Depth map creation and image-based rendering for advanced 3DTV services providing interoperability and scalability
By P. Kauff, N. Atzpadin, Christoph Fehn, Marcus Müller, Oliver Schreer, A. Smolic, R. Tanger. Signal processing. Image communication, 2007
402 citations recorded by the source corpus.
Subfields: Computer Graphics and Computer-Aided Design, Computer Vision and Pattern Recognition, Signal Processing
View Paper: https://www.semanticscholar.org/paper/261e39073725dd16d46aeaeb30b7b7dd3e8b78ee
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Graphics and Computer-Aided Design
In Computer Vision and Pattern Recognition
- K. Müller
- Philipp Merkle
- Thomas Wiegand
- A. Smolic
- Tsuhan Chen
- Jörn Ostermann
- Marcus A. Magnor
- Masayuki Tanimoto
In Signal Processing
- K. Müller
- Philipp Merkle
- Thomas Wiegand
- A. Smolic
- Tsuhan Chen
- Jörn Ostermann
- Masayuki Tanimoto
- Cha Zhang
Citations in the corpus
- 3D High-Efficiency Video Coding for Multi-View Video and Depth Data (2013, neutral): “The second approach is based on classical DIBR functionality [36].”
- Coding Algorithms for 3DTV—A Survey (2007, background): “[29] help to minimize these problems at the cost of increased data rate and complexity.”
- 3-D Video Representation Using Depth Maps (2011, methodology): “This is typically referenced as DIBR [ 19 ], [40].”
- Multiview Imaging and 3DTV (2007, methodology): “In general, the synthesis quality increases with the number of IEEE SIGNAL PROCESSING MAGAZINE [12] NOVEMBER 2007 IEEE SIGNAL PROCESSING MAGAZINE [13] NOVEMBER 2007 available views.”