Transport of video over partial order connections

A Partial Order and partial reliable Connection (POC) is an end-to-end transport connection authorized to deliver objects in an order that can differ from the transmitted one. Such a connection is also authorized to lose some objects. The POC concept is motivated by the fact that heterogeneous best-effort networks such as Internet are plagued by unordered delivery of packets and losses, which tax the performances of current applications and protocols. It has been shown, in several research works, that out of order delivery is able to alleviate (with respect to CO service) the use of end systems’ communication resources. In this paper, the efficiency of out-of-sequence delivery on MPEG video streams processing is studied. Firstly, the transport constraints (in terms of order and reliability) that can be relaxed by MPEG video decoders, for improving video transport, are detailed. Then, we analyze the performance gain induced by this approach in terms of blocking times and recovered errors. We demonstrate that POC connections fill not only the conceptual gap between TCP and UDP but also provide real performance improvements for the transport of multimedia streams such MPEG video

Towards a new generation of transport services adapted to multimedia application

Une connexion d'ordre et de fiabilité partiels (POC, partial order connection) est une connexion de transport autorisée à perdre certains objets mais également à les délivrer dans un ordre éventuellement différent de celui d'émission. L'approche POC établit un lien conceptuel entre les protocoles sans connexion au mieux et les protocoles fiables avec connexion. Le concept de POC est motivé par le fait que dans les réseaux hétérogènes sans connexion tels qu'Internet, les paquets transmis sont susceptibles de se perdre et d'arriver en désordre, entraînant alors une réduction des performances des protocoles usuels. De plus, on montre qu'un protocole associé au transport d'un flux multimédia permet une réduction très sensible de l'utilisation des ressources de communication et de mémorisation ainsi qu'une diminution du temps de transit moyen. Dans cet article, une extension temporelle de POC, nommée TPOC (POC temporisé), est introduite. Elle constitue un cadre conceptuel permettant la prise en compte des exigences de qualité de service des applications multimédias réparties. Une architecture offrant un service TPOC est également introduite et évaluée dans le cadre du transport de vidéo MPEG. Il est ainsi démontré que les connexions POC comblent, non seulement le fossé conceptuel entre les protocoles sans connexion et avec connexion, mais aussi qu'ils surpassent les performances des ces derniers lorsque des données multimédias (telles que la vidéo MPEG) sont transportées

Error resilience and concealment techniques for high-efficiency video coding

This thesis investigates the problem of robust coding and error concealment in High Efficiency Video Coding (HEVC). After a review of the current state of the art, a simulation study about error robustness, revealed that the HEVC has weak protection against network losses with significant impact on video quality degradation. Based on this evidence, the first contribution of this work is a new method to reduce the temporal dependencies between motion vectors, by improving the decoded video quality without compromising the compression efficiency. The second contribution of this thesis is a two-stage approach for reducing the mismatch of temporal predictions in case of video streams received with errors or lost data. At the encoding stage, the reference pictures are dynamically distributed based on a constrained Lagrangian rate-distortion optimization to reduce the number of predictions from a single reference. At the streaming stage, a prioritization algorithm, based on spatial dependencies, selects a reduced set of motion vectors to be transmitted, as side information, to reduce mismatched motion predictions at the decoder. The problem of error concealment-aware video coding is also investigated to enhance the overall error robustness. A new approach based on scalable coding and optimally error concealment selection is proposed, where the optimal error concealment modes are found by simulating transmission losses, followed by a saliency-weighted optimisation. Moreover, recovery residual information is encoded using a rate-controlled enhancement layer. Both are transmitted to the decoder to be used in case of data loss. Finally, an adaptive error resilience scheme is proposed to dynamically predict the video stream that achieves the highest decoded quality for a particular loss case. A neural network selects among the various video streams, encoded with different levels of compression efficiency and error protection, based on information from the video signal, the coded stream and the transmission network. Overall, the new robust video coding methods investigated in this thesis yield consistent quality gains in comparison with other existing methods and also the ones implemented in the HEVC reference software. Furthermore, the trade-off between coding efficiency and error robustness is also better in the proposed methods

A parallel H.264/SVC encoder for high definition video conferencing

In this paper we present a video encoder specially developed and configured for high definition (HD) video conferencing. This video encoder brings together the following three requirements: H.264/Scalable Video Coding (SVC), parallel encoding on multicore platforms, and parallel-friendly rate control. With the first requirement, a minimum quality of service to every end-user receiver over Internet Protocol networks is guaranteed. With the second one, real-time execution is accomplished and, for this purpose, slice-level parallelism, for the main encoding loop, and block-level parallelism, for the upsampling and interpolation filtering processes, are combined. With the third one, a proper HD video content delivery under certain bit rate and end-to-end delay constraints is ensured. The experimental results prove that the proposed H.264/SVC video encoder is able to operate in real time over a wide range of target bit rates at the expense of reasonable losses in rate-distortion efficiency due to the frame partitioning into slices

