iMAP: implicit mapping and positioning in real-time
File(s)
Accepted version
Author(s)
Sucar, Edgar
Liu, Shikun
Ortiz, Joseph
Davison, Andrew J
Type
Conference Paper
Abstract
We show for the first time that a multilayer perceptron (MLP) can serve as the only scene representation in a real-time SLAM system for a handheld RGB-D camera. Our network is trained in live operation without prior data, building a dense, scene-specific implicit 3D model of occupancy and colour which is also immediately used for tracking.Achieving real-time SLAM via continual training of a neural network against a live image stream requires significant innovation. Our iMAP algorithm uses a keyframe structure and multi-processing computation flow, with dynamic information-guided pixel sampling for speed, with tracking at 10 Hz and global map updating at 2 Hz. The advantages of an implicit MLP over standard dense SLAM techniques include efficient geometry representation with automatic detail control and smooth, plausible filling-in of unobserved regions such as the back surfaces of objects.
Date Issued
2022-02-28
Date Acceptance
2022-02-01
Citation
2021 IEEE/CVF International Conference on Computer Vision (ICCV), 2022, pp.6209-6218
Publisher
IEEE
Start Page
6209
End Page
6218
Journal / Book Title
2021 IEEE/CVF International Conference on Computer Vision (ICCV)
Copyright Statement
© 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Sponsor
Dyson Technology Limited
Engineering & Physical Science Research Council (EPSRC)
Identifier
https://ieeexplore.ieee.org/document/9710431
Grant Number
PO 4500501004
EP/S036636/1
Source
2021 IEEE/CVF International Conference on Computer Vision (ICCV)
Publication Status
Published
Start Date
2021-10-10
Finish Date
2021-10-17
Coverage Spatial
Montreal, QC, Canada
Date Publish Online
2022-02-28