diff --git a/svo_analysis/README.md b/svo_analysis/README.md
index 3fe3ea6b..84fd11eb 100644
--- a/svo_analysis/README.md
+++ b/svo_analysis/README.md
@@ -14,39 +14,14 @@ Source your new `.bashrc` script, go to the new dataset folder and download the
 
     source `~/.bashrc`
     cd ${SVO_DATASET_DIR}
-    wget http://rpg.ifi.uzh.ch/datasets/flying_room_1_rig_1.tar.gz -O - | tar -xz
-
-TODO: replace this dataset with new ones.
+    wget http://rpg.ifi.uzh.ch/datasets/sin2_tex2_h1_v8_d.tar.gz -O - | tar -xz
 
 #### Run Benchmark
 
 In the _CMakeLists.txt_ of SVO you need to set the `TRACE` flag to `TRUE` and recompile SVO.
 Afterwards run
 
-    rosrun svo_analysis benchmark.py flying_room_1_fast
+    rosrun svo_analysis benchmark.py sin2_tex2_h1_v8_d
 
 The script will create a new folder in `svo_analysis/results/`, run svo on the dataset and save the tracefile in this folder and at the end it will run some scripts to generate plots from the tracefile.
-
-
-#### Dataset file
-
-A dataset with motion-capture-system ground-truth should contain the following files
-
-* _images.txt_
-  
-     # timestamp img/imagename
-     1329330952.725747585296631 img/00000.png
-     1329330952.765715122222900 img/00001.png
-     1329330952.805604219436646 img/00002.png
-     ...
-
-* _groundtruth.txt_: groundtruth poses as acquired from a motion capture system
-
-     # timestamp tx ty tz qx qy qz qw
-     
-* _groundtruth_matched.txt_: the groundtruth pose associated to the images in images.txt. This file can be generated by the command:
-
-    cd my_dataset
-    rosrun svo_analysis associate.py images.txt groundtruth.txt
-