Respiratory organ motion in interventional MRI : tracking, guiding and modeling

Respiratory organ motion is one of the major challenges in interventional MRI, particularly in interventions with therapeutic ultrasound in the abdominal region. High-intensity focused ultrasound found an application in interventional MRI for noninvasive treatments of different abnormalities. In order to guide surgical and treatment interventions, organ motion imaging and modeling is commonly required before a treatment start. Accurate tracking of organ motion during various interventional MRI procedures is prerequisite for a successful outcome and safe therapy. In this thesis, an attempt has been made to develop approaches using focused ultrasound which could be used in future clinically for the treatment of abdominal organs, such as the liver and the kidney. Two distinct methods have been presented with its ex vivo and in vivo treatment results. In the first method, an MR-based pencil-beam navigator has been used to track organ motion and provide the motion information for acoustic focal point steering, while in the second approach a hybrid imaging using both ultrasound and magnetic resonance imaging was combined for advanced guiding capabilities. Organ motion modeling and four-dimensional imaging of organ motion is increasingly required before the surgical interventions. However, due to the current safety limitations and hardware restrictions, the MR acquisition of a time-resolved sequence of volumetric images is not possible with high temporal and spatial resolution. A novel multislice acquisition scheme that is based on a two-dimensional navigator, instead of a commonly used pencil-beam navigator, was devised to acquire the data slices and the corresponding navigator simultaneously using a CAIPIRINHA parallel imaging method. The acquisition duration for four-dimensional dataset sampling is reduced compared to the existing approaches, while the image contrast and quality are improved as well. Tracking respiratory organ motion is required in interventional procedures and during MR imaging of moving organs. An MR-based navigator is commonly used, however, it is usually associated with image artifacts, such as signal voids. Spectrally selective navigators can come in handy in cases where the imaging organ is surrounding with an adipose tissue, because it can provide an indirect measure of organ motion. A novel spectrally selective navigator based on a crossed-pair navigator has been developed. Experiments show the advantages of the application of this novel navigator for the volumetric imaging of the liver in vivo, where this navigator was used to gate the gradient-recalled echo sequence

Real-time magnetic resonance imaging: Radial gradient-echo sequences with nonlinear inverse reconstruction.

Objective The aim of this study is to evaluate a real-time magnetic resonance imaging (MRI) method that not only promises high spatiotemporal resolution but also practical robustness in a wide range of scientific and clinical applications. Materials and Methods The proposed method relies on highly undersampled gradient-echo sequences with radial encoding schemes. The serial image reconstruction process solves the true mathematical task that emerges as a nonlinear inverse problem with the complex image and all coil sensitivity maps as unknowns. Extensions to model-based reconstructions for quantitative parametric mapping further increase the number of unknowns, for example, by adding parameters for phase-contrast flow or T1 relaxation. In all cases, an iterative numerical solution that minimizes a respective cost function is achieved with use of the iteratively regularized Gauss-Newton method. Convergence is supported by regularization, for example, to the preceding frame, whereas temporal fidelity is ensured by downsizing the regularization strength in comparison to the data consistency term in each iterative step. Practical implementations of highly parallelized algorithms are realized on a computer with multiple graphical processing units. It is "invisibly" integrated into a commercial 3-T MRI system to allow for conventional usage and to provide online reconstruction, display, and storage of regular DICOM image series. Results Depending on the application, the proposed method offers serial imaging, that is, the recording of MRI movies, with variable spatial resolution and up to 100 frames per second (fps)-corresponding to 10 milliseconds image acquisition times. For example, movements of the temporomandibular joint during opening and closing of the mouth are visualized with use of simultaneous dual-slice movies of both joints at 2 x 10 fps (50 milliseconds per frame). Cardiac function may be studied at 30 to 50 fps (33.3 to 20 milliseconds), whereas articulation processes typically require 50 fps (20 milliseconds) or orthogonal dual-slice acquisitions at 2 x 25 fps (20 milliseconds). Methodological extensions to model-based reconstructions achieve improved quantitative mapping of flow velocities and T1 relaxation times in a variety of clinical scenarios. Conclusions Real-time gradient-echo MRI with extreme radial undersampling and nonlinear inverse reconstruction allows for direct monitoring of arbitrary physiological processes and body functions. In many cases, pertinent applications offer hitherto impossible clinical studies (eg, of high-resolution swallowing dynamics) or bear the potential to replace existing MRI procedures (eg, electrocardiogram-gated cardiac examinations). As a consequence, many novel opportunities will require a change of paradigm in MRI-based radiology. At this stage, extended clinical trials are needed

Motion estimation for H.264/AVC on multiple GPUs using NVIDIA CUDA

To achieve the high coding efficiency the H.264/AVC standard offers, the encoding process quickly becomes computationally demanding. One of the most intensive encoding phases is motion estimation. Even modern CPUs struggle to process high-definition video sequences in real-time. While personal computers are typically equipped with powerful Graphics Processing Units (GPUs) to accelerate graphics operations, these GPUs lie dormant when encoding a video sequence. Furthermore, recent developments show more and more computer configurations come with multiple GPUs. However, no existing GPU-enabled motion estimation architectures target multiple GPUs. In addition, these architectures provide no early-out behavior nor can they enforce a specific processing order. We developed a motion search architecture, capable of executing motion estimation and partitioning for an H.264/AVC sequence entirely on the GPU using the NVIDIA CUDA (Compute Unified Device Architecture) platform. This paper describes our architecture and presents a novel job scheduling system we designed, making it possible to control the GPU in a flexible way. This job scheduling system can enforce real-time demands of the video encoder by prioritizing calculations and providing an early-out mode. Furthermore, the job scheduling system allows the use of multiple GPUs in one computer system and efficient load balancing of the motion search over these GPUs. This paper focuses on the execution speed of the novel job scheduling system on both single and multi-GPU systems. Initial results show that real-time full motion search of 720p high-definition content is possible with a 32 by 32 search window running on a system with four GPUs