Compact real-time modeling of seated humans by video sprite sequence quantization

We propose an image-based method for real-time modeling of seated humans using upper-body video sprites, which is suitable for applications such as teleconferencing and distance learning. A database of representative video sprite sequences is pre-acquired and pre-uploaded to each remote rendering si...

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Veröffentlicht in:The Visual computer Jg. 25; H. 5-7; S. 565 - 572
Hauptverfasser: Jia, Chun, Popescu, Voicu
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Berlin/Heidelberg Springer-Verlag 01.05.2009
Springer Nature B.V
Schlagworte:
Artificial Intelligence
Computer Graphics
Computer Science
Data compression
Image Processing and Computer Vision
Matching
Modelling
Original Article
Real time
Redundancy
Rendering
Teleconferencing
Vector quantization
Video compression
Image-based modeling and rendering
ISSN:0178-2789, 1432-2315
Online-Zugang:Volltext
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Beschreibung
Zusammenfassung:We propose an image-based method for real-time modeling of seated humans using upper-body video sprites, which is suitable for applications such as teleconferencing and distance learning. A database of representative video sprite sequences is pre-acquired and pre-uploaded to each remote rendering site. At run-time, for each input sprite, a closely matching sprite is located in the database and the index of the matching sprite is sent to the rendering site, which drastically reduces the data rate. Unlike other data compression methods, our method takes advantage of the limited number of significant body positions a participant assumes during a session. Exploiting redundancy between frames with distant time stamps enables aggressive compression rates with high visual and semantic fidelity.
Bibliographie:ObjectType-Article-1
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ISSN:0178-2789
1432-2315
DOI:10.1007/s00371-009-0318-4