--- license: cc-by-4.0 --- Monado SLAM Datasets cover image # Monado SLAM Datasets The [Monado SLAM datasets (MSD)](https://huggingface.co/datasets/collabora/monado-slam-datasets), are egocentric visual-inertial SLAM datasets recorded to improve the [Basalt](https://gitlab.com/VladyslavUsenko/basalt)-based inside-out tracking component of the [Monado](https://monado.dev) project. These have a permissive license [CC-BY 4.0](http://creativecommons.org/licenses/by/4.0/), meaning you can use them for any purpose you want, including commercial, and only a mention of the original project is required. The creation of these datasets was supported by [Collabora](https://collabora.com) Monado is an open-source OpenXR runtime that you can use to make devices OpenXR compatible. It also provides drivers for different existing hardware thanks to different contributors in the community creating drivers for it. Monado provides different XR-related modules that these drivers can use. To be more specific, inside-out head tracking is one of those modules and, while you can use different tracking systems, the main system is a [fork of Basalt](https://gitlab.freedesktop.org/mateosss/basalt). Creating a good open-source tracking solution requires a solid measurement pipeline to understand how changes in the system affect tracking quality. For this reason, the creation of these datasets was essential. These datasets are very specific to the XR use case as they contain VI-SLAM footage recorded from devices such as VR headsets, but other devices like phones or AR glasses might be added in the future. These were made since current SLAM datasets like EuRoC or TUM-VI were not specific enough for XR, or they didn't have permissively enough usage licenses. For questions or comments, you can use the Hugging Face [Community](https://huggingface.co/datasets/collabora/monado-slam-datasets/discussions), join Monado's discord [server](https://discord.gg/8RkJgRJ) and ask in the `#slam` channel, or send an email to . ## List of sequences - [MI_valve_index](https://huggingface.co/datasets/collabora/monado-slam-datasets/tree/main/M_monado_datasets/MI_valve_index) - [MIC_calibration](https://huggingface.co/datasets/collabora/monado-slam-datasets/tree/main/M_monado_datasets/MI_valve_index/MIC_calibration) - [MIC01_camcalib1](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MI_valve_index/MIC_calibration/MIC01_camcalib1.zip):
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- [MIC02_camcalib2](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MI_valve_index/MIC_calibration/MIC02_camcalib2.zip):
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- [MIC03_camcalib3](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MI_valve_index/MIC_calibration/MIC03_camcalib3.zip):
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- [MIC04_imucalib1](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MI_valve_index/MIC_calibration/MIC04_imucalib1.zip):
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- [MIC05_imucalib2](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MI_valve_index/MIC_calibration/MIC05_imucalib2.zip):
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- [MIC06_imucalib3](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MI_valve_index/MIC_calibration/MIC06_imucalib3.zip):
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- [MIC07_camcalib4](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MI_valve_index/MIC_calibration/MIC07_camcalib4.zip):
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- [MIC08_camcalib5](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MI_valve_index/MIC_calibration/MIC08_camcalib5.zip):
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- [MIC09_imucalib4](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MI_valve_index/MIC_calibration/MIC09_imucalib4.zip):
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- [MIC10_imucalib5](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MI_valve_index/MIC_calibration/MIC10_imucalib5.zip):
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- [MIC11_camcalib6](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MI_valve_index/MIC_calibration/MIC11_camcalib6.zip):
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- [MIC12_imucalib6](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MI_valve_index/MIC_calibration/MIC12_imucalib6.zip):
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- [MIC13_camcalib7](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MI_valve_index/MIC_calibration/MIC13_camcalib7.zip):
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- [MIC14_camcalib8](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MI_valve_index/MIC_calibration/MIC14_camcalib8.zip):
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- [MIC15_imucalib7](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MI_valve_index/MIC_calibration/MIC15_imucalib7.zip):
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- [MIC16_imucalib8](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MI_valve_index/MIC_calibration/MIC16_imucalib8.zip):
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- [MIO_others](https://huggingface.co/datasets/collabora/monado-slam-datasets/tree/main/M_monado_datasets/MI_valve_index/MIO_others) - [MIO01_hand_puncher_1](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MI_valve_index/MIO_others/MIO01_hand_puncher_1.zip):
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- [MIO02_hand_puncher_2](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MI_valve_index/MIO_others/MIO02_hand_puncher_2.zip):
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- [MIO03_hand_shooter_easy](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MI_valve_index/MIO_others/MIO03_hand_shooter_easy.zip):
