Optimized Data Representation for Interactive Multiview Navigation

In contrary to traditional media streaming services where a unique media content is delivered to different users, interactive multiview navigation applications enable users to choose their own viewpoints and freely navigate in a 3-D scene. The interactivity brings new challenges in addition to the classical rate-distortion trade-off, which considers only the compression performance and viewing quality. On the one hand, interactivity necessitates sufficient viewpoints for richer navigation; on the other hand, it requires to provide low bandwidth and delay costs for smooth navigation during view transitions. In this paper, we formally describe the novel trade-offs posed by the navigation interactivity and classical rate-distortion criterion. Based on an original formulation, we look for the optimal design of the data representation by introducing novel rate and distortion models and practical solving algorithms. Experiments show that the proposed data representation method outperforms the baseline solution by providing lower resource consumptions and higher visual quality in all navigation configurations, which certainly confirms the potential of the proposed data representation in practical interactive navigation systems

Navigation domain representation for interactive multiview imaging

Enabling users to interactively navigate through different viewpoints of a static scene is a new interesting functionality in 3D streaming systems. While it opens exciting perspectives towards rich multimedia applications, it requires the design of novel representations and coding techniques in order to solve the new challenges imposed by interactive navigation. Interactivity clearly brings new design constraints: the encoder is unaware of the exact decoding process, while the decoder has to reconstruct information from incomplete subsets of data since the server can generally not transmit images for all possible viewpoints due to resource constrains. In this paper, we propose a novel multiview data representation that permits to satisfy bandwidth and storage constraints in an interactive multiview streaming system. In particular, we partition the multiview navigation domain into segments, each of which is described by a reference image and some auxiliary information. The auxiliary information enables the client to recreate any viewpoint in the navigation segment via view synthesis. The decoder is then able to navigate freely in the segment without further data request to the server; it requests additional data only when it moves to a different segment. We discuss the benefits of this novel representation in interactive navigation systems and further propose a method to optimize the partitioning of the navigation domain into independent segments, under bandwidth and storage constraints. Experimental results confirm the potential of the proposed representation; namely, our system leads to similar compression performance as classical inter-view coding, while it provides the high level of flexibility that is required for interactive streaming. Hence, our new framework represents a promising solution for 3D data representation in novel interactive multimedia services

Livrable D4.2 of the PERSEE project : Représentation et codage 3D - Rapport intermédiaire - Définitions des softs et architecture

51Livrable D4.2 du projet ANR PERSEECe rapport a été réalisé dans le cadre du projet ANR PERSEE (n° ANR-09-BLAN-0170). Exactement il correspond au livrable D4.2 du projet. Son titre : Représentation et codage 3D - Rapport intermédiaire - Définitions des softs et architectur

In-Network View Synthesis for Interactive Multiview Video Systems

To enable Interactive multiview video systems with a minimum view-switching delay, multiple camera views are sent to the users, which are used as reference images to synthesize additional virtual views via depth-image-based rendering. In practice, bandwidth constraints may however restrict the number of reference views sent to clients per time unit, which may in turn limit the quality of the synthesized viewpoints. We argue that the reference view selection should ideally be performed close to the users, and we study the problem of in-network reference view synthesis such that the navigation quality is maximized at the clients. We consider a distributed cloud network architecture where data stored in a main cloud is delivered to end users with the help of cloudlets, i.e., resource-rich proxies close to the users. In order to satisfy last-hop bandwidth constraints from the cloudlet to the users, a cloudlet re-samples viewpoints of the 3D scene into a discrete set of views (combination of received camera views and virtual views synthesized) to be used as reference for the synthesis of additional virtual views at the client. This in-network synthesis leads to better viewpoint sampling given a bandwidth constraint compared to simple selection of camera views, but it may however carry a distortion penalty in the cloudlet-synthesized reference views. We therefore cast a new reference view selection problem where the best subset of views is defined as the one minimizing the distortion over a view navigation window defined by the user under some transmission bandwidth constraints. We show that the view selection problem is NP-hard, and propose an effective polynomial time algorithm using dynamic programming to solve the optimization problem. Simulation results finally confirm the performance gain offered by virtual view synthesis in the network

Object-based 2D-to-3D video conversion for effective stereoscopic content generation in 3D-TV applications

Three-dimensional television (3D-TV) has gained increasing popularity in the broadcasting domain, as it enables enhanced viewing experiences in comparison to conventional two-dimensional (2D) TV. However, its application has been constrained due to the lack of essential contents, i.e., stereoscopic videos. To alleviate such content shortage, an economical and practical solution is to reuse the huge media resources that are available in monoscopic 2D and convert them to stereoscopic 3D. Although stereoscopic video can be generated from monoscopic sequences using depth measurements extracted from cues like focus blur, motion and size, the quality of the resulting video may be poor as such measurements are usually arbitrarily defined and appear inconsistent with the real scenes. To help solve this problem, a novel method for object-based stereoscopic video generation is proposed which features i) optical-flow based occlusion reasoning in determining depth ordinal, ii) object segmentation using improved region-growing from masks of determined depth layers, and iii) a hybrid depth estimation scheme using content-based matching (inside a small library of true stereo image pairs) and depth-ordinal based regularization. Comprehensive experiments have validated the effectiveness of our proposed 2D-to-3D conversion method in generating stereoscopic videos of consistent depth measurements for 3D-TV applications