Transformative technology and demonstrator for immersive and naturalistic video communication
Lead Participant:
POMMELHORSE LTD
Abstract
It is well understood that when communicating with others, only 50% of the information we share lies in the words and our tone, and the rest in visual cues such as gaze, body language and our expressions. Video communication today falls significantly short in capturing and communicating these visual cues and hence typically falls short when considered as an alternative to meeting face-to-face, especially for more important and critical communications. This is often due to the non-real feeling of video communication, and poor perspective of view.
The project involves research, exploration and development of a technology that enables significant improvements to the experience of video communication, by performing real-time manipulation of video streams, that helps capture and communicate these visual cues. The project aims to realise this in a mass market way and have a meaningful impact to all users of video communication. This enables the transition of more face-to-face interactions to digital ones, and in turn reduce the need for unnecessary travel, positively impacting global carbon reduction targets, and help more people achieve greater economic impact without having to co-locate in overpopulated cities. This will be a significant economic benefit to the UK and internationally.
The majority of the project work focuses on deep technology and algorithmic development, pushing the state-of-the-art in machine learning based real-time signal processing.
The project involves research, exploration and development of a technology that enables significant improvements to the experience of video communication, by performing real-time manipulation of video streams, that helps capture and communicate these visual cues. The project aims to realise this in a mass market way and have a meaningful impact to all users of video communication. This enables the transition of more face-to-face interactions to digital ones, and in turn reduce the need for unnecessary travel, positively impacting global carbon reduction targets, and help more people achieve greater economic impact without having to co-locate in overpopulated cities. This will be a significant economic benefit to the UK and internationally.
The majority of the project work focuses on deep technology and algorithmic development, pushing the state-of-the-art in machine learning based real-time signal processing.
Lead Participant | Project Cost | Grant Offer |
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Participant |
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POMMELHORSE LTD |
People |
ORCID iD |
Martin Lind (Project Manager) |