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- [MIO04_hand_shooter_hard](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MI_valve_index/MIO_others/MIO04_hand_shooter_hard.zip):
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- [MIO05_inspect_easy](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MI_valve_index/MIO_others/MIO05_inspect_easy.zip):
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- [MIO06_inspect_hard](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MI_valve_index/MIO_others/MIO06_inspect_hard.zip):
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- [MIO07_mapping_easy](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MI_valve_index/MIO_others/MIO07_mapping_easy.zip):
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- [MIO08_mapping_hard](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MI_valve_index/MIO_others/MIO08_mapping_hard.zip):
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- [MIO09_short_1_updown](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MI_valve_index/MIO_others/MIO09_short_1_updown.zip):
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- [MIO10_short_2_panorama](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MI_valve_index/MIO_others/MIO10_short_2_panorama.zip):
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- [MIO11_short_3_backandforth](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MI_valve_index/MIO_others/MIO11_short_3_backandforth.zip):
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- [MIO12_moving_screens](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MI_valve_index/MIO_others/MIO12_moving_screens.zip):
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- [MIO13_moving_person](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MI_valve_index/MIO_others/MIO13_moving_person.zip):
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- [MIO14_moving_props](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MI_valve_index/MIO_others/MIO14_moving_props.zip):
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- [MIO15_moving_person_props](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MI_valve_index/MIO_others/MIO15_moving_person_props.zip):
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- [MIO16_moving_screens_person_props](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MI_valve_index/MIO_others/MIO16_moving_screens_person_props.zip):
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- [MIP_playing](https://huggingface.co/datasets/collabora/monado-slam-datasets/tree/main/M_monado_datasets/MI_valve_index/MIP_playing) - [MIPB_beat_saber](https://huggingface.co/datasets/collabora/monado-slam-datasets/tree/main/M_monado_datasets/MI_valve_index/MIP_playing/MIPB_beat_saber) - [MIPB01_beatsaber_100bills_360_normal](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MI_valve_index/MIP_playing/MIPB_beat_saber/MIPB01_beatsaber_100bills_360_normal.zip):
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- [MIPB02_beatsaber_crabrave_360_hard](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MI_valve_index/MIP_playing/MIPB_beat_saber/MIPB02_beatsaber_crabrave_360_hard.zip):
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- [MIPB03_beatsaber_countryrounds_360_expert](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MI_valve_index/MIP_playing/MIPB_beat_saber/MIPB03_beatsaber_countryrounds_360_expert.zip):
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- [MIPB04_beatsaber_fitbeat_hard](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MI_valve_index/MIP_playing/MIPB_beat_saber/MIPB04_beatsaber_fitbeat_hard.zip):
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- [MIPB05_beatsaber_fitbeat_360_expert](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MI_valve_index/MIP_playing/MIPB_beat_saber/MIPB05_beatsaber_fitbeat_360_expert.zip):
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- [MIPB06_beatsaber_fitbeat_expertplus_1](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MI_valve_index/MIP_playing/MIPB_beat_saber/MIPB06_beatsaber_fitbeat_expertplus_1.zip):
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- [MIPB07_beatsaber_fitbeat_expertplus_2](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MI_valve_index/MIP_playing/MIPB_beat_saber/MIPB07_beatsaber_fitbeat_expertplus_2.zip):
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- [MIPB08_beatsaber_long_session_1](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MI_valve_index/MIP_playing/MIPB_beat_saber/):
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- [MIPP_pistol_whip](https://huggingface.co/datasets/collabora/monado-slam-datasets/tree/main/M_monado_datasets/MI_valve_index/MIP_playing/MIPP_pistol_whip) - [MIPP01_pistolwhip_blackmagic_hard](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MI_valve_index/MIP_playing/MIPP_pistol_whip/MIPP01_pistolwhip_blackmagic_hard.zip):
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- [MIPP02_pistolwhip_lilith_hard](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MI_valve_index/MIP_playing/MIPP_pistol_whip/MIPP02_pistolwhip_lilith_hard.zip):
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- [MIPP03_pistolwhip_requiem_hard](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MI_valve_index/MIP_playing/MIPP_pistol_whip/MIPP03_pistolwhip_requiem_hard.zip):
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- [MIPP04_pistolwhip_revelations_hard](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MI_valve_index/MIP_playing/MIPP_pistol_whip/MIPP04_pistolwhip_revelations_hard.zip):
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- [MIPP05_pistolwhip_thefall_hard_2pistols](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MI_valve_index/MIP_playing/MIPP_pistol_whip/MIPP05_pistolwhip_thefall_hard_2pistols.zip):
