added some more information in the readme

Author: MichaelRuhnke

README.md

@@ -1,4 +1,86 @@
 ssa
 ===
 
-Sparse Surface Adjustment
+Sparse Surface Adjustment:
+SSA is an open-source C++ tool for post optimization of 2D or 3D SLAM solutions. 
+SSA iteratively refines robot poses and surface points in one global graph optimization 
+system and produces highly accurate 3D point clouds. 
+3D sensor observations are not treated as rigid body and might be refined during the 
+optimization procedure. This leads to substantially less accumulated noise in the 
+resulting model. SSA builds upon g2o as optimization back-end.
+
+More detailed information can be found in the Sparse Surface Adjustment publication:
+http://ais.informatik.uni-freiburg.de/publications/papers/ruhnke12icra.pdf
+
+Authors:
+Michael Ruhnke; Rainer Kuemmerle; Giorgio Grisetti; Wolfram Burgard;
+
+License:
+SSA is free software: you can redistribute it and/or modify
+it under the terms of the GNU Lesser General Public License as published
+by the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+ 
+SSA is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+GNU Lesser General Public License for more details.
+ 
+You should have received a copy of the GNU Lesser General Public License
+along with this program.  If not, see <http://www.gnu.org/licenses/>.
+
+===
+
+How to get the code?
+git clone https://github.com/MichaelRuhnke/ssa.git
+
+Dependencies:
+- libqglviewer (for opengl visualization)
+- Suitesparse  (math library for sparse matrices) 
+  SSA offers an option to download and compile openBLAS and suitesparse.
+  usually this gives a speedup up between 2 and 10 for the optimization.
+- Pointcloud Library (for import / export of data)
+- FLANN (also a dependency of pcl)
+- Eigen3 (also a dependency of pcl)
+- g2o (will be checked out from the developer git repository during the build process)
+
+  On Ubuntu machines you might install the dependencies with:
+  sudo apt-get install libqglviewer-qt4-dev 
+  sudo apt-get install libsuitesparse-dev
+  sudo add-apt-repository ppa:v-launchpad-jochen-sprickerhof-de/pcl
+  sudo apt-get update
+  sudo apt-get install libpcl-all
+
+Compiling ssa:
+mkdir build
+cd build
+cmake-gui ../
+#if qmake-NOTFOUND appears change it into qmake-qt4
+make
+
+Run an example:
+There is an example data set of a dark mug in example/alufr_black_mug/
+
+First step to convert a dataset into ssa format is: 
+pcd_to_ssa
+
+$ pcd_to_ssa: converts a set of PointXYZRGBA pcd files into a ssa 3d graph file
+$ usage pcd_to_ssa [options] <ssa3d_file> options:
+$ -p [string]	prefix of the pcd file list.
+$ -r [double]	resolution of the resulting model (default resolution 0.01m)
+$ -n [int] 	count of point clouds
+$ example:
+$ pcd_to_ssa -p alufr_black_mug_raw -n 60 -r 0.001 alufr_black_mug_raw.ssa3d
+
+this will load alufr_black_mug_raw00000.pcd to alufr_black_mug_raw00059.pcd
+and subsample to a resolution of 1mm.
+
+The pcd files should have proper sensor poses and orientations (from your registration
+algorithm). The points itself should be in sensor frame and not transformed!!!
+
+> ssa_viewer_3d -ini ssa.ini alufr_black_mug_raw.ssa3d
+
+runs the optimizer gui. An example ssa.ini file is located in the ssa root dir.
+
+If you apply parameters that result in an unconnected graph, the optimizer will crash.
+Right now I do not check for the connectivity, but I will provide that feature pretty soon.