MAP-Tk started as an open source C++ collection of libraries and tools for making measurements from aerial video. Initial capability focused on estimating the camera flight trajectory and a sparse 3D point cloud of a scene. These products are jointly optimized via sparse bundle adjustment and are geo-localized if given additional control points or GPS metadata.

This project has similar goals as projects like Bundler and VisualSFM. However, the focus here in on efficiently processing aerial video rather than community photo collections. Special attention has been given to the case where the variation in depth of the 3D scene is small compared to distance to the camera. In these cases, planar homographies can be used to assist feature tracking, stabilize the video, and aid in solving loop closure problems.

MAP-Tk uses the KWIVER software architecture. Originally developed for MAP-Tk, KWIVER is highly modular and provides an algorithm abstraction layer that allows seamless interchange and run-time selection of algorithms from various other open source projects like OpenCV, VXL, Ceres Solver, and PROJ4. The core library and tools are light-weight with minimal dependencies (C++ standard library, KWIVER vital, and Eigen). The tools are written to depend only on the MAP-Tk and KWIVER vital libraries. Additional capabilities are provided by KWIVER arrows (plugin modules) that use third party libraries to implement various abstract algorithm interfaces defined in the KWIVER vital library. Earlier versions of MAP-Tk contained these core data structures, algorithms, and plugins, but these have since been moved to KWIVER for easier reuse across projects. What remains in this repository are the tools, scripts, and applications required to apply KWIVER algorithms to photogrammetry problems. As MAP-Tk capabilities have continued to migrate up into KWIVER this repository has become less of a "toolkit" and more of an end user application that uses the KWIVER toolkit. Additionally the capabilities are starting to branch out beyond aerial data. As a result, we are transitioning away from the MAP-Tk name as this repository becomes more about the GUI application named TeleSculptor.

TeleSculptor is a GUI application built on Qt. It provides a graphical interface to run photogrammetry algorithms and assist with visualization of data and results with the help of VTK. The screenshots below show TeleSculptor running on example videos from the VIRAT Video Dataset, CLIF 2007 Dataset, and other public data sets. More information about this example data can be found in the examples directory.

TeleSculptor now supports visualization of depth maps, but compution of depth maps is not yet supported by KWIVER. Instead, the cameras computed by MAP-Tk can be used with a fork of PlaneSweepLib that reads in the cameras and images and produces depthmaps that the GUI can load. We are working on extending MAP-Tk TeleSculptor to compute depth maps directly.

While the initial software implementation relies on batch post-processing of aerial video, our intent is to move to an online video stream processing framework and optimize the algorithm to run in real-time.

MAP-Tk requires C++11 compliant compiler (e.g. GCC 4.8.1, Clang 3.3, Visual Studio 2015). MAP-Tk uses CMake (www.cmake.org) for easy cross-platform compilation. The minimum required version of CMake is 3.0, but newer versions are recommended.

The build is directed by CMake to ensure it can be built on various platforms. The code is built by a CMake 'superbuild', meaning as part of the build, CMake will download and build any dependent libraries needed by MAP-Tk. The build is also out of source, meaning the code base is to be seperate from the build files. This means you will need two folders, one for the source code and one for the build files. Here is the quickest way to build via a cmd/bash shell

By default the CMAKE_BUILD_TYPE is set to Release.

Separate directories are required for Debug and Release builds, requiring cmake to be run for each.

Even if you are using a Multi-Configuration build tool (like MSVC) to build Debug you must select the Debug CMAKE_BUILD_TYPE. (On Windows in order to debug a project all dependent projects must be build with Debug information.)

For MSVC users wanting a RelWithDebInfo build we recommend you still choose Release for the superbuild. Release and RelWithDebInfo are compatible with each other, and Fletch will build its base libraries as Release. MSVC solutions will provide both Release and RelWithDebInfo configuration options. You will need to open the <build/directory>/external/kwiver-build/KWIVER.sln and build this solution with the RelWithDebInfo configuration.

The MAP-Tk TeleSculptor GUI application is enabled by default, and all dependencies will be built by the Superbuild. You may choose to disable building the GUI by setting MAPTK_ENABLE_GUI to OFF

If MAPTK_ENABLE_MANUALS is enabled, and CMake finds all dependencies, then the user manuals are built as part of the normal build process under the target "manuals". The GUI manual can be viewed from inside the GUI by choosing the "MAP-Tk TeleSculptor User Manual" action from the "Help" menu.

