Update readme

M_monado_datasets/MG_reverb_g2/README.md

@@ -0,0 +1 @@
+To be done.

M_monado_datasets/MI_valve_index/README.md

@@ -0,0 +1,251 @@
+## 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)
+
+### 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.

M_monado_datasets/MO_odyssey_plus/README.md

@@ -0,0 +1 @@
+To be done.