Progress 4/16/2012

Clear and Distinct Goal

Output true/false determination that given image is personX
Training data contains 100 faces (56 female, 44 male, 25 facial expressions each), so we aren't afraid of over fitting.

Data Aquisition

 Cheapest, cleanest option seems to be a kinnect.  This is an end of the quarter goal, but knowing what we know now, we have to keep in mind how our current algorithm seems to become more and more file format dependent.

Progress

Implemented pre-processing as described in:
Automatic 3D Facial Feature Extraction Algorithm
- Translation
-Rotation about the Y and X axes.  (Roll & Pitch, no Yaw)
   paper suggests using homogenous coordinates and 4x4 rotaion matrices.  We implemented using simple trigonometric calculations.

Hurdles

• The vrml file format can be very restrictive.  It's not as easy as changing the 3D point cloud.  We will also have to figure out a clever way to change the point cloud relationships in the vrml.
• How to get from kinnect ->  pointcloud (far off goal)
• Why the c++?  Why not implement the algorithm entirely in matlab?