State-of-the-art deformable modelling techniques implemented on top of the Menpo project. Currently, the techniques that have been implemented include:

• Active Appearance Model
  • Holistic, Patch-based, Masked, Linear, Linear Masked
  • Lucas-Kanade Optimisation (Alternating, Modified Alternating, Project Out, Simultaneous, Wiberg)
  • Casaded-Regression Optimisation
• Lucas-Kanade Image Alignment
  • Forward Additive, Forward Compositional, Inverse Additive, Inverse Compositional
• Active Template Model
  • Holistic, Patch-based, Masked, Linear, Linear Masked
  • Lucas-Kanade Optimisation (Inverse Compositional, Forward Compositional)
• Active Pictorial Structures
  • Weighted Gauss-Newton Optimisation with fixed Jacobian and Hessian
• Constrained Local Model
  • Active Shape Models
  • Regularized Landmark Mean-Shift
• Ensemble of Regression Trees (ERT) [provided by DLib]
• Supervised Descent Method
  • Non Parametric
  • Parametric Shape
  • Parametric Appearance
  • Fully Parametric

Here in the Menpo team, we are firm believers in making installation as simple as possible. Unfortunately, we are a complex project that relies on satisfying a number of complex 3rd party library dependencies. The default Python packing environment does not make this an easy task. Therefore, we evangelise the use of the conda ecosystem, provided by Anaconda. In order to make things as simple as possible, we suggest that you use conda too! To try and persuade you, go to the Menpo website to find installation instructions for all major platforms.