Careful about GLM's notation! A 3x4 matrix is a mat4x3!

Based on pybind11/eigen.h, fairly simple.
A bit of care had to be taken for matrices because glm stores the data in col-major layout in memory.
It makes an unnecessary copy of the data in glm::make_mat*, but these types are small anyway.

This fixes the constexpr bug with VS2015U3

* Added estimate_orthographic_camera inside the submodule "fitting", and also added bindings for RenderingParameters
* Updated documentation a bit

This allows buffer objects (e.g. arrays) to be converted to eos.Mat (and eos.VecXf), which will then subsequently be converted to cv::Mat/cv::VecXf in C++.
Added mostly support for 1-channel CV_32F and CV_64F types.
The explicit conversion that's required in Python is a bit cumbersome, but I can live with it for now.

Put things from the morphablemodel namespace in a python submodule.

This adds a Python buffer view to cv::Vec4f, and the type is exposed as eos.Vec4f.
That means that the type is convertible to a NumPy array using `np.array(vec4f_instance)`.

Also renamed the app that creates the bindings to generate-python-bindings.cpp.

- Added a flag GENERATE_PYTHON_BINDINGS to CMake which enables the use of pybind11
- `create-python-bindings` generates bindings for PcaModel
- pybind11 is added as a submodule; needs to be cloned with `git submodule update --init`
- Increased cmake_minimum_required to 2.8.12 for pybind11

Changed all affected functions and classes accordingly: Mainly the renderer, affine-renderer, and affine texture extraction.

This results in a ~35% speed-up of rendering meshes.

It requires some not-so-beautiful conversions in render_affine and the current texture extraction, but they will be superseded by the new renderer soon anyway.

Fits camera, shape, blendshapes and colour coefficients with a cost function containing a landmark constraint, priors, and minimising the error between the input image's RGB values and the model estimate (rendered at each vertex).

Note: The image cost function cannot be used with the model on GitHub, as it doesn't include the colour PCA.

Not sure what's the best place to put them, let's put them here for now.

* Fits the pose (camera) to landmarks using the newly added Ceres cost functions
* Added find_package(Ceres) to CMakeLists.txt

He updated it quite a few months ago and sent the file to me - now finally committed.

* The changes were necessary to fix issues with Ceres's Jet type in glm vector and matrix types
* Added glm-git-modified-readme.txt to explain these changes

* Added const and non-const overloads. The non-const is needed because of the RNG in PcaModel.
* Renamed a few variables for consistency

This is needed by the json-to-cereal-binary app to read the JSON generated from the Matlab BFM converter script.

Otherwise, it looked like JSONlab will not write the output file, probably because it's >1GB. See GitHub issue #29.

Renamed fit_shape_model to fit_shape, since it's fitting the shape in general (including blendshapes), and not only the PCA model.