Bridging standards for digital television broadcast

We address the problem of tracking points in dense vector fields. Such vector fields may come from computational fluid dynamics simulations, environmental monitoring sensors, or dense point tracking of video data. To track points in vector fields, we capture the distribution of higher-order properties (e.g., properties derived from the gradient of the velocity vector field) in a novel local descriptor called a vector spin-image. Our distribution-based approach has a number of advantages over methods that use topology analysis to track points in vector fields. The local distributions are robust to noise, adaptable to changes in the feature, and can be used to extrapolate the location of features after they have disappeared. We describe the vector spin-image data structure, the higher-order properties we record to track vector field points, and show results of tracking points in the simulated flow through a diesel engine cylinder.

In this paper, we present a surface reconstruction via 2D strokes and a vector field on the strokes based on a two-step method. In the first step, from sparse strokes drawn by artists and a given vector field on the strokes, we propose a nonlinear vector interpolation combining total variation (TV) and H 1 regularization with a curl-free con- straint for obtaining a dense vector field. In the second step, a height map is obtained by integrating the dense vector field in the first step. Jump discontinuities in surface and discontinuities of surface gradients can be well reconstructed without any surface distortion. We also provide a fast and efficient algorithm for solving the proposed func- tionals. Since vectors on the strokes are interpreted as a projection of surface gradients onto the plane, different types of strokes are easily devised to generate geometrically crucial structures such as ridge, valley, jump, bump, and dip on the surface. The stroke types help users to create a surface which they intuitively imagine from 2D strokes. We compare our results with conventional methods via many examples. AMS subject classifications: 65K10, 65D18, 65D17

Technological advancements, changes in consumer behavior, technological accessibility, social media, streaming services, and advancements in production technology have all led to exponential growth in digital audio and video production. With media convergence, the distinction between audio and video media becomes unclear. This makes multimedia content more flexible. However, changing business models,copyright issues, and content quality are also affected by this phenomenon. The development of digital audio and video production has experienced significant exponential growth, influenced by technologicaladvancements, changes in consumer behavior, technological accessibility, social media, streaming services, and advances in production technology. Media convergence has blurred the boundaries between audio and video media, creating flexibility in multimedia content. However, this phenomenon also has an impact on changing business models, content quality, and copyright issues. Copyright issues are taking center stage in the industry, especially with the rise of video sharing and streaming platforms. Copyright protection is a major challenge, and the law must constantly adapt to technological advances. The methodological approach carried out in this study is called literature research. The result of the discussion was that alternative business models such as subscribe, crowdfunding, and partnerships became strategies to address copyright issues. By studying media convergence, recommendation algorithms, copyright issues, business models, and user roles can help us to understand and control complex developments in digital audio and video production. To maintain the integrity of this industry, ethical guidelines and responses to technological trends must be created.

As of today, perioperative monitoring in the operating room is based on vital signs and clinical observations by the anesthesiologist. This, however, does not offer a complete monitoring of left ventricular function throughout the intervention. We hypothesize that functional monitoring of the heart can be performed automatically based on transesophageal echocardiographic (TEE) images. The main goal of this work is therefore to compute the non-linear deformation between subsequent images in a TEE sequence of the left ventricle and estimate basal longitudinal strain to assess regional myocardial function using a deep learning approach. An unsupervised approach based on a convolutional neural network (CNN) was implemented. The output of the CNN network is a dense vector field that describes the non-linear deformation required to maximize the similarity between two images.Recordings from 42 consecutive complete TEE exams from the Echocardiography Unit were anonymized and used for training. Recordings from 5 consecutive TEE exams performed during heart surgery, also anonymized, were used as test set. For the test set patients, the basal strain was manually annotated in EchoPac by an expert echocardiographer. For this work, 19 heart cycles were randomly selected from the test set and checked to ensure visibility of the points to be tracked. Overall when estimating strain there was a mean difference of 7.25%(±4.56%) in the strain values when compared to expert annotations.We have proven that point tracking is working as expected in most images, where the myocardium is well depicted. However, dropouts, noise generated by implants or air bubbles after surgery, confuse the tracker and drifting occurs.