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- [MIPP06_pistolwhip_thegrave_hard](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MI_valve_index/MIP_playing/MIPP_pistol_whip/MIPP06_pistolwhip_thegrave_hard.zip):
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- [MIPT_thrill_of_the_fight](https://huggingface.co/datasets/collabora/monado-slam-datasets/tree/main/M_monado_datasets/MI_valve_index/MIP_playing/MIPT_thrill_of_the_fight) - [MIPT01_thrillofthefight_setup](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MI_valve_index/MIP_playing/MIPT_thrill_of_the_fight/MIPT01_thrillofthefight_setup.zip):
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- [MIPT02_thrillofthefight_fight_1](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MI_valve_index/MIP_playing/MIPT_thrill_of_the_fight/MIPT02_thrillofthefight_fight_1.zip):
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- [MIPT03_thrillofthefight_fight_2](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MI_valve_index/MIP_playing/MIPT_thrill_of_the_fight/MIPT03_thrillofthefight_fight_2.zip):
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- [MG_reverb_g2](https://huggingface.co/datasets/collabora/monado-slam-datasets/tree/main/M_monado_datasets/MG_reverb_g2) - [MGC_calibration](https://huggingface.co/datasets/collabora/monado-slam-datasets/tree/main/M_monado_datasets/MG_reverb_g2/MGC_calibration) - [MGC01_camcalib01_1](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MG_reverb_g2/MGC_calibration/MGC01_camcalib01_1.zip):
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- [MGC02_camcalib02_1](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MG_reverb_g2/MGC_calibration/MGC02_camcalib02_1.zip):
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- [MGC03_camcalib13_1](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MG_reverb_g2/MGC_calibration/MGC03_camcalib13_1.zip):
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- [MGC04_imucalib01_1](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MG_reverb_g2/MGC_calibration/MGC04_imucalib01_1.zip):
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- [MGC05_imucalib02_1](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MG_reverb_g2/MGC_calibration/MGC05_imucalib02_1.zip):
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- [MGC06_imucalib13_1](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MG_reverb_g2/MGC_calibration/MGC06_imucalib13_1.zip):
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- [MGC07_magcalib_1](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MG_reverb_g2/MGC_calibration/MGC07_magcalib_1.zip):
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- [MGC08_camcalib01_2](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MG_reverb_g2/MGC_calibration/MGC08_camcalib01_2.zip):
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- [MGC09_camcalib02_2](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MG_reverb_g2/MGC_calibration/MGC09_camcalib02_2.zip):
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- [MGC10_camcalib13_2](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MG_reverb_g2/MGC_calibration/MGC10_camcalib13_2.zip):
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- [MGC11_imucalib01_2](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MG_reverb_g2/MGC_calibration/MGC11_imucalib01_2.zip):
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- [MGC12_imucalib02_2](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MG_reverb_g2/MGC_calibration/MGC12_imucalib02_2.zip):
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- [MGC13_imucalib13_2](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MG_reverb_g2/MGC_calibration/MGC13_imucalib13_2.zip):
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- [MGC14_magcalib_2](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MG_reverb_g2/MGC_calibration/MGC14_magcalib_2.zip):
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- [MGC15_camcalib01_3](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MG_reverb_g2/MGC_calibration/MGC15_camcalib01_3.zip):
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- [MGC16_camcalib02_3](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MG_reverb_g2/MGC_calibration/MGC16_camcalib02_3.zip):
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- [MGC17_camcalib13_3](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MG_reverb_g2/MGC_calibration/MGC17_camcalib13_3.zip):
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- [MGC18_imucalib01_3](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MG_reverb_g2/MGC_calibration/MGC18_imucalib01_3.zip):
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- [MGC19_imucalib02_3](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MG_reverb_g2/MGC_calibration/MGC19_imucalib02_3.zip):
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- [MGC20_imucalib13_3](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MG_reverb_g2/MGC_calibration/MGC20_imucalib13_3.zip):
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- [MGC21_magcalib_3](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MG_reverb_g2/MGC_calibration/MGC21_magcalib_3.zip):
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- [MGC22_camcalib01_4](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MG_reverb_g2/MGC_calibration/MGC22_camcalib01_4.zip):
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- [MGC23_camcalib02_4](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MG_reverb_g2/MGC_calibration/MGC23_camcalib02_4.zip):
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- [MGC24_camcalib13_4](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MG_reverb_g2/MGC_calibration/MGC24_camcalib13_4.zip):
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- [MGC25_imucalib01_4](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MG_reverb_g2/MGC_calibration/MGC25_imucalib01_4.zip):
