Section: Contracts and Grants with Industry
Industrial contracts
CIFRE contract with France Telecom on the problem of 3D video representation
Participants : Thomas Colleu, Claude Labit.
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Title : 3D video representation for 3DTV and Free viewpoint TV.
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Research axis : § 6.1.2 .
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Partners : France Télécom, Irisa/Inria-Rennes.
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Funding : France Télécom.
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Period : Oct.07-Sept.10.
This contract with France Telecom R&D (started in October 2007) aims at investigating the data representation for 3DTV and Free Viewpoint TV applications. 3DTV applications consist in 3D relief rendering and Free Viewpoint TV applications consist in an interactive navigation inside the content. As an input, multiple color videos and depth maps are given to our system. The goal is to process this data so as to obtain a compact representation suitable for 3D TV and Free Viewpoint functionalities. In 2008, we have developed a multi-view video representation based on a global geometric model composed with a soup of polygons. In 2009, the construction of the representation has been improved in order to reduce the number of quads and eliminate artifacts around depth discontinuities as well as the corresponding rendering approach (see Section 6.1.2 ). A coding algorithm adapted to the polygon soup representation has been developed. The performance of the coding scheme has been compared with the encoding of the depth maps using JPEG2000.
CIFRE contract with Thomson on the problem of spectral deconvolution for video compression and protection
Participants : Jean-Jacques Fuchs, Christine Guillemot, Aurélie Martin.
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Title : Spectral deconcolution: application to compression
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Research axis : § 6.2.3 .
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Partners : Thomson, Irisa/Inria-Rennes.
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Funding : Thomson, ANRT.
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Period : Nov.06- Oct.09.
This CIFRE contract concerns the Ph.D of Aurélie martin. The objective of the Ph.D. is to develop image spectral deconvolution methods for prediction in video compression schemes. Closed-loop spatial prediction has indeed been widely used in video compression standards (H.261/H.263, MPEG-1/2/4, H.264). In H.264 used for digital terrestrial TV, the prediction is done by simply “propagating” the pixel values along the specified direction. This approach is suitable in presence of contours, the directional mode chosen corresponds to the orientation of the contour. However, it fails in more complex textured areas. The spatial image prediction approach developed in the context of this collaboration relies on sparse approximations based on matching pursuit algorithms. In a first step dictionaries based on classical waveforms such as DCT and DFT have been considered. In 2009, a method to enhance to dictionaries taking into account a phase shift between the signal to be approximated and the waveforms taken as dictionary atoms has been developed showing further rate saving (up to 9
Collaboration with Alcatel on robust video compression
Participants : Simon Bos, Christine Guillemot, Laurent Guillo, Aline Roumy.
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Title: Self adaptive video codec
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Research axis: 6.3.1
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Funding: Joint research laboratory between INRIA and Alcatel
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Period: Nov. 2008 - Oct. 2011.
In the framework of the joint research lab between Alcatel-Lucent and INRIA, we participate in the ADR (action de recherche) Selfnets (or Self optimizing wireless networks). More precisely, we collaborate with the Alcatel-Lucent team on a self adaptive video codec. This collaboration concerns the Ph.D. of Simon Bos. The goal is to design a video codec, which has the intrinsic knowledge of the dynamic video quality requirements, and which is able to self-adapt to the existing underlying transport network. In this approach, the video codec has to include:
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Means to dynamically "sense" the underlying transport channel (e.g BER, PER, Markov model)
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Means at the encoder to adapt dynamically the output bitrate to the estimated channel throughput and to the effective transport QoS while maintaining the video quality requirements.
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Means at the decoder to be resilient to any remaining packet losses. enditemize