Film grain is often a desirable feature in video production, creating a natural appearance and contributing to the expression of creative intent. Film grain, however, does not compress well with modern video compression standards, such as Versatile Video Coding (VVC) also known as ITU-T H.266 and ISO/IEC 23090-3. Indeed, within various filtering and lossy compression steps, film grain is suppressed without the possibility of recovering it. One option to alleviate this problem is to use lower quantization parameters to better preserve fine details such as film grain. However, this may strongly increase the bitrate. In some scenarios, information on film grain can be communicated as metadata through for instance an SEI message specified by Versatile Supplemental Enhancement Information (VSEI, also known as ITU-T Recommendation H.274 and ISO/IEC 23002-7). Thus, film grain is often modeled and removed prior to compression, and it is then synthesized at the decoder side with the aid of appropriate metadata. In addition, film grain can also be used as a tool to mask coding artifacts introduced by the compression. Different approaches have been studied for film grain modeling. In the context of the novel VVC standard, a frequency filtering solution to parameterize and synthesize film grain can be used. This paper provides an overview of such film grain VVC-compatible technology, including parameterization, signaling and decoder side synthesis. Thus, in this paper, an approach based on the frequency filtering is firstly summarized. Then, a quantitative and qualitative simulations are preformed to show the benefits of film grain parameterization in terms of the bitrate savings for the same perceived quality.

This article presents the results of a study using Q-methodology to identify and compare different learning styles between video production and media studies undergraduate courses. Three groups emerged from the video production course compared to four groups from a previous study. These two sets of groups were compared. Results demonstrate distinctions and similarities between the different learning styles that emerged from the two types of courses. The article concludes that the use of Q-methodology can deepen understanding of students’ learning preferences and improve instruction through more balanced and learner-focused curricular approaches.

Some heart abnormalities like ischemia and infarction of myocardium can produce significant changes in cardiac wall motion and decrease severely the cardiac function. For this reason the cardiac motion estimation and quantification have been the focus of many investigations. The aim of this work is to study cardiac motion by means a dense velocity vector field based on the computation of the Wigner-Ville distribution, a common transformation used in the spatiotemporal-frequency (STF) analysis. The major motivation for considering the use of STF comes from observations in mammalian vision. This paper describes a method to obtain a 3D-frequency spectrum, based on the computation of the Wigner-Ville distribution, and a procedure to determine, automatically, the velocity of pixels in a temporal series of images. The method is also applied to synthetic images and real images obtained from gated-SPECT.

In this paper a mechanism for computing multiple motion models along with the corresponding regions of support for a sequence of images is presented. The mechanism is an indirect parametric motion estimation technique. Firstly, a robust technique based on the fundamental constraint equation of multiple optical flow is used to estimate a dense multiple vector field of the scene. Secondly, from the recovered low-level data, motion models and their corresponding regions of support are estimated through a variant of the expectation-maximisation (EM) algorithm. The proposed algorithm is shown to provide good motion estimates and regions of support.

This paper deals with the estimation of a dense displacement vector field between two successive images in a sequence using the markovian modelization. The optical flow is processed in two different hierarchical frameworks with the regularized constraint model we proposed. This model is derived from the potential function introduced by Geman and MacClure, in which we integrate the local motion amplitude obtained by Fourier analysis. It enables adaptive smoothness and then preserves motions discontinuities. First we apply a coarse-to-fine strategy in a standard multiresolution pyramid. We use the ICM algorithm only on the finest resolution scale of the pyramid, and the simulated annealing on the other scales. Secondly, we work with the multiscale scheme which allows only one resolution for the observations and a pyramidal structure for the primitives (the estimated optical flow). The results obtained on synthetic and real images sequences show that the estimation is efficiency increased. In our second contribution in this paper, we define a criterion for the determination of the regularization hyperparameter which controls the weight of the regularization term in the energy function. It is based on the entropy of the estimated motion vectors. An experimental study of this entropy allows to find the value of the hyperparameter which best fits a given sequence.© (1999) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Monocular depth estimation is vital for scene understanding and downstream tasks. We focus on the supervised setup, in which ground-truth depth is available only at training time. Based on knowledge about the high regularity of real 3D scenes, we propose a method that learns to selectively leverage information from coplanar pixels to improve the predicted depth. In particular, we introduce a piecewise planarity prior which states that for each pixel, there is a seed pixel which shares the same planar 3D surface with the former. Motivated by this prior, we design a network with two heads. The first head outputs pixel-level plane coefficients, while the second one outputs a dense off-set vector field that identifies the positions of seed pixels. The plane coefficients of seed pixels are then used to predict depth at each position. The resulting prediction is adaptively fused with the initial prediction from the first head via a learned confidence to account for potential deviations from precise local planarity. The entire architecture is trained end-to-end thanks to the differentiability of the proposed modules and it learns to predict regular depth maps, with sharp edges at occlusion boundaries. An extensive evaluation of our method shows that we set the new state of the art in supervised monocular depth estimation, surpassing prior methods on NYU Depth-v2 and on the Garg split of KITTI. Our method delivers depth maps that yield plausible 3D reconstructions of the input scenes. Code is available at: https://github.com/SysCV/P3Depth

Based on recent experimental as well as theoretical investigations, a generalization of previously published approaches towards the estimation of displacement vector fields is formulated. The calculus of variation allows to transform this approach into a set of two partial differential equations for the two components of the displacement vector field. Some simplifying assumptions facilitate the derivation of an iterative solution approach which can be studied in closed form.

