updated readme and added some comments about planned work

README.md

-# Using OPENPOSE Wrapper
+# openpose_ros 
+My ROS Wrapper for openpose https://github.com/CMU-Perceptual-Computing-Lab/openpose
+(see commit number `a1e0a5f4136e702b5731a268c2993fb75ca4753c`)
+# Installing and Testing the Openpose ROS Wrapper
 1. Install openpose and its dependencies then enable the package by running
 ````
 ./install_openpose_and_enable_package.sh
@@ -20,7 +23,8 @@ and subscribe to `/openpose_ros/input_image` for the input image and `/openpose_
 
 
 # Similar packages
-Naturally, `openpose` is quite popular and similar packages for ros can be found on
+Naturally, `openpose` is quite popular and similar packages for ros can be found at
 
 https://github.com/tue-robotics/openpose_ros
+
 https://github.com/firephinx/openpose_ros
\ No newline at end of file

skeleton_extract_3d/launch/openpose_skeleton_extract.launch

 <launch>
   <!-- Launch openpose service-->
-  <node name="openpose_ros_node" pkg="openpose_ros_pkg" type="openpose_ros_node" />
+  <node name="openpose_ros_node" pkg="openpose_ros_pkg" type="openpose_ros_node" output="screen" />
   <!-- Launch the skeleton extractor node -->
   <node name="skeleton_extract_3d_node" pkg="skeleton_extract_3d" type="skeleton_extract_3d_node" >
     <remap from="~point_cloud" to="/multisense/organized_image_points2_color_reverse_order" />

skeleton_extract_3d/src/skeleton_extract_3d_node.cpp

@@ -32,6 +32,21 @@ void callback(const sensor_msgs::PointCloud2ConstPtr& cloud_msg, const sensor_ms
       if (client.call(srv))
       {
         ROS_INFO("ROS Service call Successful");
+        // Prepare a new ROS Message for all skeletal detections
+        // Prepare a new point cloud to publish
+
+        // for each detection,
+          // Prepare a new ROS Message for this skeletal detection
+          // Prepare a new color to use
+
+          // for each body part 
+              // grab a small area of pixels surrounding the x,y image coordinate
+
+                  //for each pixel in that area, check if it is a valid point: (the point exists in the organized point cloud and that its z-depth is less than Z_MAX)
+                  //      mean-shift valid 3D points and store largest cluster
+
+                  //      
+
 //        ROS_INFO("Hello!: %ld", (long int)srv.response.sum);
       }
       else