Skip to main content
We gratefully acknowledge support from the Simons Foundation, member institutions, and all contributors. Donate
arXiv logo
Cornell University Logo

Computer Science > Robotics

arXiv:2108.08494 (cs)
[Submitted on 19 Aug 2021]

Title:Towards a Multispectral RGB-IR-UV-D Vision System -- Seeing the Invisible in 3D

Authors:Tanhao Zhang, Luyin Hu, Lu Li, David Navarro-Alarcon
View PDF
Abstract:In this paper, we present the development of a sensing system with the capability to compute multispectral point clouds in real-time. The proposed multi-eye sensor system effectively registers information from the visible, (long-wave) infrared, and ultraviolet spectrum to its depth sensing frame, thus enabling to measure a wider range of surface features that are otherwise hidden to the naked eye. For that, we designed a new cross-calibration apparatus that produces consistent features which can be sensed by each of the cameras, therefore, acting as a multispectral "chessboard". The performance of the sensor is evaluated with two different cases of studies, where we show that the proposed system can detect "hidden" features of a 3D environment.
Subjects: Robotics (cs.RO); Systems and Control (eess.SY)
Cite as: arXiv:2108.08494 [cs.RO]
  (or arXiv:2108.08494v1 [cs.RO] for this version)
  https://doi.org/10.48550/arXiv.2108.08494

Submission history

From: David Navarro-Alarcon [view email]
[v1] Thu, 19 Aug 2021 04:36:50 UTC (12,718 KB)
Full-text links:

Access Paper:

  • View PDF
  • TeX Source
  • Other Formats
license icon view license
Current browse context:
cs.RO
< prev   |   next >
new | recent | 2021-08
Change to browse by:
cs
cs.SY
eess
eess.SY

References & Citations

DBLP - CS Bibliography

listing | bibtex
Lu Li
David Navarro-Alarcon
export BibTeX citation

Bookmark

BibSonomy logo Reddit logo

Bibliographic and Citation Tools

Bibliographic Explorer (What is the Explorer?)
Connected Papers (What is Connected Papers?)
Litmaps (What is Litmaps?)
scite Smart Citations (What are Smart Citations?)

Code, Data and Media Associated with this Article

alphaXiv (What is alphaXiv?)
CatalyzeX Code Finder for Papers (What is CatalyzeX?)
DagsHub (What is DagsHub?)
Gotit.pub (What is GotitPub?)
Hugging Face (What is Huggingface?)
Papers with Code (What is Papers with Code?)
ScienceCast (What is ScienceCast?)

Demos

Replicate (What is Replicate?)
Hugging Face Spaces (What is Spaces?)
TXYZ.AI (What is TXYZ.AI?)

Recommenders and Search Tools

Influence Flower (What are Influence Flowers?)
CORE Recommender (What is CORE?)

arXivLabs: experimental projects with community collaborators

arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.

Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.

Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.

Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)