Update README.md

README.md

@@ -5,6 +5,8 @@ Requires CUDA, Boost, Eigen and OpenCV. I've built it to take in raw TUM RGB-D d
 
 The code is a mishmash of my own stuff written from scratch, plus a bunch of random classes/types taken from [PCL](https://github.com/PointCloudLibrary/pcl/tree/master/gpu/kinfu/src/cuda) (on which the code does not depend :D). The slower version of ICP I compare to is the exact same version in PCL. In my benchmarks I have also found it to be faster than the [SLAMBench](http://apt.cs.manchester.ac.uk/projects/PAMELA/tools/SLAMBench/) implementation and hence the [KFusion](https://github.com/GerhardR/kfusion) implementation. I have not tested against [InfiniTAM](https://github.com/victorprad/InfiniTAM).
 
+The particular version of ICP implemented is the one introduced by [KinectFusion](http://homes.cs.washington.edu/~newcombe/papers/newcombe_etal_ismar2011.pdf). This means a three level coarse-to-fine registration pyramid, from 160x120 to 320x240 and finally 640x480 image sizes, with 4, 5 and 10 iterations per level respectively. 
+
 The fast ICP implementation, which is my own, essentially exploits the shlf instruction added to compute capable 3.0 devices that removes the need for warp level synchronisation when exchanging values, see more [here](http://devblogs.nvidia.com/parallelforall/faster-parallel-reductions-kepler/).
 
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