Rewrite of the tutorial.

1. Quicker starting point.
2. Better discussion of derivatives.
3. Better hyperlinking to code and class documentation.
4. New robust estimation example.
5. Better naming of example code.
6. Removed dependency on gflags in all the core examples covered
   in the tutorial.

Change-Id: Ibf3c7fe946fa2b4d22f8916a9366df267d34ca26

examples/simple_bundle_adjuster.cc

@@ -160,6 +160,14 @@ struct SnavelyReprojectionError {
     return true;
   }
 
+  // Factory to hide the construction of the CostFunction object from
+  // the client code.
+  static ceres::CostFunction* Create(const double observed_x,
+                                     const double observed_y) {
+    return (new ceres::AutoDiffCostFunction<SnavelyReprojectionError, 2, 9, 3>(
+                new SnavelyReprojectionError(observed_x, observed_y)));
+  }
+
   double observed_x;
   double observed_y;
 };
@@ -177,6 +185,8 @@ int main(int argc, char** argv) {
     return 1;
   }
 
+  const double* observations = bal_problem.observations();
+
   // Create residuals for each observation in the bundle adjustment problem. The
   // parameters for cameras and points are added automatically.
   ceres::Problem problem;
@@ -184,12 +194,10 @@ int main(int argc, char** argv) {
     // Each Residual block takes a point and a camera as input and outputs a 2
     // dimensional residual. Internally, the cost function stores the observed
     // image location and compares the reprojection against the observation.
-    ceres::CostFunction* cost_function =
-        new ceres::AutoDiffCostFunction<SnavelyReprojectionError, 2, 9, 3>(
-            new SnavelyReprojectionError(
-                bal_problem.observations()[2 * i + 0],
-                bal_problem.observations()[2 * i + 1]));
 
+    ceres::CostFunction* cost_function =
+        SnavelyReprojectionError::Create(observations[2 * i + 0],
+                                         observations[2 * i + 1]);
     problem.AddResidualBlock(cost_function,
                              NULL /* squared loss */,
                              bal_problem.mutable_camera_for_observation(i),