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The code for creation of a dataset for 6D pose estimation. The code was used to create the HomebrewedDB dataset.

Requirements

The code uses C++17 and has been tested on Windows platform with MS Visual Studio 2017. Here is the list of libraries with the versions the code has been tested with:

• OpenCV (with contrib modules) == 3.4.0 (BSD License: https://opencv.org/license/)
• VTK == 8.1.2 (BSD License: https://vtk.org/about/#license)
• Eigen == 3.3.4 (MPL2: http://eigen.tuxfamily.org/index.php?title=Main_Page#License)
• Ceres Solver == 1.14.0 (New BSD license: http://ceres-solver.org/license.html)
• Boost == 1.69 (Boost Software License - Version 1.0: https://www.boost.org/users/license.html)
• Qt == 5.13 ( GPL or LGPLv3 open source licenses)
• Glog == 0.3.3 (Apache License 2.0 -- https://github.com/golang/glog/blob/master/LICENSE)
• Gflags == 2.2.2 (BSD 3-Clause "New" or "Revised" License :https://github.com/gflags/gflags/blob/master/COPYING.txt)
• nlohmann/json == 3.4.0 (MIT License)
• yaml-cpp == 0.6.2 (MIT License)
• Halcon HDevelop == 18.11 Progress (Halcon Campus License: https://www.mvtec.com/company/on-campus/licenses/). Note that the parts of the SW using Hacon Library will not function unless you get Halcon Campus License from MVTec Software GmbH or their authorized dealers.)

For RGB-D images capturing the follwoing SDKs were used:

• OpenNI2, alternatively libfreenect (Apache License 2.0)
• Kinect For Windows SDK 2.0 (Microsoft Kinect for Windows Software Development Kit (SDK) 2.0, End User License Agreement: https://download.microsoft.com/download/0/D/C/0DC5308E-36A7-4DCD-B299-B01CDFC8E345/Kinect-SDK2.0-EULA_en-US.pdf )
• Intel RealSense SDK 2.0 (Apache License, Version 2.0.)
• Kinect Azure SDK 1.3.0 (MIT License)

Building

Having the required libraries installed and respective environment variables set, each sub-project can be built using CMake and further compiled with Visual Studio.

Environment

rgbd_capture

This project is composed of two modules: librgbdcapture and app. First, build librgbdcapture. Then, to build app, place the respective binaries of librgbdcapture into app/librgbdcapture/lib and app/librgbdcapture/bin.

refiner

This project depends on libqtoffscreenrenderer. Build and compile libqtoffscreenrenderer and place its respective binaries into refiner/third-party/librenderer/lib refiner/third-party/librenderer/bin, then build and compile refiner.

gtwriter

This project depends on libqtoffscreenrenderer. Build and compile libqtoffscreenrenderer and place its respective binaries into gtwriter/third-party/librenderer/lib gtwriter/third-party/librenderer/bin, then build and compile gtwriter.

Other subprojects do not require any particular handling to be built.

Usage

rgbd_capture/app

Used to capture sequences of rgb-d images. Captured images are stored into respective directories <out_dir>/rgb and <out_dir>/depth

{help h       |          | help message   }		
{camera       |          | RGB-D camera (kinect, kinect2, realsense or kinect_azure)}
{num_frames   |          | number of frames to capture}
{async_save   |          | save frames asynchronously or store in memory while capturing}
{out_dir      |          | output directory for images}
{timeout      |          | timeout between frames in ms (for non-async capturing)}

sdf_fusion

Used to filter frames with correctly estimated camera poses. Stores correct poses and respective images, and then performs a dense 3D reconstruction of the scene. Outputs camera_poses.txt, images directory with valid rgb and depth images and a dense reconstruction of the scene in model.ply file.

{help h usage ?  |          | help on usage}
{images_dir      |          | input images dir containing /rgb and /depth dirs}
{config_dir      |          | config dir containing board.yml and dict.yml for AruCo markerboard}
{intrinsics_file |          | file containing row-wise intrinsic matrix}
{marker_size     |  0.0491  | marker size of the markerboard (in meters)}
{voxel_size      |  0.002   | voxel size}
{preprocess      |          | do pose estimation and discarding of frames }
{req_num_frames  |          | out number of frames to perform reconstruction}
{out_dir         |          | out directory for storing camera poses, filtered images, reconstructed mesh}

ppfshapematchinghalcon

Used to estimate poses of 3D models in the densely reconstructed scene. Reference models used for refinement must be stored in a format obj_xxxxx.ply in meters. Poses are ouputed into scene out directory <scene_dir>/object_poses in format xxxxxx.txt and stored as a 4x4 matrix. scene_dir must be a directory where the output of sdf_fusion is stored.

{ help h usage ?  |          | help on usage }
{ref_models_dir   |          | reference models directory}
{scene_dir        |          | directory containing the scene}
{model_ids        |          | comma-separated model ids}
{rel_smp_dist     |   0.05   | relative sampling distance}
{kp_frac          |   0.4    | keypoint fraction}

refiner

Use to refine poses using multi-view edge based refinement on rgb images. scene_dir must be the same directory as used by ppfshapematchinghalcon, where the output of sdf_fusion is stored.

{help h usage ? |          | help on usage }
{scene_dir      |          | path to the scene where poses must be refined}
{model_ids      |     -1   | model ids to be refined, default -1, i.e. refinement for all object_poses}
{config_file    |          | path to the json config file (e.g. see refiner/config/config.json}

gtwriter/scene-gt-writer

Used to write pose ground truth labels for scenes.

{help h               |         | help message}
{intrinsics_file      |         | intrinsics file}
{reference_models_dir |         | directory with reference models}
{scenes_dirs          |         | comma separated scene directories, which will be joined}
{out_dir              |         | output directory}
{copy_images          |         | should re-index images and copy the do the output dir}

gtwriter/model-info-writer

Used to compute meta-info for the 3D models.

{help h      |         | help message }
{models_dir  |         | models dir}

refine-depth

A utility used to estimate a first degree polynomial correction function for depth. The correction function treats depth in meters. The images must capture an empty AruCo markerboard at different distances and elevations.

{help h          |         | help message}
{images_dir      |         | input images dir}
{config_dir      |         | configuration dir with board.yml and dict.yml files for AruCo markerboard}
{intrinsics_file |         | intrinsics file}
{marker_size     |         | marker size in meters}