The Newer College Dataset is a large dataset with a variety of mobile mapping sensors collected using a handheld device carried at typical walking speeds for nearly 2.2 km through New College, Oxford. The dataset includes data from two commercially available devices - a stereoscopic-inertial camera and a multi-beam 3D LiDAR, which also provides inertial measurements. Additionally, the authors used a tripod-mounted survey grade LiDAR scanner to capture a detailed millimeter-accurate 3D map of the test location (containing ∼290 million points).

Using the map the authors inferred centimeter-accurate 6 Degree of Freedom (DoF) ground truth for the position of the device for each LiDAR scan to enable better evaluation of LiDAR and vision localisation, mapping and reconstruction systems. The dataset combines both built environments, open spaces and vegetated areas so as to test localization and mapping systems such as vision-based navigation, visual and LiDAR SLAM, 3D LIDAR reconstruction and appearance-based place recognition.

We present The Newer College Dataset with a variety of mobile mapping sensors handcarried at typical walking speeds through New College, Oxford for nearly 6.7 km. The dataset uses two different devices made up of commercially available sensors. These datasets contain some challenging sequences such as fast motion, aggressive shaking, rapid lighting change, and textureless surface.

Stereo Vision Lidar IMU dataset (Original, March 2020):

Intel Realsense D435i - a stereoscopic-inertial camera Ouster OS-1 (Gen 1) 64 - a 64 multi-beam 3D LiDAR also with an IMU Multicam Vision Lidar IMU dataset (Extension, December 2021):

Sevensense Alphasense Core - a 4-camera visual inertial camera Ouster OS-0 128 - a 128 multi-beam 3D LiDAR also with an IMU Both datasets are paired with precise centimetre accurate ground truth for the motion of the sensor rig.

We present The Newer College Dataset with a variety of mobile mapping sensors handcarried at typical walking speeds through New College, Oxford for nearly 6.7 km. The dataset uses two different devices made up of commercially available sensors. These datasets contain some challenging sequences such as fast motion, aggressive shaking, rapid lighting change, and textureless surface.