| POQUITO Dataset that accompanies the paper: | |
| "Tiny Satellites, Big Challenges: A Feasibility Study of Machine Vision Pose Estimation for PocketQubes during Conjunctions" | |
| Niki Sajjad, Andrew Price, Mehran Mirshams and Mathieu Salzmann | |
| September 2024 | |
| The dataset formatting is adapted from the BOP format. | |
| The dataset is organized as: | |
| POQUITO_Dataset | |
| |---1_Distance_Check_Data | |
| |---Training | |
| |---Validation | |
| |---Testing | |
| |---2_Performance_Check_Data | |
| |---Training | |
| |---Validation | |
| |---Testing | |
| |---1_Stationary_cases | |
| |---2_Sequential_Trajectories | |
| |---Trajectory1 | |
| |---Trajectory2 | |
| |---Trajectory3 | |
| |---Trajectory4 | |
| |---Trajectory5 | |
| |---3_Satellite_Model | |
| |---POQUITO_bbox.json | |
| |---POQUITO.ply | |
| |---4_Earth_Background | |
| |---real_Earth_images | |
| |---real_Earth_images_cropped | |
| |---rendered_Earth_images | |
| |---README.txt | |
| [1] Contains images of the POQUITO target centred on the image. The distance from the camera to the POQUITO is slowly increased. | |
| [2] Contains rgb images with various post processing affects applied. | |
| -foc- camera depth of field (focal) blur applied as Gaussian blurring. | |
| -mot- motion blur applied with custom XiaolinWu filter kernels. | |
| -earth- images of the Earth inserted into the background. | |
| Testing contains two separate cases, <1_Stationary_cases> and <2_Sequential_Trajectories> | |
| /Testing/1_Stationary_cases/ is similar to Training and <Validation | |
| /Testing/2_Sequential_Trajectories/ contains 5 trajectories, the motion blur and focal blur included in these trajectories is physically proportional and is labeled. | |
| Ex. /2_Performance_Check_Data/Testing/2_Sequential_Trajectories/Trajectory1/rgb_foc/0.45 contains images with a Gaussian blur std of 0.45 applied. | |
| Ex. /2_Performance_Check_Data/Testing/2_Sequential_Trajectories/Trajectory1/rgb_motEarth/15 contains images with Earth background and a motion blur kernel of 15 applied. | |
| [3] Contains the POQUITO CAD file and POQUITO_bbox.json which contains 8 xyz points [millimetres] defining the bounding box of POQUITO. | |
| [4] Contains the Earth background images inserted during post processing to 2_Performance_Check_Data | |
| rgb folders contain the images | |
| mask_visib folders contain masks indicating the visible portion of the target | |
| scene_gt.json contains the ground truth pose annotations for images in the associated directory. | |
| scene_camera.json contains the camera intrinsics for images in the associated directory. Note we use the same camera intrinsics for the entire dataset. | |
| If you use this dataset, please consider citing our work. | |
| @article{POQUITO_Sajjad2024, | |
| title={Tiny Satellites, Big Challenges:A Feasibility Study of Machine Vision Pose Estimation for PocketQubes during Conjunctions}, | |
| author={Niki Sajjad and Andrew Price and Mehran Mirshams and Mathieu Salzmann}, | |
| journal={}, | |
| year={}, | |
| volume={}, | |
| number={}, | |
| pages={}, | |
| doi={} | |
| } |