[Mar. 2015] New paper accepted in IEEE TCSVT

Authors: S. Khattak, T. Maugey, R. Hamzaoui, S. Ahmad, P. Frossard

Title: Temporal and Inter-view Consistent Error Concealment Technique for Multiview  plus Depth Video Broadcasting accepted in  IEEE Transactions on Circuits and System for Video Technology (J11)

Abstract: Multiview plus depth (MVD) is an emerging video format with many applications, including 3D television and free viewpoint television. During broadcast of MVD video, trans- mission errors may cause the loss of whole frames, resulting in significant degradation of video quality. Error concealment techniques have been widely used to deal with transmission errors in video communication. However, the existing solutions do not address the requirement that the reconstructed frames be consistent with other frames. We propose a consistency model for error concealment of MVD video that allows to maintain a high level of consistency between frames of the same view (temporal consistency) and those of the neighbouring views (inter-view consistency). Simulations with the reference software for the Multiview Video Coding (MVC) project of the Joint Video Team (JVT) of the ISO/IEC Moving Pictures Experts Group (MPEG) and the ITU-T Video Coding Experts Group (VCEG) show that our technique outperforms two standard error concealment techniques with respect to both reconstruction quality and view consistency.

[Feb. 2015] New paper accepted in IEEE TIP

Authors: Thomas Maugey, Antonio Ortega, Pascal Frossard

Title: Graph-based representation for multiview image geometry accepted in  IEEE Transactions on Image Processing (J10)

Abstract: In this paper, we propose a new geometry representation method for multiview image sets. Our approach relies on graphs to describe the multiview geometry information in a compact and controllable way. The links of the graph connect pixels in different images and describe the proximity between pixels in 3D space. These connections are dependent on the geometry of the scene and provide the right amount of information that is necessary for coding and reconstructing multiple views. Our multiview image representation is very compact and adapts the transmitted geometry information as a function of the complexity of the prediction performed at the decoder side. To achieve this, our graph-based representation (GBR) carefully selects the amount of geometry information needed before coding. This is in contrast with depth coding, which directly compresses with losses the original geometry signal, thus making it difficult to quantify the impact of coding errors on geometry-based interpolation. We present the principles of this GBR and we build an efficient coding algorithm to represent it.
We compare our GBR approach to classical depth compression methods and compare their respective view synthesis qualities as a function of the compactness of the geometry description. We show that GBR can achieve significant gains in geometry coding rate over depth-based schemes operating at similar quality. Experimental results demonstrate the potential of this new representation.

More details: here

[Dec. 2014] Attending VCIP

From December 7th to 11th, I am attending VCIP 2014 that takes place in Malta.

I present three papers:

◊ L. Toni, T. Maugey, and P. Frossard, Packet Scheduling in Multi-Camera Capture Systems, IEEE VCIP, Matla, Dec. 2014

◊ A. De Abreu, N. Thomos, T. Maugey, L. Toni and P. Frossard, Multiview Video Representations for Quality-Scalable Navigation, IEEE VCIP, Matla, Dec. 2014

◊ T. Maugey, G. Petrazzuoli, P. Frossard, M. Cagnazzo and B. Pesquet-Popescu, Key view selection in distributed multiview coding, IEEE VCIP, Matla, Dec. 2014.

[Dec. 2014] New TMM submission

Authors: Laura Toni, Thomas Maugey, Pascal Frossard

Title: Optimized Packet Scheduling in Multiview Video Navigation Systems submitted for review to IEEE Transactions on Multimedia (ArXiv version)

Abstract: In multiview video systems, multiple cameras generally acquire the same scene from different perspectives, such that users have the possibility to select their preferred viewpoint. This results in large amounts of highly redundant data, which needs to be properly handled during encoding and transmission over resource-constrained channels. In this work, we study coding and transmission strategies in multicamera systems, where correlated sources send data through a bottleneck channel to a central server, which eventually transmits views to different interactive users. We propose a dynamic correlation-aware packet scheduling optimization under delay, bandwidth, and interactivity constraints. The optimization relies both on a novel rate-distortion model, which captures the importance of each view in the 3D scene reconstruction, and on an objective function that optimizes resources based on a client navigation model. The latter takes into account the distortion experienced by interactive clients as well as the distortion variations that might be observed by clients during multiview navigation.
We solve the scheduling problem with a novel trellis-based solution, which permits to formally decompose the multivariate optimization problem thereby significantly reducing the computation complexity. Simulation results show the gain of the proposed algorithm compared to baseline scheduling policies.
More in details, we show the gain offered by our dynamic scheduling policy compared to static camera allocation strategies and to schemes with constant coding strategies. Finally, we show that the best scheduling policy consistently adapts to the most likely user navigation path and that it minimizes distortion variations that can be very disturbing for users in traditional navigation systems.