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CrowdAR: augmenting live video with a real-time crowd

CrowdAR: augmenting live video with a real-time crowd
CrowdAR: augmenting live video with a real-time crowd
Finding and tracking targets and events in a live video feed is important for
many commercial applications, from CCTV surveillance used by police and security
firms, to the rapid mapping of events from aerial imagery.
However, descriptions of targets are typically provided in natural language by
the end users, and interpreting these in the context of a live video stream is a
complex task. Due to current limitations in artificial intelligence, especially
vision, this task cannot be automated and instead requires human supervision.
Hence, in this paper, we consider the use of real-time crowdsourcing to identify
and track targets given by a natural language description. In particular we
present a novel method for augmenting live video with a real-time crowd.
169-177
Salisbury, Elliot
3573f86f-8305-4850-b911-41fdf896e946
Stein, Sebastian
cb2325e7-5e63-475e-8a69-9db2dfbdb00b
Ramchurn, Sarvapali
1d62ae2a-a498-444e-912d-a6082d3aaea3
Salisbury, Elliot
3573f86f-8305-4850-b911-41fdf896e946
Stein, Sebastian
cb2325e7-5e63-475e-8a69-9db2dfbdb00b
Ramchurn, Sarvapali
1d62ae2a-a498-444e-912d-a6082d3aaea3

Salisbury, Elliot, Stein, Sebastian and Ramchurn, Sarvapali (2015) CrowdAR: augmenting live video with a real-time crowd. HCOMP 2015: Third AAAI Conference on Human Computation and Crowdsourcing, San Diego, United States. 08 - 11 Nov 2015. pp. 169-177 .

Record type: Conference or Workshop Item (Paper)

Abstract

Finding and tracking targets and events in a live video feed is important for
many commercial applications, from CCTV surveillance used by police and security
firms, to the rapid mapping of events from aerial imagery.
However, descriptions of targets are typically provided in natural language by
the end users, and interpreting these in the context of a live video stream is a
complex task. Due to current limitations in artificial intelligence, especially
vision, this task cannot be automated and instead requires human supervision.
Hence, in this paper, we consider the use of real-time crowdsourcing to identify
and track targets given by a natural language description. In particular we
present a novel method for augmenting live video with a real-time crowd.

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salisbury_hcomp2015.pdf - Author's Original
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More information

Published date: 8 November 2015
Venue - Dates: HCOMP 2015: Third AAAI Conference on Human Computation and Crowdsourcing, San Diego, United States, 2015-11-08 - 2015-11-11
Organisations: Agents, Interactions & Complexity
Learn more about Agents, Interactions & Complexity research

Identifiers

Local EPrints ID: 382948
URI: http://eprints.soton.ac.uk/id/eprint/382948
PURE UUID: 1197b42f-d45f-4256-8edf-a1fc6f9b3b41
ORCID for Sebastian Stein: ORCID iD orcid.org/0000-0003-2858-8857
ORCID for Sarvapali Ramchurn: ORCID iD orcid.org/0000-0001-9686-4302

Catalogue record

Date deposited: 29 Oct 2015 11:31
Last modified: 15 Mar 2024 03:30

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Contributors

Author: Elliot Salisbury
Author: Sebastian Stein ORCID iD
Author: Sarvapali Ramchurn ORCID iD

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