Docs: Add performance to faq.

docs/faq.md

@@ -9,3 +9,28 @@
   [here](http://dlib.net/face_landmark_detection_ex.cpp.html).
   Use the `-DUSE_AVX_INSTRUCTIONS=ON` in the first `cmake` command.
   If your architecture does not support AVX, try SSE4 or SSE2.
+
+## How much time does OpenFace take to process an image?
+
+The execution time depends on the size of the input images.
+The following results are from processing these example images
+of John Lennon and Steve Carell, which are respectively sized
+1050x1400px and 891x601px on an 8 core 3.70 GHz CPU.
+The network processing time is significantly less on a GPU.
+
+<img src='https://raw.githubusercontent.com/cmusatyalab/openface/master/images/examples/lennon-1.jpg' height='200px' />
+<img src='https://raw.githubusercontent.com/cmusatyalab/openface/master/images/examples/carell.jpg' height='200px' />
+
+The improvement makes the alignment time negligible
+and reduces the neural network execution time.
+OpenFace's execution times are reduced from almost 3 seconds
+to about 1.5 seconds for the larger image of John Lennon,
+and from almost 1.5 seconds to a little over 0.75 seconds
+for the image of Steve Carell.
+These times are obtained from averaging 100 trials with
+our [util/profile-pipeline.py](https://github.com/cmusatyalab/openface/blob/master/util/profile-pipeline.py)
+script.
+The standard deviations are low,
+see [the raw data](/data/2016-01-19/execution-times.txt).
+
+<img src='https://raw.githubusercontent.com/cmusatyalab/openface/master/images/performance.png' />