The fact that I recently tried to solve the same problem (face and eye detection) was as follows:
Reduce the processed image to achieve decent performance (I scaled down to 320 pixels)
Face detection in an image using the Core Computer Vision library - https://github.com/liuliu/ccv
Based on the detected information about the face rectangle, detect the eyes using HAAR object detectors (it has a cascade for detecting only eyes - https://github.com/inspirit/jsfeat
For step 2, I also used grayscale and equalize_histogram from the JSFEAT library.
Also, if step 3 fails, you can try to guess the position of the eyes (depending on how high precision you will do).
This workflow gave me satisfactory results and performance. He tested it both on the desktop (~ 500 ms on the iMac) and on mobile devices (~ 3000 ms on the iphone 4 using a webcam image). Unfortunately, I cannot post a link to a working example at the moment, but I will post a link to github as soon as I have something there.
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