made cameras virtual and simplified pose factor (with Frank)

gtsam/slam/SmartFactorBase.h

@@ -142,7 +142,7 @@ public:
   }
 
   /**
-   * Add a bunch of measurements and uses the same noise model for all of them
+   * Add a bunch of measurements and use the same noise model for all of them
    */
   void add(std::vector<Z>& measurements, std::vector<Key>& cameraKeys,
       const SharedNoiseModel& noise) {
@@ -177,7 +177,7 @@ public:
   }
 
   /// Collect all cameras: important that in key order
-  Cameras cameras(const Values& values) const {
+  virtual Cameras cameras(const Values& values) const {
     Cameras cameras;
     BOOST_FOREACH(const Key& k, this->keys_)
       cameras.push_back(values.at<CAMERA>(k));

gtsam/slam/SmartProjectionPoseFactor.h

@@ -103,24 +103,6 @@ public:
     return e && Base::equals(p, tol);
   }
 
-  /**
-   * Linearize to Gaussian Factor
-   * @param values Values structure which must contain camera poses for this factor
-   * @return a Gaussian factor
-   */
-  boost::shared_ptr<GaussianFactor> linearizeDamped(const Values& values,
-      const double lambda = 0.0) const {
-    // depending on flag set on construction we may linearize to different linear factors
-    typename Base::Cameras cameras = this->cameras(values);
-    return Base::linearizeDamped(cameras, lambda);
-  }
-
-  /// linearize
-  virtual boost::shared_ptr<GaussianFactor> linearize(
-      const Values& values) const {
-    return linearizeDamped(values);
-  }
-
   /**
    * error calculates the error of the factor.
    */
@@ -156,15 +138,6 @@ public:
     return cameras;
   }
 
-  /**
-   * Triangulate and compute derivative of error with respect to point
-   * @return whether triangulation worked
-   */
-  bool triangulateAndComputeE(Matrix& E, const Values& values) const {
-    typename Base::Cameras cameras = this->cameras(values);
-    return Base::triangulateAndComputeE(E, cameras);
-  }
-
 private:
 
   /// Serialization function