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Basically there are several ways of going faster

1. Aplly GPU detection if you have large images (the time for sending data to GPU needs to be sufficiently small compared to the CPU processing time, which is not the case for single small images)
2. Reduce the size of your input image if the faces are much larger than 24x24 pixels.
3. Apply LBP features, which are no floating point operations like Haar wavelets.

Another question: do you perform the eye detection only on possible face regions? This will also reduce calculation time alot. Furthermore, the more positive detections there are in an image, the longer the processing will actually take, because those regions will go deeper in the cascade.