List of Datasets

Handheld

Newer College

Handheld visual-inertial and LiDAR localization

Original handheld stereo-infrared, OS1-64 lidar and dual-IMU campus collection with surveyed-map trajectory references and five motion recordings. The later multicamera collection is separate.

Metadata: Complete Metadata curator reviewed Released 2020

Primary places to inspect, download, read about, or reproduce the dataset.

Quick facts

Vehicle type
Handheld
Environment
Outdoor
Data origin
Real-world
Sensor count
5
Ground truth
Available
Calibration
Partial Raw Data
Annotations
Not reported

Sensor overview

High-level sensor availability before the detailed sensor records below.

Cameras

2 reported

IMUs

2 reported

GNSS

Not reported

LiDAR

1 reported

Magnetometers

Not reported

Barometers

Not reported

UWB

Not reported

Ground truth

Reference scope, method, rate, coverage, and provenance.

Scope Method Reference system Count Rate Coverage Reference provenance
External
Measured using equipment independent of the platform’s normal onboard sensor pipeline.
Derived
Computed primarily from the dataset’s own recorded sensors.
Hybrid
Combines independent reference equipment with onboard measurements.
6DoF Other Leica surveyed map with ICP · Leica BLK360 Not reported Not reported Full Reference provenance
External
Measured using equipment independent of the platform’s normal onboard sensor pipeline.
Derived
Computed primarily from the dataset’s own recorded sensors.
Hybrid
Combines independent reference equipment with onboard measurements.
Hybrid
Accuracy and notes
Accuracy notes
Approximately 3 cm overall is stationary dispersion for ten seconds only; dynamic trajectory accuracy is not independently quantified.
Reference notes
Recorded lidar scans registered to an independently surveyed prior map; left-camera base frame. Interpolated camera poses at 30 Hz are the same reference process, not a second independent source.

Calibration and synchronization

Reported calibration level, reproducibility signals, and supporting notes.

Level
Partial Raw Data
Processed parameters
Available
Raw calibration data
Available
Calibration targets
Aprilgrid

Reproducible calibration data

Raw calibration data is reported, so users can reproduce or inspect the calibration process.

Notes

Kalibr camera/dual-IMU spatial and temporal parameters and calibration bags are supplied. The Ouster lidar is covered during camera/IMU calibration, so complete raw calibration for every sensor pairing is not established.

Known or intentional limitations

Reported constraints and characteristics to check before using the dataset.

Dynamic trajectory accuracy is not independently quantified; stationary dispersion is not a moving-trajectory error bound.

Camera timestamps require the supplied temporal-offset correction.

Aggregate duration and distance are not stated for all five motion recordings.

Access requires the official request form; data use is governed by CC BY-NC-SA 4.0.

Cameras

Camera 1

Model
Intel RealSense D435i
Setup
Stereo
Count
1
Effective cameras
2
Modality
Nir
Resolution
848 x 480
Rate
30 Hz
Shutter
Global
Lens type
Not Reported
HFOV
Not reported
VFOV
Not reported
Notes
Released imagery is infrared stereo; RGB/depth capability is not taken as a release claim.

IMUs

Ouster integrated IMU

Model
ICM-20948
Count
1
Accel / gyro
100 / 100 Hz

RealSense integrated IMU

Model
Bosch BMI055
Count
1
Accel / gyro
250 / 400 Hz

GNSS

Not reported

LiDAR

Ouster OS1-64

Model or name
Ouster OS1-64
Count
1
Dimensions
3
Rate
10 Hz
Channels
64
Range
120 m

Additional sensors

Not reported

Annotations

Reported annotation availability and task support.

Availability
Not reported
Format
Not reported
Class count
Not reported
Semantic segmentation Not reported
Instance segmentation Not reported
Object detection Not reported
Optical flow Not reported
Depth ground truth Not reported

Citation

Citation key and BibTeX kept at the end of the page for reference.

Citation key
ramezani-2022-newer-college-v2

BibTeX

@misc{ramezani-2022-newer-college-v2,
  title = {The Newer College Dataset: Handheld LiDAR, Inertial and Vision with Ground Truth},
  author = {Milad Ramezani and Yiduo Wang and Marco Camurri and David Wisth and Matias Mattamala and Maurice Fallon},
  year = {2022},
  eprint = {2003.05691v2},
  archivePrefix = {arXiv}
}

Dataset corrections

Notice a specific issue after reviewing the page?

Report an inaccuracy