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OPT-PCC SIGNED

Optimized Dynamic Point Cloud Compression

Total Cost €

0

EC-Contrib. €

0

Partnership

0

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Project "OPT-PCC" data sheet

The following table provides information about the project.

Coordinator
DE MONTFORT UNIVERSITY 

Organization address
address: THE GATEWAY
city: LEICESTER
postcode: LE1 9BH
website: www.dmu.ac.uk

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country United Kingdom [UK]
 Total cost 112˙466 €
 EC max contribution 112˙466 € (100%)
 Programme 1. H2020-EU.1.3.2. (Nurturing excellence by means of cross-border and cross-sector mobility)
 Code Call H2020-MSCA-IF-2018
 Funding Scheme MSCA-IF-EF-ST
 Starting year 2020
 Duration (year-month-day) from 2020-07-01   to  2021-06-30

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    DE MONTFORT UNIVERSITY UK (LEICESTER) coordinator 112˙466.00

Map

 Project objective

3D point clouds are receiving increased attention due to their potential for many important applications, such as real-time 3D immersive telepresence. Compared to traditional video technology, 3D point cloud systems allow free viewpoint rendering, as well as mixing of natural and synthetic objects. However, this improved user experience comes at the cost of increased storage and bandwidth requirements as point clouds are typically represented by the geometry and colour of millions up to billions of 3D points. For this reason, major efforts are being made to develop efficient point cloud compression schemes. The task, however, is very challenging due to the irregular structure of point clouds. To standardize these efforts, the Moving Picture Experts Group (MPEG) launched in January 2017 a call for proposals for 3D point cloud compression technology. In October 2017, the responses were evaluated and the first test model for lossy compression of dynamic point clouds (TMC2) was established. This test model defines a first “common core” algorithm for collaborative work towards the final standard. The aim of OPT-PCC is to contribute to these efforts by developing algorithms that optimize the rate-distortion performance of the test model. OPT-PCC’s objectives are to:

1. O1: build analytical models that accurately describe the effect of the geometry and colour quantization of a 3D point cloud on the bit rate and distortion; 2. O2: develop fast search algorithms that optimize the allocation of the available bit budget between the geometry information and colour information; 3. O3: implement a compression scheme for dynamic 3D point clouds that outperforms the state-of-the-art in terms of rate-distortion performance. The target is to reduce the bit rate by at least 20% for the same reconstruction quality; 4. O4: provide multi-disciplinary training to the researcher in algorithm design, metaheuristic optimisation, computer graphics, and leadership and management skills.

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The information about "OPT-PCC" are provided by the European Opendata Portal: CORDIS opendata.

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