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Iris folding is an art-form consisting of layered strips of paper, forming a spiral pattern behind an aperture, which can be used to make cards and gift tags. This paper describes an interactive computational tool to assist in the design and construction of original iris folding patterns. The design of iris folding patterns is formulated as the calculation of a circumscribed polygonal sequence around a seed polygon. While it is possible to compute the positions of vertices analytically for a regular polygon, it is not straightforward to do so for irregular polygons. We give a numerical method for irregular polygons, which can be applied to arbitrary convex seed polygons. The user can quickly experiment with various patterns using the system prior to constructing the art-form. [ABSTRACT FROM AUTHOR]

The purpose of this study is to investigate student designers' attitude and choices towards the use of computers and paper sketches when involved in a graphic design process. 65 computer graphic technology undergraduates participated in this research. A mixed method study with survey and in-depth interviews was applied to answer the research questions. This result shows that sketches and computers as design tools help students generate ideas in the early stage of design. Students' preferences to use sketches or computers differ, since each tool has its own advantages and disadvantages. [ABSTRACT FROM AUTHOR]

The text is a preface to the Journal of Computer Science & Technology's special section on the Computational Visual Media (CVM) conference series. The CVM conference serves as an international platform for the exchange of research ideas and computational methodologies related to visual media. The conference encourages collaboration across disciplines such as computer graphics, computer vision, machine learning, and more. The 12th international conference in the series, CVM 2024, was held in Wellington, New Zealand, and attracted attention from researchers worldwide. The special section includes six outstanding papers covering various topics, as well as an invited survey paper. The editors express gratitude to the authors and reviewers for their contributions. The preface also provides brief biographies of the leading editor and guest editors. [Extracted from the article]

The document is an editorial message from the guest editors of the Computational Visual Media (CVM) 2024 Special Issue. The CVM conference series aims to facilitate the exchange of research ideas and computational methodologies related to visual media. The 12th international conference, CVM 2024, was held in New Zealand and received significant attention from researchers worldwide. The special issue includes 10 outstanding papers covering various topics such as 3D fabrication, image processing, and music generation. The editors express gratitude to the authors and reviewers for their contributions. [Extracted from the article]

The integration of edge intelligence (EI) in animation design, particularly when dealing with large models, represents a significant advancement in the field of computer graphics and animation. This survey aims to provide a comprehensive overview of the current state and future prospects of EI-assisted animation design, focusing on the challenges and opportunities presented by large model implementations. Edge intelligence, characterized by its decentralized processing and real-time data analysis capabilities, offers a transformative approach to handling the computational and data-intensive demands of modern animation. This paper explores various aspects of EI in animation and then delves into the specifics of large models in animation, examining their evolution, current trends, and the inherent challenges in their implementation. Finally, the paper addresses the challenges and solutions in integrating EI with large models in animation, proposing future research directions. This survey serves as a valuable resource for researchers, animators, and technologists, offering insights into the potential of EI in revolutionizing animation design and opening new avenues for creative and efficient animation production. [ABSTRACT FROM AUTHOR]

Design and artwork driven by image sampling processing has a half-century tradition in contemporary art and computer graphics. In the past two decades, a similar approach has been used for the fabrication of abstract surface patterns for building facades. Recent advances in digital manufacturing based on industrial robots have reignited the interest toward developing new design-to-fabrication techniques which can possess intriguing visual and tectonic properties of the facades, based on image sampling processing and abstract image representation. The aim of the paper is to investigate the different strategies for creating surface patterns, based on image sampling and applying industrial robots as fabrication tools. In this paper, three different robotic fabrication strategies for generating surface patterns driven by image sampling are presented. [ABSTRACT FROM AUTHOR]

Computational Visual Media is a journal that has been successful for nine years, and the editor-in-chief expresses gratitude to the authors, reviewers, and editorial board members for their contributions. In 2023, the journal published 48 papers in four issues, including regular submissions and papers recommended by the CVM Conference. Starting in 2024, the journal will change from quarterly to bimonthly issues to accommodate the increasing number of submissions. The journal has achieved a high impact factor and is included in important indexing and database services. The editor looks forward to receiving excellent papers in 2024. [Extracted from the article]

With the advancement of 3D scanning technologies and deep learning theories, point cloud-based deep learning networks have gained considerable attention in the fields of 3D vision and computer graphics. Leveraging the rich geometric information present in 3D point clouds, these networks facilitate more accurate feature learning tasks. However, existing networks often suffer from generalization defects caused by variations in pose and inconsistent representations of training data. In this paper, we propose a novel data augmentation framework to overcome these limitations. Our approach utilizes principal component analysis (PCA) to generate four aligned copies of a point cloud. These copies are then input into a multi-channel structure, which is compatible with popular backbones of point cloud-based deep networks. Finally, the outputs of the multi-channel structure are merged to generate rotation-invariant feature learning results. Experimental evaluations demonstrate the efficacy of our framework, showcasing significant improvements in various existing point cloud-based deep learning methods. Notably, our method exhibits enhanced robustness in classification tasks, particularly when dealing with point clouds containing random pose variations and non-uniform densities. Project link: https://github.com/LAB123-tech/PCAlign. [ABSTRACT FROM AUTHOR]

