VECtor: A Versatile Event-Centric Benchmark for Multi-Sensor SLAM

Event cameras have recently gained in popularity as they hold strong potential to complement regular cameras in situations of high dynamics or challenging illumination. An important problem that may benefit from the addition of an event camera is given by Simultaneous Localization And Mapping (SLAM)...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:IEEE robotics and automation letters Ročník 7; číslo 3; s. 1 - 8
Hlavní autoři: Gao, Ling, Liang, Yuxuan, Yang, Jiaqi, Wu, Shaoxun, Wang, Chenyu, Chen, Jiaben, Kneip, Laurent
Médium: Journal Article
Jazyk:angličtina
Vydáno: Piscataway IEEE 01.07.2022
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Benchmark testing
Benchmarks
Cameras
Data Sets for Robot Learning
Data Sets for Robotic Vision
Data Sets for SLAM
Inertial platforms
Inertial sensing devices
Laser radar
Motion capture
Robot vision systems
Sensor Fusion
Sensors
Sequences
Simultaneous localization and mapping
Synchronization
ISSN:2377-3766, 2377-3766
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí:Event cameras have recently gained in popularity as they hold strong potential to complement regular cameras in situations of high dynamics or challenging illumination. An important problem that may benefit from the addition of an event camera is given by Simultaneous Localization And Mapping (SLAM). However, in order to ensure progress on event-inclusive multi-sensor SLAM, novel benchmark sequences are needed. Our contribution is the first complete set of benchmark datasets captured with a multi-sensor setup containing an event-based stereo camera, a regular stereo camera, multiple depth sensors, and an inertial measurement unit. The setup is fully hardware-synchronized and underwent accurate extrinsic calibration. All sequences come with ground truth data captured by highly accurate external reference devices such as a motion capture system. Individual sequences include both small and large-scale environments, and cover the specific challenges targeted by dynamic vision sensors.
Bibliografie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:2377-3766
2377-3766
DOI:10.1109/LRA.2022.3186770