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Company profile

Vision Semantics Limited

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Veritone Tracker enables investigators to track individuals across videos, helping teams find persons of interest (POI) across multiple...

CRN
04088646
Founded
2000
Age
25

Overview

Browse spinouts
Legal name
VISION SEMANTICS LIMITED
Region
Unknown
Registered address
Unknown
Insolvency history
No

Company events

Reference milestones and recent Companies House filing stream events.

2 events
30 Oct
2024

Liquidation Voluntary Members Return Of Final Meeting

Insolvency

LIQ13 | Transaction MzQ0MDYzNzc0MWFkaXF6a2N4 | Paper/PDF filed

Published 31 Oct 2024 07:57

12 Oct
2000

Incorporated

Inception

Company registered at Companies House

Spinout profile

3 entries

Company description

Vision Semantics Ltd is a spin-out company of Queen Mary University of London, developing self-configuring video analysis and dynamic scene understanding tools & applications that employ innovative learning and statistical methods.

Vision Semantics develops software that analyses CCTV footage uses statistical methods to identify relevant security footage from a large quantity of videos and images.

Project impact

Five patents granted and pending, a joint venture start-up in the Far East (2012), a world-wide licensing for setting up another start-up (2014).

Vision Semantics Ltd
2007
Vision Semantics
2000
Vision Semantics
2000

Public funding

1 award
First funded
2018
Funded years
2018
Age at first award
17 years

Projects

2018 Collaborative R&D Lead participant

Developing and Commercialising Intelligent Video Analytics Solutions for Public Safety

1 Feb 2018 to 31 Jan 2020

Awarded
£348,045
Total cost £499,750

Effective automatic intelligent video analysis of large scale data from public spaces is an important tool in the fight against crime and for safeguarding public safety. Yet, it is challenging to extract critical information from very large scale unstructured surveillance videos with a very high ratio of mundane data subject to severe visual ambiguity and...

Product types

Collaborative R&D