could you please give a hint?

[GladPL]

@heguner Generally it's based on contrast difference between brows and skin..

[fadillaazeaza]

wow.. i wanna make a program about image processing but still confuse what must i do

[GladPL]

@fadillaazeaza I suggest looking into OpenCV's samples, where you can find some code written in C or Python (e.g. face detection, contour extraction, shape fitting, ...).

It also depends what you want to implement? Object detection, letter recognition, motion detection, ...

[Judegl]

Hello ! I'm trying to make a smile detector using opencv. I want to start with pictures and then real time with video streaming. Can you please recommend me some fast algorithms to use (classifiers etc) and a path i should follow. I'm new in computer vision and i wanted an advice. I "googled" it first but i am asking u because you have practical experience and I think you will be more specific. I would appreciate it. Thanq you a lot ! Sorry if i double posted it.

[GladPL]

@Judegl You need to detect mouth region. You can do it in OpenCV by using cvHaarDetectObjects() which implements Viola-Jones algorithm. For more information check OpenCV samples where you can find face detection demo using still images and camera stream. Then you have to analyze extracted region and e.g. segment lips pixels using color filtering, detect mouth corners positions and make a decision based on collected information.

[jeetendrag10acc2]

@GladPL 0:32

if (emotion_detected==surprise)

{

add_current_www_link_to_banned­_porn_website_database(webbrow­ser1.active_window.current_add­ress);

}

:-)

[LittlePokeDigi]

Hi. I have a Sample of a Face Detection Program .

When it detects a face , it draw a Square box of the face it detects.

This is what I want to do.

When it detects a face , it paste a picture over it.

Do you have any idea how I can do it? Thanks

[GladPL]

@superharryboy Right, you can detect face and then find e.g. mouth, nose, eyes in parallel threads because they don't depend on each other. After that you have to synchronize.

[superharryboy]

@GladPL Up to now I've found a way to overlay images, but needs more work to track recognized/detected areas as rectangles do. I'm using a dual core machine, camera settings checked. Right now i'm have to stick with Haar object detection. So ROIs will be of help. By parallel detection you mean paralell processes? I was wondering if this was possible.

[superharryboy]

@LittlePokeDigi There are many ways to do this. What I do is use Get2D() and Set2D() to accomplish this task. I haven't try other methods yet. This one i'm using may not be the fastest method,but it does the job. If you want more info about how to implement this method, google aishack. There is a post about this. The author has the code in c++, so if you use python you'll have to translate the code as I did.

[GladPL]

@superharryboy Yes, quite important, you can process smaller image region faster than a whole image. I use also parallel detection of multiple face parts, so everything scales very well on 4-6 core machines. You can also take a look on your camera settings - the higher exposure = the slower framerate. Furthermore, standard Haar object detection is not too fast, but quite.