update README

README.md

@@ -6,6 +6,7 @@
 - **All parallerized** : small_gicp provides parallelized implementations of several algorithms in the point cloud registration process (Downsampling, KdTree construction, Normal/covariance estimation). As a parallelism backend, either (or both) of [OpenMP](https://www.openmp.org/) and [Intel TBB](https://github.com/oneapi-src/oneTBB) can be used. 
 - **Minimum dependency** : Only [Eigen](https://eigen.tuxfamily.org/) (and bundled [nanoflann](https://github.com/jlblancoc/nanoflann) and [Sophus](https://github.com/strasdat/Sophus)) are required at a minimum. Optionally, it provides the [PCL](https://pointclouds.org/) registration interface so that it can be used as a drop-in replacement in many systems.
 - **Customizable** : small_gicp is implemented with the trait mechanism that allows feeding any custom point cloud class to the registration algorithm. Furthermore, the template-based implementation allows customizing the regisration process with your original correspondence estimator and registration factors.
+- **Python bindinds** (coming soon) : The isolation from PCL makes the small_gicp's python bindinds more portable and connectable to other libraries seamlessly. 
 
 [![Build](https://github.com/koide3/small_gicp/actions/workflows/build.yml/badge.svg)](https://github.com/koide3/small_gicp/actions/workflows/build.yml)
 
@@ -15,6 +16,8 @@ This library uses some C++20 features. While porting it to older environments sh
 
 ## Installation
 
+### C++
+
 small_gicp is a header-only library. You can just download and drop it in your project directory to use it.
 
 Meanwhile, if you need only basic point cloud registration, you can build and install the helper library as follows.
@@ -28,13 +31,17 @@ cmake .. -DCMAKE_BUILD_TYPE=Release && make -j
 sudo make install
 ```
 
-## Usage
+### Python
+
+Coming soon.
+
+## Usage (C++)
 
 The following examples assume `using namespace small_gicp` is placed somewhere.
 
 ### Using helper library ([01_basic_resigtration.cpp](https://github.com/koide3/small_gicp/blob/master/src/example/01_basic_registration.cpp))
 
-The helper library (`registration_helper.hpp`) enables processing point clouds represented as `std::vector<Eigen::Vector(3|4)(f|d)>` easily.
+The helper library (`registration_helper.hpp`) enables easily processing point clouds represented as `std::vector<Eigen::Vector(3|4)(f|d)>`.
 <details><summary>Expand</summary>
 
 `small_gicp::align` takes two point clouds (`std::vectors` of `Eigen::Vector(3|4)(f|d)`) and returns a registration result (estimated transformation and some information on the optimization result). This is the easiest way to use **small_gicp** but causes an overhead for duplicated preprocessing.
@@ -226,6 +233,10 @@ registration.optimizer.init_lambda = 1e-3;
 
 </details>
 
+## Usage (Python)
+
+Coming soon.
+
 ## Benchmark
 
 ### Downsampling