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Grant: Collaborative Research and Development Grants

Concordia University

$50,500.00

High-fidelity, directable animation transfer using facial decomposition on optimized micro-sequences

EF 2018-19

Résumé
*The entertainment industry delivers media products around the world to people speaking a large number of distinct languages. Media products such as TV or internet spots, movies and video games, typically consist of a video and sound stream. To accommodate different languages, the producers typically re-generate the sound stream in different language in a post-production step, a process known as dubbing. While it still takes a lot of effort to re-generate the sound stream (dubbing), one of the remaining open challenges both from a research and production point of view is how to synchronize the original video stream with the new audio stream. The lack of synchronization creates a very uncanny effect that takes away from the experience since the lip motion of the actors does not correspond to the soundtrack. In this project we propose a practical solution to the dubbing synchronization problem, producing natural results that can be used in a production studio. To achieve that, we created a strategic partnership with AudioZ, a production studio located in Montreal with whom we will collaborate on this project. We propose a video synthesis method that blends animation focusing on the lip area while preserving the facial expression of the original actor. Our method uses novel optimization techniques to avoid the common undesired uncanny valley effect of video synthesis.*
Programme
Collaborative Research and Development Grants
Bénéficiaire
Emplacement
Quebec, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data

Tel que publié

Application id
522014-2017
Name nom
Popa, Tiberiu
Department département
Computer Science and Software Engineering
Organization id
70
Institution établissement
Concordia University
Province en
Québec
Province fr
Québec
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2018
Competition year année de concours
2017
Award amount
50500
Program id
CRDPJ
Program name en
Collaborative Research and Development Grants
Program name fr
Subventions de recherche et développement coopérative
Group en
Research partnerships programs
Group fr
Programmes de partenariat
Committee code
96
Committee name en
RPP Internal Decision Cttee
Committee name fr
Cté de décision interne - PPR
Area of application code
1207
Area of application group en
Advancement of knowledge
Area of application group fr
Avancement des connaissances
Area of application en
Information, computer and communication technologies
Area of application fr
Technologie de l'information, des ordinateurs et des réseaux de communications
Research subject code
2708
Research subject group en
Information technology
Research subject group fr
Technologie de l'information
Research subject en
Image processing
Research subject fr
Traitement des images
Partie
1
Nb partie
1
Application title
High-fidelity, directable animation transfer using facial decomposition on optimized micro-sequences
Keyword
NSERC
Application summary
*The entertainment industry delivers media products around the world to people speaking a large number of distinct languages. Media products such as TV or internet spots, movies and video games, typically consist of a video and sound stream. To accommodate different languages, the producers typically re-generate the sound stream in different language in a post-production step, a process known as dubbing. While it still takes a lot of effort to re-generate the sound stream (dubbing), one of the remaining open challenges both from a research and production point of view is how to synchronize the original video stream with the new audio stream. The lack of synchronization creates a very uncanny effect that takes away from the experience since the lip motion of the actors does not correspond to the soundtrack. In this project we propose a practical solution to the dubbing synchronization problem, producing natural results that can be used in a production studio. To achieve that, we created a strategic partnership with AudioZ, a production studio located in Montreal with whom we will collaborate on this project. We propose a video synthesis method that blends animation focusing on the lip area while preserving the facial expression of the original actor. Our method uses novel optimization techniques to avoid the common undesired uncanny valley effect of video synthesis.*