PennCOSYVIO: A challenging Visual Inertial Odometry benchmark
Bernd Pfrommer, Nitin Sanket, Kostas Daniilidis, Jonas Cleveland
Abstract
We present PennCOSYVIO, a new challenging Visual Inertial Odometry (VIO) benchmark with synchronized data from a VI-sensor (stereo camera and IMU), two Project Tango hand-held devices, and three GoPro Hero 4 cameras. Recorded at UPenn's Singh center, the 150m long path of the hand-held rig crosses from outdoors to indoors and includes rapid rotations, thereby testing the abilities of VIO and Simultaneous Localization and Mapping (SLAM) algorithms to handle changes in lighting, different textures, repetitive structures, and large glass surfaces. All sensors are synchronized and intrinsically and extrinsically calibrated. We demonstrate the accuracy with which ground-truth poses can be obtained via optic localization off of fiducial markers. The data set can be found at https://daniilidis-group.github.io/penncosyvio/.
BibTeX
@inproceedings{icra2017_penncosyvioachal,
title = {PennCOSYVIO: A challenging Visual Inertial Odometry benchmark},
author = {Bernd Pfrommer and Nitin Sanket and Kostas Daniilidis and Jonas Cleveland},
booktitle = {ICRA 2017},
year = {2017}
}