kth.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Event-Based Vision: A Survey
Tech Univ Berlin, D-10623 Berlin, Germany.;Einstein Ctr Digital Future, D-10117 Berlin, Germany..
Swiss Fed Inst Technol, Dept Informat Technol & Elect Engn, CH-8092 Zurich, Switzerland.;Univ Zurich, Inst Neuroinformat, CH-8057 Zurich, Switzerland.;Swiss Fed Inst Technol, CH-8057 Zurich, Switzerland..ORCID iD: 0000-0001-5479-1141
Intel Labs, Santa Clara, CA 95054 USA..
Ist Italiano Tecnol, I-16163 Genoa, Italy..
Show others and affiliations
2022 (English)In: IEEE Transactions on Pattern Analysis and Machine Intelligence, ISSN 0162-8828, E-ISSN 1939-3539, Vol. 44, no 1, p. 154-180Article in journal (Refereed) Published
Abstract [en]

Event cameras are bio-inspired sensors that differ from conventional frame cameras: Instead of capturing images at a fixed rate, they asynchronously measure per-pixel brightness changes, and output a stream of events that encode the time, location and sign of the brightness changes. Event cameras offer attractive properties compared to traditional cameras: high temporal resolution (in the order of mu s), very high dynamic range (140 dB versus 60 dB), low power consumption, and high pixel bandwidth (on the order of kHz) resulting in reduced motion blur. Hence, event cameras have a large potential for robotics and computer vision in challenging scenarios for traditional cameras, such as low-latency, high speed, and high dynamic range. However, novel methods are required to process the unconventional output of these sensors in order to unlock their potential. This paper provides a comprehensive overview of the emerging field of event-based vision, with a focus on the applications and the algorithms developed to unlock the outstanding properties of event cameras. We present event cameras from their working principle, the actual sensors that are available and the tasks that they have been used for, from low-level vision (feature detection and tracking, optic flow, etc.) to high-level vision (reconstruction, segmentation, recognition). We also discuss the techniques developed to process events, including learning-based techniques, as well as specialized processors for these novel sensors, such as spiking neural networks. Additionally, we highlight the challenges that remain to be tackled and the opportunities that lie ahead in the search for a more efficient, bio-inspired way for machines to perceive and interact with the world.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE) , 2022. Vol. 44, no 1, p. 154-180
Keywords [en]
Event cameras, bio-inspired vision, asynchronous sensor, low latency, high dynamic range, low power
National Category
Computer graphics and computer vision
Identifiers
URN: urn:nbn:se:kth:diva-306815DOI: 10.1109/TPAMI.2020.3008413ISI: 000728561300013PubMedID: 32750812Scopus ID: 2-s2.0-85122414075OAI: oai:DiVA.org:kth-306815DiVA, id: diva2:1627031
Note

QC 20220112

Available from: 2022-01-12 Created: 2022-01-12 Last updated: 2025-02-07Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textPubMedScopus

Authority records

Conradt, Jörg

Search in DiVA

By author/editor
Delbruck, TobiConradt, JörgDaniilidis, Kostas
By organisation
Computational Science and Technology (CST)
In the same journal
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computer graphics and computer vision

Search outside of DiVA

GoogleGoogle Scholar

doi
pubmed
urn-nbn

Altmetric score

doi
pubmed
urn-nbn
Total: 135 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf