Audio-visual object-based production for live events.
Lead Research Organisation:
University of Surrey
Department Name: Vision Speech and Signal Proc CVSSP
Abstract
Audio-visual object-based production for live events. Signal processing and machine learning techniques are useful for
extracting and tracking the metadata that accompanies media objects in an object-based workflow. Higher-level labels
may tag the video category or genre giving semantic information about a piece as a whole, where complementary data
from different modalities tends to enhance usability. In contrast, this project interrogates the more-detailed information that
can assist in the construction and manipulation of content within an authored audio-visual experience, such as the relative
location and geometry of actors or other scene elements. Furthermore, the focus will be towards techniques applicable in
a live production setting, e.g., for immersive and interactive 3D audio-visual media.
extracting and tracking the metadata that accompanies media objects in an object-based workflow. Higher-level labels
may tag the video category or genre giving semantic information about a piece as a whole, where complementary data
from different modalities tends to enhance usability. In contrast, this project interrogates the more-detailed information that
can assist in the construction and manipulation of content within an authored audio-visual experience, such as the relative
location and geometry of actors or other scene elements. Furthermore, the focus will be towards techniques applicable in
a live production setting, e.g., for immersive and interactive 3D audio-visual media.
Organisations
People |
ORCID iD |
| Nicholas Graham-Rack (Student) |
Studentship Projects
| Project Reference | Relationship | Related To | Start | End | Student Name |
|---|---|---|---|---|---|
| EP/R513350/1 | 30/09/2018 | 29/09/2023 | |||
| 2435520 | Studentship | EP/R513350/1 | 30/09/2020 | 31/12/2023 | Nicholas Graham-Rack |