Edge-aware image smoothing refers to the removal of details with edges preserved. It is an essential topic in the field of image processing and computer graphics. In this paper, in order to achieve better edge preservation than the existing models, we propose a robust edge-preserving image filtering method based on a complementary weighting scheme. Both isotropic and anisotropic weights are involved in our model to adapt the fidelity and the regularization terms. To efficiently solve the proposed model, we introduce an effective algorithm based on additive half quadratic minimization, alternating direction of multipliers, and Fourier domain optimization strategies. We experimentally validate the proposed filter on several low-level vision tasks. Both quantitative and qualitative experimental results show significant superiority of our proposed filter compared to existing techniques. Furthermore, the filter exhibits high efficiency and is able to process 720P color images (over 10 fps) in real-time on an NVIDIA RTX 3070. Therefore, it is practical for real-world applications. [ABSTRACT FROM AUTHOR]

The target detection algorithm has a high accuracy rate for the detection of general objects. However, for specific kinds of objects, especially those with complex application scenarios and high requirements on recognition rates, the accuracy and real-time performance are still far behind the actual application requirements. Meanwhile, the high real-time performance of most current target detection algorithm depends on high-performance computers or Graphics Processing Units (GPUs), which limits their application in low-performance embedded system. In this paper, an embedded vehicle detection algorithm was proposed. Compared to the existing general detection algorithms, the network structure of the proposed algorithm has been improved in many aspects. Firstly, the overall network structure of YOLOv3-tiny has been improved, and the way of feature extraction has been modified to increase the network in terms of detection speed and recognition accuracy. Secondly, a spatial pyramid pooling structure is introduced into the network to enhance the learning capability, and the spatial pyramid pooling structure is also improved by increasing the number of pooling layers in the structure and cascading multiple groups of pooling layers of different sizes. Thirdly, to speed up target detection process, the original clustering algorithm is replaced by Kmean++ clustering algorithm, and the original IoU (The Intersection over Union) loss function is replaced by GIoU (Generalized IoU). Fourthly, according to the scale factor of batch normalization layer, the model is compressed and trimmed to remove redundant channels, and a small model more suitable for embedded system application is obtained. Finally, Raspberry Pi 4B and Inter NCS2 neural computing stick are used as the embedded system with the input image size of 416 × 416. Experimental tests on UA-DETRAC dataset obtain higher mAP than other advanced existing methods, indicating that the network model proposed in this paper could effectively improve the real time and accuracy of multi-vehicle target detection. [ABSTRACT FROM AUTHOR]

Various rotation operations are required in paleomagnetism. These include transformations to the geographic coordinate system, tilt correction, and finding virtual geomagnetic poles. Different methods have been used for each rotation operation—graphical manipulation on stereonet, matrix calculation, and spherical trigonometry—and computer software has been developed based on these methods. Quaternions, which are commonly used in three-dimensional computer graphics, can handle rotations about arbitrary axes and provide a unified description of the various rotation operations in paleomagnetism. The conversion from a sample coordinate system to the geographic coordinate system depends on orientation methods that vary by sample type and laboratory. Traditionally, coordinate transformations have been computed using rotation matrices of Euler angles based on stereonet manipulation, but quaternions can flexibly accommodate samples oriented by different conventions. Tilt correction can be expressed as a single rotation around the strike direction of the formation. Virtual geomagnetic poles can be obtained by a single quaternion rotation instead of complicated spherical trigonometry. Python functions are provided for all of the rotation operations discussed in this paper, so the readers can incorporate these functions into their own programs to perform rotations using quaternions. [ABSTRACT FROM AUTHOR]

This paper is motivated by results of extensive comparative study of three-point methods for solving nonlinear equations presented in the paper (C. Chun, B. Neta, Comparative study of eighth-order methods for finding simple roots of nonlinear equations, Numer. Algor. 74, 1169–1201, 2017). In the first part, we show that the best ranking method, constructed by Sharma and Arora in 2016, is actually a special case of the family of three-point methods presented in the paper (J. Džunić, M. S. Petković, L. D. Petković, A family of optimal three-point methods for solving nonlinear equations using two parametric functions, Appl. Math. Comput. 217, 7612–7619, 2011). Since the mentioned Chun-Neta's comparative study was carried out by testing algebraic polynomials of low degree (not higher than 6), in the second part we have extended comparative study to higher-order polynomials, polynomials with random coefficients, and polynomials with clusters of zeros. The performed experiments confirmed results of Chun and Neta. As in the cited paper of Chun and Neta, we have also applied the quality study based on computer visualization plotting the basins of attraction. [ABSTRACT FROM AUTHOR]

In this short paper, we analyze the problem of finding the triangular barycentric coordinates of an interpolated ray hitting a given point. This task, which we term the inverse barycentric displacement problem, is general and useful in geometry processing and computer graphics. Concrete applications of the solution include the construction of displacement maps and texture baking. We derive the set of complete, closed-form solutions and discuss the number and existence of solutions. We close with a discussion of implementation-oriented optimizations and a few example applications. [ABSTRACT FROM AUTHOR]