To build the user manual(s), you need:

• Python

  version 2.6 or greater http://www.python.org/

• Docutils

  version 0.11 or greater http://docutils.sourceforge.net/

(At present, only the GUI has a user manual. Other manuals may be added in the future.)

Continuous integration testing is provided by CDash. Our MAP-Tk dashboard hosts nightly build and test results across multiple platforms including Windows, Mac, and Linux.

Anyone can contribute a build to this dashboard using the dashboard script provided. Follow the instructions in the comments.

Travis CI is also used for continued integration testing. Travis CI is limited to a single platform (Ubuntu Linux), but provides automated testing of all topic branches and pull requests whenever they are created.

Travis CI master branch:	_
Travis CI release branch:	_

MAP-Tk is built on top of the KWIVER toolkit. which is in turn built on the Fletch super build system. As mentioned above, to make it easier to build MAP-Tk, a "super-build" is provided to build both KWIVER and Fletch. But, if you wish, you may point the MAP-Tk build to use your own KWIVER builds.

If you would like MAP-Tk to use a prebuilt version of KWIVER, specify the kwiver_DIR flag to cmake. The kwiver_DIR is the KWIVER build directory root, which contains the kwiver-config.cmake file.

You must ensure that the specified build of KWIVER was built with at least the following options set:

The required KWIVER flags can be found in this file : CMake/maptk-external-kwiver.cmake

The required Fletch flags can be found in this file : CMake/maptk-external-fletch.cmake

MAP-Tk command line tools are placed in the bin directory of the build or install path. These tools are described below.

The primary tools are maptk_track_features and maptk_bundle_adjust_tracks. Together these form the sparse bundle adjustment pipeline. The other tools are for debugging and analysis purposes.

maptk_detect_and_describe

This optional tool pre-computes feature points and descriptors on each frame of video and caches them on disk. The same is also done in the maptk_track_features, so this step is not required. However, this tool makes better use of threading to process all frames in parallel.

maptk_track_featues

Takes a list of images and produces a feature tracks file.

maptk_bundle_adjust_tracks

Takes feature tracks and produces cameras (KRTD files) and 3D points (PLY file). Can also take input POS files or geo-reference points and produce optimized POS files.

maptk_apply_gcp

This tool takes an existing solution from maptk_bundle_adjust_tracks and uses provided ground control points (GCPs) to fit a 3D similarity transformation to align the solution to the GCPs. The same is done in the bundle adjust tool, but this tool lets you update and reapply GCPs without recomputing bundle adjustment.

maptk_pos2krtd

Takes POS files and directly produces KRTD.

maptk_analyze_tracks

Takes images and feature tracks and produces tracking statistics or images with tracks overlaid.

maptk_estimate_homography

Estimates a homography transformation between two images, outputting a file containing the matrices.

Each MAP-Tk tool has the same interface and accepts three command line arguments:

• -c to specify an input configuration file
• -o to output the current configuration to a file
• -h for help (lists these options)

Each tool has all of its options, including paths to input and output files, specified in the configuration file. To get started, run one of the tools like this:

$ maptk_track_features -o config_file.conf

This will produce an initial set of configuration options. You can then edit config_file.conf to specify input/output files, choices of algorithms, and algorithm parameters. Just as in CMake, configuring some parameters will enable new sub-parameters and you need to re-run the tool to get the updated list of parameters. For example:

$ maptk_track_features -c config_file.conf -o config_file.conf

The above command will overwrite the existing config file with a new file. Ordering of entries and comments are not preserved. Use a different output file name to prevent overwriting the original. Continue to adjust parameters and re-run the above command until the tool no longer reports the message:

ERROR: Configuration not valid.

Note that the config file itself contains detail comments documenting each parameter. For each abstract algorithm you must specify the name of variant to use, but the list of valid names (based on which modules are compiled) is provided directly in the comment for easy reference. When the config file is complete and valid, run the tool one final time as:

$ maptk_track_features -c config_file.conf

An easier way to get started is to use the sample configuration files for each tool that are provided in the examples directory. These examples use recommended default settings that are known to produce useful results on some selected public data samples. The example configuration files include the default configuration files for each algorithm in the config directory.

MAP-Tk is a component of Kitware's collection of open source computer vision tools known as KWIVER. Please join the kwiver-users mailing list to discuss MAP-Tk or to ask for help with using MAP-Tk. For less frequent announcements about MAP-Tk and other KWIVER components, please join the kwiver-announce mailing list.

The authors would like to thank AFRL/Sensors Directorate for their support of this work via SBIR Contract FA8650-14-C-1820. This document is approved for public release via 88ABW-2015-2555.