Added new fit-model app that fits using the new iterative fitting

It uses pose, shape, blendshapes and contour fitting.

examples/CMakeLists.txt

@@ -33,10 +33,14 @@ if(MSVC)
 	set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} /bigobj")
 endif()
 
-# Model fitting (affine cam & shape to landmarks) example:
+# Simple model fitting (orthographic camera & shape to landmarks) example:
 add_executable(fit-model-simple fit-model-simple.cpp)
 target_link_libraries(fit-model-simple ${OpenCV_LIBS} ${Boost_LIBRARIES})
 
+# Model fitting example that fits orthographic camera, shape, blendshapes, and contours:
+add_executable(fit-model fit-model.cpp)
+target_link_libraries(fit-model ${OpenCV_LIBS} ${Boost_LIBRARIES})
+
 if(BUILD_CERES_EXAMPLE)
 	# Find Ceres, for the fit-model-ceres app:
 	find_package(Ceres REQUIRED)
@@ -56,5 +60,6 @@ target_link_libraries(generate-obj ${OpenCV_LIBS} ${Boost_LIBRARIES})
 
 # install target:
 install(TARGETS fit-model-simple DESTINATION bin)
+install(TARGETS fit-model DESTINATION bin)
 install(TARGETS generate-obj DESTINATION bin)
 install(DIRECTORY ${CMAKE_SOURCE_DIR}/examples/data DESTINATION bin)

examples/fit-model-simple.cpp

@@ -105,7 +105,7 @@ LandmarkCollection<cv::Vec2f> read_pts_landmarks(std::string filename)
  * model of a 3D Morphable Model from an ibug LFPW image with its landmarks.
  *
  * First, the 68 ibug landmarks are loaded from the .pts file and converted
- * to vertex indices using the LandmarkMapper. Then, an affine camera matrix
+ * to vertex indices using the LandmarkMapper. Then, an orthographic camera
  * is estimated, and then, using this camera matrix, the shape is fitted
  * to the landmarks.
  */
@@ -131,7 +131,7 @@ int main(int argc, char *argv[])
 		po::variables_map vm;
 		po::store(po::command_line_parser(argc, argv).options(desc).run(), vm);
 		if (vm.count("help")) {
-			cout << "Usage: fit-model [options]" << endl;
+			cout << "Usage: fit-model-simple [options]" << endl;
 			cout << desc;
 			return EXIT_SUCCESS;
 		}