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- [MGC26_imucalib02_4](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MG_reverb_g2/MGC_calibration/MGC26_imucalib02_4.zip):
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- [MGC27_imucalib13_4](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MG_reverb_g2/MGC_calibration/MGC27_imucalib13_4.zip):
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- [MGC28_magcalib_4](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MG_reverb_g2/MGC_calibration/MGC28_magcalib_4.zip):
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- [MGO_others](https://huggingface.co/datasets/collabora/monado-slam-datasets/tree/main/M_monado_datasets/MG_reverb_g2/MGO_others) - [MGO01_low_light](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MG_reverb_g2/MIO_others/MGO01_low_light.zip):
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- [MGO02_hand_puncher](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MG_reverb_g2/MIO_others/MGO02_hand_puncher.zip):
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- [MGO03_hand_shooter_easy](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MG_reverb_g2/MIO_others/MGO03_hand_shooter_easy.zip):
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- [MGO04_hand_shooter_hard](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MG_reverb_g2/MIO_others/MGO04_hand_shooter_hard.zip):
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- [MGO05_inspect_easy](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MG_reverb_g2/MIO_others/MGO05_inspect_easy.zip):
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- [MGO06_inspect_hard](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MG_reverb_g2/MIO_others/MGO06_inspect_hard.zip):
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- [MGO07_mapping_easy](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MG_reverb_g2/MIO_others/MGO07_mapping_easy.zip):
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- [MGO08_mapping_hard](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MG_reverb_g2/MIO_others/MGO08_mapping_hard.zip):
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- [MGO09_short_1_updown](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MG_reverb_g2/MIO_others/MGO09_short_1_updown.zip):
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- [MGO10_short_2_panorama](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MG_reverb_g2/MIO_others/MGO10_short_2_panorama.zip):
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- [MGO11_short_3_backandforth](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MG_reverb_g2/MIO_others/MGO11_short_3_backandforth.zip):
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- [MGO12_freemovement_long_session](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MG_reverb_g2/MIO_others):
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- [MGO13_sudden_movements](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MG_reverb_g2/MIO_others/MGO13_sudden_movements.zip):
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- [MGO14_flickering_light](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MG_reverb_g2/MIO_others/MGO14_flickering_light.zip):
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- [MGO15_seated_screen](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MG_reverb_g2/MIO_others/MGO15_seated_screen.zip):
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- [MOC_calibration](https://huggingface.co/datasets/collabora/monado-slam-datasets/tree/main/M_monado_datasets/MO_odyssey_plus/MOC_calibration) - [MOC01_camcalib_1](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MO_odyssey_plus/MOO_calibration/MOC01_camcalib_1.zip):
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- [MOC02_imucalib_1](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MO_odyssey_plus/MOO_calibration/MOC02_imucalib_1.zip):
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- [MOC03_magcalib_1](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MO_odyssey_plus/MOO_calibration/MOC03_magcalib_1.zip):
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- [MOC04_camcalib_2](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MO_odyssey_plus/MOO_calibration/MOC04_camcalib_2.zip):
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- [MOC05_imucalib_2](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MO_odyssey_plus/MOO_calibration/MOC05_imucalib_2.zip):
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- [MOC06_magcalib_2](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MO_odyssey_plus/MOO_calibration/MOC06_magcalib_2.zip):
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- [MOC07_camcalib_3](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MO_odyssey_plus/MOO_calibration/MOC07_camcalib_3.zip):
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- [MOC08_imucalib_3](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MO_odyssey_plus/MOO_calibration/MOC08_imucalib_3.zip):
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- [MOC09_magcalib_3](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MO_odyssey_plus/MOO_calibration/MOC09_magcalib_3.zip):
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- [MOC10_camcalib_4](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MO_odyssey_plus/MOO_calibration/MOC10_camcalib_4.zip):
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- [MOC11_imucalib_4](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MO_odyssey_plus/MOO_calibration/MOC11_imucalib_4.zip):
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- [MOC12_magcalib_4](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MO_odyssey_plus/MOO_calibration/MOC12_magcalib_4.zip):
