clang and gcc complained about this, while VS2015 accepted it. It turns out this is the much better way to do it!

* Now using the transparent glm bindings
* Replaced nonlinear camera estimate with the linear algorithm
* Updated RenderingParameters bindings

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.

* 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

Added a BUILD_UTILS CMake option, defaulting to OFF.