Pine Island Glacier and Pine Island Bay

@article{Mankoff:2012The-role,
	Title = {{The role of Pine Island Glacier ice shelf basal
                  channels in deep water upwelling, polynyas, and
                  ocean circulation in Pine Island Bay, Antarctica}},
	Author = {Kenneth D. Mankoff and Stanley S. Jacobs and
                  Slawek M. Tulaczyk and Sharon E. Stammerjohn},
	Journal = {Annals of Glaciology},
	Number = {60},
	Volume = {53},
	Year = {2012}}

AGU Poster: `Kinects as sensors in earth science: glaciological, geomorphological, and hydrological applications`

@conference{Mankoff:2011Kinects,
  Author = {Kenneth D. Mankoff and Tess Alethea Russo and
            Benjamin Kenneth Norris and Saffia Hossainzadeh and
            Lucas H. Beem and Jacob I. Walter and
            Slawek M. Tulaczyk},
  Title = {{Kinects as sensors in earth science: glaciological,
            geomorphological, and hydrological applications}},
  Address = {San Francisco, CA},
  Booktitle = {American Geophysical Union, Fall Meeting},
  Month = {December 5 - 9,},
  Note = {Abstract \#C41D-0442.},
  Year = {2011}}

Kinect Go Kit: Top level

Kinect Go Kit Pelican Case

I travel with two Kinects, two power supplies, and two computers in case one gets damaged or destroyed in the field, although only one computer is in the kit.

The Netbook is a cheap $240 computer running Ubuntu and the libfreenect software stack at a minimum. I have also found it useful to have more advanced data collection software (ROS, RGBDemo, RGBDSLAM), and some analysis software (CloudCompare, points2grid, Viewpoints, etc.). This netbook works fine for raw data dumps from the libfreenect ‘record’ program. It can run the more computationally expensive scene stitching algorithms such as RGBDSLAM, but it takes about 10 seconds per stitch, while a more powerful laptop (but still a few years old) can do it at 0.5 to 1 Hz. Since ‘record’ collects about 1.5 GB of data per minute, it is good to have a lot of free space on the hard drive.

The plugs and cables are shown laid out below, and in addition, some velcro straps are stored in that compartment, used to attach the Kinect to the tripod arm.

The Pelican 1510 case supports two levels, and the lower level looks like this:

Kinect Go Kit: Bottom level

Battery #1 is a 12 V 5 Ah sealed led acid battery. It provides >5 hours of Kinect runtime, about equal to the runtime of the netbook.

Battery #2 is 8 AA batteries (12 V), and underneath is an 8 AA battery holder and a battery charger. If I need to turn the Kinect on for a short amount of time and want to travel lightly, these will do.

Kinect cable layouts

As shown above the cord to the Kinect can be cut and alligator clips or some other electrical termination can be attached. I often have wall power and have attached clips to the detached plug so I can use it as originally intended. However, when in the field, the clips can connect directly to the 12 V battery or the AA battery pack.

Kinect mounted on tripod

The Kinect Go Kit above is close to the minimum necessary for fieldwork. Things that I would like in it, but are not yet, include:

• Tape measure
• Liquid container (tupperwear) and opaque liquid (or additive) so that any scene can have a defined flat surface
• Sling for under tripod to hold battery, netbook, protecting equipment and keeping it off the ground
• Counter weight for tripod arm

Additional tools I have found handy to have with me in the field include, but are not limited to, the following:

• External hard disk for backups
• Zip-ties to complement the Velcro straps
• Multimeter
• Spare notebook, perhaps with a more powerful CPU, for scene stitching
• Rope or other ‘image noise’ for scene stitching with RGBSLAM when working in environments that have ‘self similar’ scenes (no good tie points)
• Mounting systems for long term deployment
• Trashbags for environmental protection

There are a variety software interfaces to the Kinect. One high-level tool that is easy to use (binaries provided, no need to compile source, supports ‘scene painting’) is RGB-Demo. It is a good tool to start with if you want to work with the Kinect.

However, most Kinect software and calibrations so far have been developed by the robotics and computer vision communities. I am grateful for the work they have done, but those communities have different data needs than earth scientists. For example, quadrotor obstacle avoidance (link (PDF), link) has distance measurement errors that appear to be on order cm, but it still works fine as the helicopter avoids obstacles by an amount larger than the error.

Earth scientists should aim for a better model of the world than the one currently provided by the Kinect and its primary users. I suggest recording and storing the raw digital numbers (DN) from the Kinect rather than higher-level auto-calibrated real-world coordinates. It will require more post-processing, but storing the DNs will allow the data to be re-processed as better calibrations are developed. In addition, the low level recorder operates at 30 Hz and the higher level point-cloud products currently do not record data at that rate.

The best supported low-level interface is the LibFreenect Fakenect record program. It dumps the uncalibrated RGB and depth images to a folder at 30 Hz until you kill the process. Uncalibrated means both that the depth data is in sensor units, and that the depth and RGB images are not aligned. You can easily convert the depth data to real world x,y,z coordinates using existing published algorithms (link, link, link, and many others exist on the web), but importantly the raw data is stored and can be used with better calibrations in the future.

After processing the raw ‘record’ data, you can work with the point cloud data or DEMs using a variety of standard software for pointclouds, LiDAR, etc. I have had great success with CloudCompare and Poinst2Grid, in addition to custom code in MATLAB, IDL, and Python. A good list of software is available at the NSF OpenTopography site.

To work with the depth data to we initially use the following algorithms found on the various sites dedicated to Kinect hacking. The data provided by these algorithms is sufficient for certain uses, and for testing algorithms and visualizations, while better calibrations are performed.

DN to distance (source):

k1 = 1.1863d
k2 = 2842.5d
k3 = 0.1236d
Z = k3 * tan( double( DN ) / k2 + k1 )

XYZ to world (source):

Xres = 640
Yres = 480
FovH = 1.0144686707507438 (rad)
FovV = 0.78980943449644714 (rad)
XtoZ = tan( FovH / 2 ) * 2
YtoZ = tan( FovV / 2 ) * 2
X = ( X_pixel / Xres – 0.5 ) * Z * XtoZ
Y = ( 0.5 – Y_pixel / Yres ) * Z * YtoZ

Question or comments? Post below…

Can I unplug my fridge at night without ruining my food?

BUBBLES is an acronym for some combination of the words Bubbles the Underwater Undersea Blue Bathymetric Basal Buoyant Little Liquid Exploration Submersible or Submarine.

Bubble was previously deployed in a hot-tub and in Younger Lagoon, Santa Cruz, CA, as test sites. Recently Bubbles went swimming under the ice-covered Silver Lake near Kirkwood, CA. Due to the late season, we could not walk on the ice and the shore-based deployment was complicated by the shallow waters. Nevertheless, she again proved to be liquid-worthy, and spent some time swimming in the shallow waters with some fish.

Bubbles heading under the ice. Photo by E. Lynne Harden

Bubbles operations. Photo by E. Lynne Harden

Bubbles was built by Ken Mankoff and E. Lynne Harden.