RedTag: automatic content metadata capture for cameras

Tom Bartindale, Daniel Jackson, Karim Ladha, Sebastian Mellor, Patrick Olivier, Peter Wright

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearch

3 Citations (Scopus)

Abstract

RedTag is an optical tagging system that provides time based identification of objects, people or devices via small low cost infrared transmitters and receivers. We have developed RedTag as a cheap and flexible method of augmenting existing video capture equipment with an additional temporal metadata output of content based information. In this note, we describe the technology behind RedTag and demonstrate the interaction opportunities that arise through access to temporal metadata.

Original languageEnglish
Title of host publicationTVX’14 - Proceedings of the 2014 ACM International Conference on Interactive Experiences for TV and Online Video
Subtitle of host publicationJune 25-27, 2014 Newcastle Upon Tyne, UK
EditorsMarianna Obrist, Pablo Cesar, Santosh Basapur
Place of PublicationNew York NY USA
PublisherAssociation for Computing Machinery (ACM)
Pages19-22
Number of pages4
ISBN (Electronic)9781450328388
DOIs
Publication statusPublished - 2014
Externally publishedYes
EventACM International Conference on Interactive Experiences for TV and Online Video 2014 - Newcastle Upon Tyne, United Kingdom
Duration: 25 Jun 201427 Jun 2014
http://tvx.acm.org/2014/index.html

Conference

ConferenceACM International Conference on Interactive Experiences for TV and Online Video 2014
Abbreviated titleTVX 2014
CountryUnited Kingdom
CityNewcastle Upon Tyne
Period25/06/1427/06/14
Internet address

Keywords

  • DTMF
  • Editing
  • Electronics
  • Film
  • Infrared
  • Metadata
  • Production

Cite this

Bartindale, T., Jackson, D., Ladha, K., Mellor, S., Olivier, P., & Wright, P. (2014). RedTag: automatic content metadata capture for cameras. In M. Obrist, P. Cesar, & S. Basapur (Eds.), TVX’14 - Proceedings of the 2014 ACM International Conference on Interactive Experiences for TV and Online Video: June 25-27, 2014 Newcastle Upon Tyne, UK (pp. 19-22). Association for Computing Machinery (ACM). https://doi.org/10.1145/2602299.2602303