A method for face alignment comprising: identifying a mesh shape adjusted to an image of a face , the mesh shape having a set of elements, each element having a set of vertices; wherein the mesh shape is a mean shape averaged from a plurality of randomized shapes, the plurality of random shapes corresponding to a labeled image with known facial anchor points; for each decision tree in a cascade level having a plurality of decision trees, traversing the decision tree until a leaf node is reached from a plurality of leaf nodes: identifying one or more positions associated with a traversal decision ; each position described in coordinates with respect to an element of the mesh shape; for each of the one or more identified positions, identifying a pixel on the image based on the coordinates and the location of the set of vertices of the element on the image ; determining a subsequent node for the traversal decision based on a pixel value of the pixel identified for the one or more identified positions; for each leaf node reached of the plurality of decision trees , identifying an adjustment vector for the mesh shape relative to the image of the face ; combining the identified adjustment vector for the leaf nodes to determine a combined adjustment vector for the cascade level ; and modifying the adjustment of the mesh shape to the face in the image based on the combined adjustment vector . identifying a mesh shape adjusted to an image of a face , the mesh shape having a set of elements, each element having a set of vertices; wherein the mesh shape is a mean shape averaged from a plurality of randomized shapes, the plurality of random shapes corresponding to a labeled image with known facial anchor points; for each decision tree in a cascade level having a plurality of decision trees, traversing the decision tree until a leaf node is reached from a plurality of leaf nodes: identifying one or more positions associated with a traversal decision ; each position described in coordinates with respect to an element of the mesh shape; for each of the one or more identified positions, identifying a pixel on the image based on the coordinates and the location of the set of vertices of the element on the image ; determining a subsequent node for the traversal decision based on a pixel value of the pixel identified for the one or more identified positions; for each leaf node reached of the plurality of decision trees , identifying an adjustment vector for the mesh shape relative to the image of the face ; combining the identified adjustment vector for the leaf nodes to determine a combined adjustment vector for the cascade level ; and modifying the adjustment of the mesh shape to the face in the image based on the combined adjustment vector . identifying one or more positions associated with a traversal decision ; each position described in coordinates with respect to an element of the mesh shape; for each of the one or more identified positions, identifying a pixel on the image based on the coordinates and the location of the set of vertices of the element on the image ; determining a subsequent node for the traversal decision based on a pixel value of the pixel identified for the one or more identified positions; for each leaf node reached of the plurality of decision trees , identifying an adjustment vector for the mesh shape relative to the image of the face ; combining the identified adjustment vector for the leaf nodes to determine a combined adjustment vector for the cascade level ; and modifying the adjustment of the mesh shape to the face in the image based on the combined adjustment vector . <EOS>