H.264 Scalable Video Coding (SVC) is an extension to the Advanced Video Coding (AVC) H.264 standard which provides efficient scalability functionalities on top of the high coding efficiency of H.264/AVC. SVC allows for temporal, spatial, and quality scalability of the output video stream, encoding the video information into an H.264/AVC base layer and a series of enhancement layers which incrementally improve the quality, increase screen resolution and/or frame rate. SVC is particularly suited for mobile TV reception, since the received video quality is adaptable to variable reception conditions and heterogeneous receiver capabilities. However, mobile TV Digital Video Broadcasting (DVB) standards such as DVB-H and DVB-SH were designed prior to the introduction of SVC, and therefore the underlying transmission protocols are not optimized for scalable video delivery. In this overview paper, we review recently proposed solutions for SVC stream adaptation on the underlying DVB-H/SH protocols, and point out novel technical solutions that are currently under consideration for the next generation mobile broadcasting standard DVB-NGH.

Digital broadcasting has been an area of active\nresearch, development, innovation and business models development\nin recent years. This paper presents a survey on the characteristics of\nthe digital terrestrial television broadcasting (DTTB) standards, and\nimplementation status of DTTB worldwide showing the standards\nadopted. It is clear that only the developed countries and some in the\ndeveloping ones shall be able to beat the ITU set analogue to digital\nbroadcasting migration deadline because of the challenges that these\ncountries faces in digitizing their terrestrial broadcasting. The\nchallenges to keep on track the DTTB migration plan are also\ndiscussed in this paper. They include financial, technology gap,\npolicies alignment with DTTB technology, etc. The reported\nperformance comparisons for the different standards are also\npresented. The interesting part is that the results for many\ncomparative studies depends to a large extent on the objective behind\nsuch studies, hence counter claims are common.

Background: It is a common fact that the rapid development of technology influenced many aspects of the world, including mass communication. Television, as the most popular and familiar broadcast media in Indonesia, has experienced several changes due to the presence of advanced technology. One of the significant transformations is the transition from analog to digital broadcasting systems. The new era of digital broadcasting could improve the performance and quality of digital television itself. Purpose: This recent study aimed to obtain an overview of the realization carried out by one of the local private broadcasting institutions in Banten, JPM TV. Methods: Using a qualitative case study along with in-depth interviews and observation as data collection techniques, this study examines JPM TV from various aspects in realizing digital TV broadcasts in Banten Province. Results: The study’s findings highlighted that JPM TV strives to realize digital broadcasting by gradually replacing equipment with tools that support digital broadcasting and elements of human resources trained and prepared with special internal and external training. JPM TV also collaborated with LPPM (Mix Broadcasting Organizing Agency), namely Mix Metro TV. The ongoing process is coordinated with the government. Obstacles faced during the migration process are the socioeconomic conditions of the people who have not been able to support the digital broadcasting process, which is characterized by the difficulty of obtaining digital broadcasting at relatively low prices; besides that, it is also necessary to increase the capacity of Human Resources (HR) so that television shows are more comfortable to watch. Implications: One of the implications is that the government must innovate to provide incentives that can stimulate the readiness of the digital broadcasting ecosystem.

Motion estimation (ME) methods based on differential techniques provide useful information for video analysis, and moreover it is relatively easy to embed into them regularity constraints enforcing for example, contour preservation. On the other hand, these techniques are rarely employed for video compression since, though accurate, the dense motion vector field (MVF) they produce requires too much coding resource and computational effort. However, this kind of algorithm could be useful in the framework of distributed video coding (DVC), where the motion vector are computed at the decoder side, so that no bit-rate is needed to transmit them. Moreover usually the decoder has enough computational power to face with the increased complexity of differential ME. In this paper we introduce a new image interpolation algorithm to be used in the context of DVC. This algorithm combines a popular DVC technique with differential ME. We adapt a pel-recursive differential ME algorithm to the DVC context; moreover we insert a regularity constraint which allows more consistent MVFs. The experimental results are encouraging: the quality of interpolated images is improved of up to 1.1 dB w.r.t. to state-of-the-art techniques. These results prove to be consistent when we use different GOP sizes.