Motion Capture

Motion capture is an excellent tool for examining and analyzing human and robot movement. It tracks the locations of specific points through time. To represent such data, we present the mocap_point_cloud/MotionCapture message.

Message Details

MotionCapture messages have four primary features.

1. id - An optional string describing the motion capture

2. labels - An optional array of strings labeling each of the points in the cloud

3. frames - An array of PointClouds representing the locations of the markers through time.

4. rate - A float specifying the number of frames per second.

The labels should correspond to the points in the pointclouds such that label[i] is the label for the point stored at frames[t].points[i]. Missing data is demarcated with the point (0,0,0).

Mocap Storage

Reading motion capture data from their original compressed formats (i.e. c3d) can often be a slow process. Instead, we have started storing the data as rosbag files, containing mocap_point_cloud/MotionCapture messages.

Library

This package can be used either in library format in Python, or by using the four nodes described below.

mcpc_helper

This library contains basic operations for reading in and converting mocap files.

• load(filename) - reads in mocap data from a file. If the filename contains "c3d", it reads in the c3d file. Otherwise, it reads in the bag file. It returns an array of MotionCapture messages.

• read_from_c3d(filename) - reads in c3d file, returns as a MotionCapture

• read_from_bag(filename) - reads in bag file, returns array of MotionCaptures

• write_to_bag(filename, mocaps) - writes the array of MotionCaptures to a bag file

• There are also a number of helper functions (center, rotate, etc.)

mcpc_player

This library allows you to create a player object, which broadcasts the PointClouds over time, using specified topics. Example usage:

#python
player = MocapPlayer(scale=100.0)
player.add(mocap, "/mocap0")
player.play()

You can also send the messages for a particular frame using play_frame(t).

The MocapPlayer will broadcast the data points as PointClouds, with the labels sent out in Markers. It is also possible to create an additional set of Markers that draw a skeleton for the given points.

Nodes

This package provides four different nodes for reading/examining mocap data.

C3d Converter

This node uses the c3d package to convert c3d motion capture files to mocap_point_cloud/MotionCapture messages, stored in bag files.

rosrun mocap_point_cloud convert.py file1.c3d file2.c3d ...

This will convert the c3d files into the bag files file1.c3d

Play

This node will load a single c3d/bag file, and play its contents using the mcpc_player library. It will keep looping through all timepoints according to the frame rate, until manually killed.

rosrun mocap_point_cloud play.py file1.bag

Play using a GUI

This node is similar to Play, but allows the user to control which timepoint is displayed using a GUI slider.

rosrun mocap_point_cloud play_gui.py file1.bag

Statistics

The final node is a statistics utility that we've found useful in our own work. Given a list of c3d/bag files as parameters, it will print out the following statistics for each individual MotionCapture contained in the files.

• filename
• id
• Number of frames
• Number of points per frame ("tracks")
• Number of non-zero points in first time frame ("initial")
• Minimum/Maximum/Average number of non-zero points in any time frame ("minTrks"/"maxTrks"/"avgTrks")
• Minimum/Maximum/Average coverage of a given track over all time frames ("minCov"/"maxCov"/"avgCov")
• Number of tracks that are non-zero in all time frames ("full")
• Number of tracks that are non-zero in 90% of time frames