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- [MOC13_imustatic](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MO_odyssey_plus/MOO_calibration/MOC13_imustatic.zip):
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- [MOO_others](https://huggingface.co/datasets/collabora/monado-slam-datasets/tree/main/M_monado_datasets/MO_odyssey_plus/MOO_others) - [MOO01_hand_puncher_1](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MO_odyssey_plus/MOO_others/MOO01_hand_puncher_1.zip):
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- [MOO02_hand_puncher_2](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MO_odyssey_plus/MOO_others/MOO02_hand_puncher_2.zip):
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- [MOO03_hand_shooter_easy](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MO_odyssey_plus/MOO_others/MOO03_hand_shooter_easy.zip):
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- [MOO04_hand_shooter_hard](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MO_odyssey_plus/MOO_others/MOO04_hand_shooter_hard.zip):
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- [MOO05_inspect_easy](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MO_odyssey_plus/MOO_others/MOO05_inspect_easy.zip):
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- [MOO06_inspect_hard](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MO_odyssey_plus/MOO_others/MOO06_inspect_hard.zip):
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- [MOO07_mapping_easy](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MO_odyssey_plus/MOO_others/MOO07_mapping_easy.zip):
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- [MOO08_mapping_hard](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MO_odyssey_plus/MOO_others/MOO08_mapping_hard.zip):
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- [MOO09_short_1_updown](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MO_odyssey_plus/MOO_others/MOO09_short_1_updown.zip):
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- [MOO10_short_2_panorama](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MO_odyssey_plus/MOO_others/MOO10_short_2_panorama.zip):
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- [MOO11_short_3_backandforth](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MO_odyssey_plus/MOO_others/MOO11_short_3_backandforth.zip):
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- [MOO12_freemovement_long_session](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MO_odyssey_plus/MOO_others/):
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- [MOO13_sudden_movements](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MO_odyssey_plus/MOO_others/MOO13_sudden_movements.zip):
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- [MOO14_flickering_light](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MO_odyssey_plus/MOO_others/MOO14_flickering_light.zip):
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- [MOO15_seated_screen](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MO_odyssey_plus/MOO_others/MOO15_seated_screen.zip):
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- [MOO16_still](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MO_odyssey_plus/MOO_others/MOO16_still.zip):
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## Valve Index datasets These datasets were recorded using a Valve Index with the `vive` driver in Monado and they have ground truth from 3 lighthouses tracking the headset through the proprietary OpenVR implementation provided by SteamVR. The exact commit used in Monado at the time of recording is [a4e7765d](https://gitlab.freedesktop.org/mateosss/monado/-/commit/a4e7765d7219b06a0c801c7bb33f56d3ea69229d). The datasets are in the ASL dataset format, the same as the [EuRoC datasets](https://projects.asl.ethz.ch/datasets/doku.php?id=kmavvisualinertialdatasets). Besides the main EuRoC format files, we provide some extra files with raw timestamp data for exploring real time timestamp alignment techniques. The dataset is post-processed to reduce as much as possible special treatment from SLAM systems: camera-IMU and ground truth-IMU timestamp alignment, IMU alignment and bias calibration have been applied, lighthouse tracked pose has been converted to IMU pose, and so on. Most of the post-processing was done with Basalt [calibration](https://gitlab.com/VladyslavUsenko/basalt/-/blob/master/doc/Calibration.md?ref_type=heads#camera-imu-mocap-calibration) and [alignment](https://gitlab.com/VladyslavUsenko/basalt/-/blob/master/doc/Realsense.md?ref_type=heads#generating-time-aligned-ground-truth) tools, as well as the [xrtslam-metrics](https://gitlab.freedesktop.org/mateosss/xrtslam-metrics) scripts for Monado tracking. The post-processing process is documented in [this video][post-processing-video] which goes through making the [MIPB08] dataset ready for use starting from its raw version. ### Data #### Camera samples In the `vive` driver from Monado, we don't have direct access to the camera device timestamps but only to V4L2 timestamps. These are not exactly hardware timestamps and have some offset with respect to the device clock in which the IMU samples are timestamped. The camera frames can be found in the `camX/data` directory as PNG files with names corresponding to their V4L2 timestamps. The `camX/data.csv` file contains aligned timestamps of each frame. The `camX/data.extra.csv` also contains the original V4L2 timestamp and the "host timestamp" which is the time at which the host computer had the frame ready to use after USB transmission. By separating arrival time and exposure time algorithms can be made to be more robust for real time operation. The cameras of the Valve Index have global shutters with a resolution of 960×960 streaming at 54fps. They have auto exposure enabled. While