Add example info to readme.
Changes to make libwcl compile on Ubuntu 12.10.

 o Now need to explicitly include <unistd.h> in order
   to use functions like sleep, usleep, etc.
Stop throwing exceptions if getting an image causes an error.

 o This seems to happen pretty often, and throwing an exception
   just seems cruel. Instead we will just ignore that frame.

 o For the record, this is the error I'm talking about:

ERROR: There is an image consistency issue with this image.
SUpport info: Error Trace:
Source: CameraInternal.cpp(123) Built: Oct  4 2012 04:38:07 - There is
an image consistency issue with this image.
+-> From: Iso.cpp(759) Built: Oct  4 2012 04:38:19 - There is an image
consistency issue with this image.
Lets make this API a little easier to understand.
Fixes to OBJ parser to load files exported from SolidWorks

 o Support negative integers
 o Allow doubles or ints in most places, since really we just want
   numbers.
Initialise contexts to null.

 o Otherwise newer AVCodecs don't work
Config flags to get examples building on OSX.
Constructor and method for bulk adding wcl::Vectors to bounding box.
Intial K-Means clustering class.
Get OpenGL based examples to build on OSX.
KMeans clustering class works!

 o Give it a set of points and the number of clusters you want,
   and call compute()

 o Or, call step repeatedly to see the clustering unfold

 o See the example!
Add a destructor to clean up after KMeans.
Include headers to get KMeans to build on Linux.
Angle now returns 0 if two vectors are equal.

 o Previously returned NaN, which is not nearly as useful.
KMeans clusters now have their own bounding box.
KMeans example shows cluster bounding boxes.
Transmission Factor (opacity) can be an RGB value in OBJ.

 o Was originally coded as a single float.
 o Mini OBJ file is now loadable again.
Make KMeans more useful by using an interface for positions.

 o Previously, KMeans operated on wcl::Vectors. This is fine for
   testing, but in real life we probably want it working on some class.

 o Create a new pure-virtual class, Position, which has methods for
   getting position (x,y,z). Use this throughout KMeans.

 o Code that uses KMeans need to use a data structure that implements
   these pure virtual methods to provide position information.

 o See kmeans example for a SimplePosition class that uses a
   wcl::Vector internally.
Template-ise KMeans.

 o Was getting sick of all the maps I had to create to convert from
   KMeans' data structures to my graph structures.

 o Now you specify the PositionType and ClusterType you want to use.

 o You can extend wcl::Cluster or use it directly if you don't want any
   extra data associated with clusters.

 o Your PositionType has to have x() y() and z() functions to get the
   position.
Implement Forgy initialisation step in KMeans.

 o Hopefully will reduce the occurance of empty clusters.