Update readme

README.md

+# About this tool
+This tool is meant to as a pipeline to show 2D and 3D reconstructions using An
+Active Appearance Model and a 2D or 3D model to rebuild the face. Face
+reconstruction is a difficult subject but like with everything, if you
+understand the steps, it's actually ok. This small library, can give you a
+feeling what is needed to solve this problem, but also some quick-and-dirty
+tricks are used. Like using dlib to solve landmark detection, instead of
+estimating them using a more traditional way by as done by [[Coots|coots]].
+Instead, dlib uses a sophistaticated approach to estimate 2D landmarks. This
+capability is re-used to find the PCA parameters needed to rebuild a person's
+face.
+
 ## Prerequisites
-Run the following command
-~~~~
-$ make
-$ source bin/activate
-$ make show_reconstruction
-~~~~
+- Docker
 
-Will get the data needed for this tool.
+# Run
+- $ make
+> *Note*: this will build the docker image, retrieves the imm dataset and dlib
+> trained landmark file.
+> $ make server
+- Use https://github.com/icyrizard/py-3d-face-reconstruction-viewer to run a
+viewer which uses the server to make the reconstruction insightful.
 
 # Imm dataset
-
 # IBUG + dlib
 For the IBUG dataset we use dlib to detect landmarks. You will need the train
 file for that. http://dlib.net/files/shape_predictor_68_face_landmarks.dat.bz2
@@ -22,3 +34,4 @@ $ bzip2 -d shape_predictor_68_face_landmarks.dat.bz2
 
 ## References
 1. [imm_dataset](http://www.imm.dtu.dk/~aam/datasets/datasets.html, "Imm dataset")
+2. [coots](https://www.cs.cmu.edu/~efros/courses/AP06/Papers/cootes-eccv-98.pdf, "Coots")