the cameras of the Index are RGB you will find only grayscale images in these datasets. The original images are provided in YUYV422 format but only the luma component is stored. For each dataset, the camera timestamps are aligned with respect to IMU timestamps by running visual-only odometry with Basalt on a 30-second subset of the dataset. The resulting trajectory is then aligned with the [`basalt_time_alignment`](https://gitlab.com/VladyslavUsenko/basalt/-/blob/master/doc/Realsense.md?ref_type=heads#generating-time-aligned-ground-truth) tool that aligns the rotational velocities of the trajectory with the gyroscope samples and returns the resulting offset in nanoseconds. That correction is then applied to the dataset. Refer to the post-processing walkthrough [video][post-processing-video] for more details. #### IMU samples The IMU timestamps are device timestamps, they come at about 1000Hz. We provide an `imu0/data.raw.csv` file that contains the raw measurements without any axis scale misalignment o bias correction. `imu0/data.csv` has the scale misalignment and bias corrections applied so that the SLAM system can ignore those corrections. `imu0/data.extra.csv` contains the arrival time of the IMU sample to the host computer for algorithms that want to adapt themselves to work in real time. #### Ground truth information The ground truth setup consists of three lighthouses 2.0 base stations and a SteamVR session providing tracking data through the OpenVR API to Monado. While not as precise as other MoCap tracking systems like OptiTrack or Vicon it should still provide pretty good accuracy and precision close to the 1mm range. There are different attempts at studying the accuracy of SteamVR tracking that you can check out like [this](https://dl.acm.org/doi/pdf/10.1145/3463914.3463921), [this](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7956487/pdf/sensors-21-01622.pdf), or [this](http://doc-ok.org/?p=1478). When a tracking system gets closer to millimeter accuracy these datasets will no longer be as useful for improving it. The raw ground truth data is stored in `gt/data.raw.csv`. OpenVR does not provide timestamps and as such, the timestamps recorded are from when the host asks OpenVR for the latest pose with a call to [`GetDeviceToAbsoluteTrackingPose`](https://github.com/ValveSoftware/openvr/wiki/IVRSystem::GetDeviceToAbsoluteTrackingPose). The poses contained in this file are not of the IMU but of the headset origin as interpreted by SteamVR, which usually is between the middle of the eyes and facing towards the displays. The file `gt/data.csv` corrects each entry of the previous file with timestamps aligned with the IMU clock and poses of the IMU instead of this headset origin. #### Calibration There are multiple calibration datasets in the [`MIC_calibration`](https://huggingface.co/datasets/collabora/monado-slam-datasets/tree/main/M_monado_datasets/MI_valve_index/MIC_calibration) directory. There are camera-focused and IMU-focused calibration datasets. See the [README.md](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MI_valve_index/MIC_calibration/README.md) file in there for more information on what each sequence is. In the [`MI_valve_index/extras`](https://huggingface.co/datasets/collabora/monado-slam-datasets/tree/main/M_monado_datasets/MI_valve_index/extras) directory you can find the following files: - [`calibration.json`](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MI_valve_index/extras/calibration.json): Calibration file produced with the [`basalt_calibrate_imu`](https://gitlab.com/VladyslavUsenko/basalt/-/blob/master/doc/Calibration.md?ref_type=heads#camera-imu-mocap-calibration) tool from [`MIC01_camcalib1`](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MI_valve_index/MIC_calibration/MIC01_camcalib1.zip) and [`MIC04_imucalib1`](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MI_valve_index/MIC_calibration/MIC04_imucalib1.zip) datasets with camera-IMU time offset and IMU bias/misalignment info removed so that it works with the fully the all the datasets by default which are fully post-processed and don't require those fields. - [`calibration.extra.json`](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MI_valve_index/extras/calibration.extra.json): Same as `calibration.json` but with the cam-IMU time offset and IMU bias and misalignment information filled in. - [`factory.json`](https://huggingface.co/datasets/collabora/monado-slam-datasets/blob/main/M_monado_datasets/MI_valve_index/extras/factory.json): JSON file exposed by the headset's firmware with information of the device. It includes camera and display calibration as well as more data that might be of interest. It is not used but included for completeness' sake. - [`other_calibrations/`](https://huggingface.co/datasets/collabora/monado-slam-datasets/tree/main/M_monado_datasets/MI_valve_index/extras/other_calibrations): Calibration results obtained from the other calibration datasets. Shown for comparison and ensuring that all of them have similar values. `MICXX_camcalibY` has camera-only calibration produced with the [`basalt_calibrate`](https://gitlab.com/VladyslavUsenko/basalt/-/blob/master/doc/Calibration.md?ref_type=heads#camera-calibration) tool, while the corresponding `MICXX_imucalibY` datasets use these datasets as a starting point and have the `basalt_calibrate_imu` calibration results. ##### Camera model By default, the `calibration.json` file provides parameters `k1`, `k2`, `k3`, and `k4` for the [Kannala-Brandt camera model](https://vladyslavusenko.gitlab.io/basalt-headers/classbasalt_1_1KannalaBrandtCamera4.html#a423a4f1255e9971fe298dc6372345681) with fish-eye distortion (also known as [OpenCV's fish-eye](https://docs.opencv.org/3.4/db/d58/group__calib3d__fisheye.html#details)). Calibrations with other camera models might be added later on, otherwise, you can use the calibration sequences for custom calibrations. ##### IMU model For the default `calibration.json` where all parameters are zero, you can ignore any model and just use the measurements present in `imu0/data.csv` directly. If instead, you want to use the raw measurements from `imu0/data.raw.csv` you will need to apply the Basalt [accelerometer](https://vladyslavusenko.gitlab.io/basalt-headers/classbasalt_1_1CalibAccelBias.html#details) and [gyroscope](https://vladyslavusenko.gitlab.io/basalt-headers/classbasalt_1_1CalibGyroBias.html#details) models that use a misalignment-scale correction matrix together with a constant initial bias. The random walk and white noise parameters were not computed and default reasonable values are used instead. #### Post-processing walkthrough If you are interested in understanding the step-by-step procedure of post-processing of the dataset, below is a video detailing the procedure for the [MIPB08] dataset. [![Post-processing walkthrough video](https://img.youtube.com/vi/0PX_6PNwrvQ/0.jpg)](https://www.youtube.com/watch?v=0PX_6PNwrvQ) ### Sequences - [MIC_calibration](https://huggingface.co/datasets/collabora/monado-slam-datasets/tree/main/M_monado_datasets/MI_valve_index/MIC_calibration): Calibration sequences that record [this](https://drive.google.com/file/d/1DqKWgePodCpAKJCd_Bz-hfiEQOSnn_k0) calibration target from Kalibr with the squares of the target having sides of 3 cm. Some sequences are focused on camera calibration covering the image planes of both stereo cameras while others on IMU calibration properly exciting all six components of the IMU. - [MIP_playing](https://huggingface.co/datasets/collabora/monado-slam-datasets/tree/main/M_monado_datasets/MI_valve_index/MIO_others): Datasets in which the user is playing a particular VR game on SteamVR while Monado records the datasets. - [MIPB_beat_saber](https://huggingface.co/datasets/collabora/monado-slam-datasets/tree/main/M_monado_datasets/MI_valve_index/MIP_playing/MIPB_beat_saber): This contains different songs played at different speeds. The fitbeat song is one that requires a lot of head movement while [MIPB08] is a long 40min dataset with many levels played. - [MIPP_pistol_whip](https://huggingface.co/datasets/collabora/monado-slam-datasets/tree/main/M_monado_datasets/MI_valve_index/MIP_playing/MIPP_pistol_whip): This is a shooting and music game, each dataset is a different level/song. - [MIPT_thrill_of_the_fight](https://huggingface.co/datasets/collabora/monado-slam-datasets/tree/main/M_monado_datasets/MI_valve_index/MIP_playing/MIPT_thrill_of_the_fight): This is a boxing game. - [MIO_others](https://huggingface.co/datasets/collabora/monado-slam-datasets/tree/main/M_monado_datasets/MI_valve_index/MIO_others): These are other datasets that might be useful, they include play-pretend scenarios in which the user is supposed to be playing some particular game, then there is some inspection and scanning/mapping of the room, some very short and lightweight datasets for quick testing, and some datasets with a lot of movement around the environment. ### Evaluation These are the results of running the [current](https://gitlab.freedesktop.org/mateosss/basalt/-/commits/release-b67fa7a4?ref_type=tags) Monado tracker that is based on [Basalt](https://gitlab.com/VladyslavUsenko/basalt) on the dataset sequences. | Seq. | Avg. time\* | Avg. feature count | ATE (m) | RTE 100ms (m) \*\* | SDM 0.01m (m/m) \*\*\* | | :------ | :--------------- | :-------------------- | :---------------- | :---------------------- | :--------------------- | | MIO01 | 10.04 ± 1.43 | [36 23] ± [28 18] | 0.605 ± 0.342 | 0.035671 ± 0.033611 | 0.4246 ± 0.5161 | | MIO02 | 10.41 ± 1.48 | [32 18] ± [25 16] | 1.182 ± 0.623 | 0.063340 ± 0.059176 | 0.4681 ± 0.4329 | | MIO03 | 10.24 ± 1.37 | [47 26] ± [26 16] | 0.087 ± 0.033 | 0.006293 ± 0.004259 | 0.2113 ± 0.2649 | | MIO04 | 9.47 ± 1.08 | [27 16] ± [25 16] | 0.210 ± 0.100 | 0.013121 ± 0.010350 | 0.3086 ± 0.3715 | | MIO05 | 9.95 ± 1.01 | [66 34] ± [33 21] | 0.040 ± 0.016 | 0.003188 ± 0.002192 | 0.1079 ± 0.1521 | | MIO06 | 9.65 ± 1.06 | [44 28] ± [33 22] | 0.049 ± 0.019 | 0.010454 ± 0.008578 | 0.2620 ± 0.3684 | | MIO07 | 9.63 ± 1.16 | [46 26] ± [30 19] | 0.019 ± 0.008 | 0.002442 ± 0.001355 | 0.0738 ± 0.0603 | | MIO08 | 9.74 ± 0.87 | [29 22] ± [18 16] | 0.059 ± 0.021 | 0.007167 ± 0.004657 | 0.1644 ± 0.3433 | | MIO09 | 9.94 ± 0.72 | [44 29] ± [14 8] | 0.006 ± 0.003 | 0.002940 ± 0.002024 | 0.0330 ± 0.0069 | | MIO10 | 9.48 ± 0.82 | [35 21] ± [18 10] | 0.016 ± 0.009 | 0.004623 ± 0.003310 | 0.0620 ± 0.0340 | | MIO11 | 9.34 ± 0.79 | [32 20] ± [19 10] | 0.024 ± 0.010 | 0.007255 ± 0.004821 | 0.0854 ± 0.0540 | | MIO12 | 11.05 ± 2.20 | [43 23] ± [31 19] | 0.420 ± 0.160 | 0.005298 ± 0.003603 | 0.1546 ± 0.2641 | | MIO13 | 10.47 ± 1.89 | [35 21] ± [24 18] | 0.665 ± 0.290 | 0.026294 ± 0.022790 | 1.0180 ± 1.0126 | | MIO14 | 9.27 ± 1.03 | [49 31] ± [30 21] | 0.072 ± 0.028 | 0.002779 ± 0.002487 | 0.1657 ± 0.2409 | | MIO15 | 9.75 ± 1.16 | [52 26] ± [29 16] | 0.788 ± 0.399 | 0.011558 ± 0.010541 | 0.6906 ± 0.6876 | | MIO16 | 9.72 ± 1.26 | [33 17] ± [25 15] | 0.517 ± 0.135 | 0.013268 ± 0.011355 | 0.4397 ± 0.7167 | | MIPB01 | 10.28 ± 1.25 | [63 46] ± [34 24] | 0.282 ± 0.109 | 0.006797 ± 0.004551 | 0.1401 ± 0.1229 | | MIPB02 | 9.88 ± 1.08 | [55 37] ± [30 20] | 0.247 ± 0.097 | 0.005065 ± 0.003514 | 0.1358 ± 0.1389 | | MIPB03 | 10.21 ± 1.12 | [66 44] ± [32 23] | 0.186 ± 0.103 | 0.005938 ± 0.004261 | 0.1978 ± 0.3590 | | MIPB04 | 9.58 ± 1.02 | [51 37] ± [24 17] | 0.105 ± 0.060 | 0.004822 ± 0.003428 | 0.0652 ± 0.0555 | | MIPB05 | 9.97 ± 0.97 | [73 48] ± [32 23] | 0.039 ± 0.017 | 0.004426 ± 0.002828 | 0.0826 ± 0.1313 | | MIPB06 | 9.95 ± 0.85 | [58 35] ± [32 21] | 0.050 ± 0.022 | 0.004164 ± 0.002638 | 0.0549 ± 0.0720 | | MIPB07 | 10.07 ± 1.00 | [73 47] ± [31 20] | 0.064 ± 0.038 | 0.004984 ± 0.003170 | 0.0785 ± 0.1411 | | MIPB08 | 9.97 ± 1.08 | [71 47] ± [36 24] | 0.636 ± 0.272 | 0.004066 ± 0.002556 | 0.0740 ± 0.0897 | | MIPP01 | 10.03 ± 1.21 | [36 22] ± [21 15] | 0.559 ± 0.241 | 0.009227 ± 0.007765 | 0.3472 ± 0.9075 | | MIPP02 | 10.19 ± 1.20 | [42 22] ± [22 15] | 0.257 ± 0.083 | 0.011046 ± 0.010201 | 0.5014 ± 0.7665 | | MIPP03 | 10.13 ± 1.24 | [37 20] ± [23 15] | 0.260 ± 0.101 | 0.008636 ± 0.007166 | 0.3205 ± 0.5786 | | MIPP04 | 9.74 ± 1.09 | [38 23] ± [22 16] | 0.256 ± 0.144 | 0.007847 ± 0.006743 | 0.2586 ± 0.4557 | | MIPP05 | 9.71 ± 0.84 | [37 24] ± [21 15] | 0.193 ± 0.086 | 0.005606 ± 0.004400 | 0.1670 ± 0.2398 | | MIPP06 | 9.92 ± 3.11 | [37 21] ± [21 14] | 0.294 ± 0.136 | 0.009794 ± 0.008873 | 0.4016 ± 0.5648 | | MIPT01 | 10.78 ± 2.06 | [68 44] ± [33 23] | 0.108 ± 0.060 | 0.003995 ± 0.002716 | 0.7109 ± 13.3461 | | MIPT02 | 10.85 ± 1.27 | [79 54] ± [39 28] | 0.198 ± 0.109 | 0.003709 ± 0.002348 | 0.0839 ± 0.1175 | | MIPT03 | 10.80 ± 1.55 | [76 52] ± [42 30] | 0.401 ± 0.206 | 0.005623 ± 0.003694 | 0.1363 ± 0.1789 | | **AVG** | **11.33 ± 1.83** | **[49 23] ± [37 15]** | **0.192 ± 0.090** | **0.009439 ± 0.007998** | **0.3247 ± 0.6130** | | Seq. | Avg. time\* | Avg. feature count | ATE (m) | RTE 100ms (m) \*\* | SDM 0.01m (m/m) \*\*\* | | :------ | :--------------- | :-------------------- | :---------------- | :---------------------- | :--------------------- | | MGO01 | 12.06 ± 2.10 | [19 16] ± [13 12] | 0.680 ± 0.249 | 0.022959 ± 0.019026 | 0.3604 ± 1.3031 | | MGO02 | 11.20 ± 1.83 | [19 15] ± [19 16] | 0.556 ± 0.241 | 0.027931 ± 0.019074 | 0.3218 ± 0.4599 | | MGO03 | 9.88 ± 1.92 | [22 16] ± [16 16] | 0.145 ± 0.041 | 0.013003 ± 0.008555 | 0.2433 ± 0.3512 | | MGO04 | 9.43 ± 1.45 | [16 14] ± [16 16] | 0.261 ± 0.113 | 0.024674 ± 0.017380 | 0.3609 ± 0.4829 | | MGO05 | 9.93 ± 1.71 | [39 40] ± [17 26] | 0.030 ± 0.011 | 0.004212 ± 0.002632 | 0.0621 ± 0.1044 | | MGO06 | 10.40 ± 1.84 | [24 22] ± [18 18] | 0.111 ± 0.038 | 0.018013 ± 0.011398 | 0.2496 ± 0.2802 | | MGO07 | 9.74 ± 1.54 | [30 24] ± [13 12] | 0.021 ± 0.010 | 0.005628 ± 0.003707 | 0.0992 ± 0.1538 | | MGO08 | 9.42 ± 1.43 | [17 13] ± [11 8] | 0.027 ± 0.015 | 0.013162 ± 0.009729 | 0.1667 ± 0.4068 | | MGO09 | 10.90 ± 1.70 | [39 34] ± [11 9] | 0.008 ± 0.004 | 0.006278 ± 0.004054 | 0.0738 ± 0.0492 | | MGO10 | 9.31 ± 1.36 | [29 37] ± [14 17] | 0.008 ± 0.003 | 0.003496 ± 0.002333 | 0.0439 ± 0.0311 | | MGO11 | 9.26 ± 1.08 | [30 22] ± [13 17] | 0.017 ± 0.006 | 0.006065 ± 0.004285 | 0.0687 ± 0.0604 | | MGO12 | 9.33 ± 1.39 | [20 19] ± [17 19] | 0.610 ± 0.270 | 0.017372 ± 0.016246 | 0.7225 ± 10.7366 | | MGO13 | 10.08 ± 1.98 | [18 17] ± [16 17] | 0.683 ± 0.211 | 0.025764 ± 0.017900 | 0.2542 ± 0.3324 | | MGO14 | 10.00 ± 1.83 | [29 25] ± [17 21] | 0.070 ± 0.025 | 0.012013 ± 0.007674 | 0.1417 ± 0.1850 | | MGO15 | 9.07 ± 1.39 | [9 7] ± [10 7] | 0.037 ± 0.016 | 0.003737 ± 0.003425 | 0.7053 ± 4.3405 | | **AVG** | **10.00 ± 1.64** | **[24 21] ± [15 15]** | **0.218 ± 0.084** | **0.013620 ± 0.009828** | **0.2583 ± 1.2852** | | Seq. | Avg. time\* | Avg. feature count | ATE (m) | RTE 100ms (m) \*\* | SDM 0.01m (m/m) \*\*\* | | :------ | :--------------- | :-------------------- | :---------------- | :---------------------- | :--------------------- | | MOO01 | 7.58 ± 1.55 | [30 23] ± [21 20] | 0.281 ± 0.131 | 0.016662 ± 0.010451 | 0.2358 ± 0.3848 | | MOO02 | 6.89 ± 1.65 | [27 21] ± [24 25] | 0.237 ± 0.101 | 0.015469 ± 0.009201 | 0.1710 ± 0.2281 | | MOO03 | 7.33 ± 1.77 | [30 26] ± [21 24] | 0.177 ± 0.088 | 0.013521 ± 0.009276 | 0.2610 ± 0.6376 | | MOO04 | 6.11 ± 1.35 | [22 14] ± [20 16] | 0.065 ± 0.026 | 0.009849 ± 0.005401 | 0.0889 ± 0.1166 | | MOO05 | 7.04 ± 1.54 | [53 46] ± [20 30] | 0.018 ± 0.007 | 0.003070 ± 0.001838 | 0.0284 ± 0.0181 | | MOO06 | 6.66 ± 1.58 | [38 35] ± [21 27] | 0.056 ± 0.028 | 0.008395 ± 0.005154 | 0.0847 ± 0.1033 | | MOO07 | 6.38 ± 1.71 | [43 31] ± [16 21] | 0.013 ± 0.006 | 0.003422 ± 0.002073 | 0.0317 ± 0.0326 | | MOO08 | 7.17 ± 1.65 | [25 19] ± [19 15] | 0.028 ± 0.015 | 0.011164 ± 0.006958 | 0.0939 ± 0.1051 | | MOO09 | 8.31 ± 1.84 | [43 38] ± [19 17] | 0.004 ± 0.002 | 0.003284 ± 0.002181 | 0.0063 ± 0.0000 | | MOO10 | 6.94 ± 1.43 | [38 21] ± [18 15] | 0.010 ± 0.005 | 0.003765 ± 0.002338 | 0.0440 ± 0.0232 | | MOO11 | 6.66 ± 1.57 | [32 32] ± [18 22] | 0.019 ± 0.010 | 0.005102 ± 0.003253 | 0.0433 ± 0.0356 | | MOO12 | 5.78 ± 1.40 | [32 34] ± [21 26] | 0.694 ± 0.329 | 0.008292 ± 0.007220 | 0.1275 ± 0.2512 | | MOO13 | 6.12 ± 1.60 | [21 16] ± [22 19] | 0.501 ± 0.188 | 0.017042 ± 0.010342 | 0.1448 ± 0.1551 | | MOO14 | 7.07 ± 1.32 | [26 19] ± [17 16] | 0.113 ± 0.058 | 0.007743 ± 0.004316 | 0.1130 ± 0.1661 | | MOO15 | 6.51 ± 1.70 | [20 11] ± [15 6] | 0.629 ± 0.312 | 0.015308 ± 0.014007 | 0.7254 ± 0.3257 | | MOO16 | 5.21 ± 1.08 | [23 28] ± [6 8] | 0.046 ± 0.022 | 0.001441 ± 0.001238 | 0.1750 ± 0.1788 | | **AVG** | **6.74 ± 1.55** | **[31 26] ± [19 19]** | **0.181 ± 0.083** | **0.008971 ± 0.005953** | **0.1484 ± 0.1726** | - \*: Average frame time. On an AMD Ryzen 7 5800X CPU. Run with pipeline fully saturated. Real time operation frame times should be slightly lower. - \*\*: RTE using delta of 6 frames (11ms) - \*\*\*: The SDM metric is similar to RTE, it represents distance in meters drifted for each meter of the dataset. The metric is implemented in the [xrtslam-metrics](https://gitlab.freedesktop.org/mateosss/xrtslam-metrics) project. ## License This work is licensed under a Creative Commons Attribution 4.0 International License. Creative Commons License [post-processing-video]: https://youtu.be/0PX_6PNwrvQ [MIPB08]: https://huggingface.co/datasets/collabora/monado-slam-datasets/tree/main/M_monado_datasets/MI_valve_index/MIP_playing/MIPB_beat_saber