The neural radiance field (NeRF) has shown promising results in preserving the fine details of objects and scenes. However, unlike explicit shape representations e.g., mesh, it remains an open problem to build dense correspondences across different NeRFs of the same category, which is essential in many downstream tasks. The main difficulties of this problem lie in the implicit nature of NeRF and the lack of ground-truth correspondence annotations. In this paper, we show it is possible to bypass these challenges by leveraging the rich semantics and structural priors encapsulated in a pre-trained NeRF-based GAN. Specifically, we exploit such priors from three aspects, namely (1) a dual deformation field that takes latent codes as global structural indicators, (2) a learning objective that regards generator features as geometric-aware local descriptors, and (3) a source of infinite object-specific NeRF samples. Our experiments demonstrate that such priors lead to 3D dense correspondence that is accurate, smooth, and robust. We also show that established dense correspondence across NeRFs can effectively enable many NeRF-based downstream applications such as texture transfer. [ABSTRACT FROM AUTHOR]

The text is a preface to the Journal of Computer Science & Technology, specifically a special section on the Computer Graphics International (CGI) conference. The CGI conference is a prestigious international academic conference in the field of computer graphics and virtual reality. It aims to foster collaboration between different disciplines and showcase advancements in computer graphics technology. The CGI 2023 conference was held in Shanghai, China, and featured discussions on various topics including computer graphics, virtual reality, geometric design, animation, and healthcare. The special section in the journal includes five selected papers that cover a range of topics and provide an overview of the latest trends in computer graphics and virtual reality. The preface expresses gratitude to the authors and reviewers and encourages readers to explore the special section to stay updated on the developments in these fields. [Extracted from the article]

Computer vision-based inspection methods show promise for automating post-earthquake building inspections. These methods survey a building with unmanned aerial vehicles and automatically detect damage in the collected images. Nevertheless, assessing the damage's impact on structural safety requires localizing damage to specific building components with known design and function. This paper proposes a BIM-based automated inspection framework to provide context for visual surveys. A deep learning-based semantic segmentation algorithm is trained to automatically identify damage in images. The BIM automatically associates any identified damage with specific building components. Then, components are classified into damage states consistent with component fragility models for integration with a structural analysis. To demonstrate the framework, methods are developed to photorealistically simulate severe structural damage in a synthetic computer graphics environment. A graphics model of a real building in Urbana, Illinois, is generated to test the framework; the model is integrated with a structural analysis to apply earthquake damage in a physically realistic manner. A simulated UAV survey is flown of the graphics model and the framework is applied. The method achieves high accuracy in assigning damage states to visible structural components. This assignment enables integration with a performance-based earthquake assessment to classify building safety. [ABSTRACT FROM AUTHOR]

Our long-term project involves performing general-purpose computation on 2D amorphous computing media, which consist of arbitrary many, small, identical processing elements that are homogeneously spread in 2D Euclidian space, and that communicate locally in space. While the minimal assumptions on hardware provide the fascinating perspective of arbitrary large computing power, they also make programming notoriously difficult. Furthermore, our project involves simulating objects extended in 2D-space, called "blobs". Maintaining the connectedness of blobs while they move in space adds another layer of difficulty since it demands to process the topology of 2D space. This paper describes a new parallel data structure that can simplify the programming task, in this context. In computer graphics, processing related to 2D topology is performed by using triangle meshes. We consider synchronous media whose underlying network is also a triangle mesh. Our data structure, derived from computer graphics, is anchored on that mesh so that its operations can be compiled on the medium. More precisely, our compiler produces a circuit of logic gates, which enables a high-performance simulation, in the case of crystalline media (Cellular Automata). We demonstrate the expressiveness of the data structure's operation by using an incremental and modular programming style. We program, first small, then larger building-block functions, and re-use them. Blobs are implemented and re-used to compute the Voronoï diagram. What is the scope of the data-structure? This poses the question of whether there exists a universal set of primitives able to program any processing specified only in terms of 2D-geometry. [ABSTRACT FROM AUTHOR]

Synthesizing garment dynamics according to body motions is a vital technique in computer graphics. Physics-based simulation depends on an accurate model of the law of kinetics of cloth, which is time-consuming, hard to implement, and complex to control. Existing data-driven approaches either lack temporal consistency, or fail to handle garments that are different from body topology. In this paper, we present a motion-inspired real-time garment synthesis workflow that enables high-level control of garment shape. Given a sequence of body motions, our workflow is able to generate corresponding garment dynamics with both spatial and temporal coherence. To that end, we develop a transformerbased garment synthesis network to learn the mapping from body motions to garment dynamics. Frame-level attention is employed to capture the dependency of garments and body motions. Moreover, a post-processing procedure is further taken to perform penetration removal and auto-texturing. Then, textured clothing animation that is collision-free and temporally-consistent is generated. We quantitatively and qualitatively evaluated our proposed workflow from different aspects. Extensive experiments demonstrate that our network is able to deliver clothing dynamics which retain the wrinkles from the physics-based simulation, while running 1 000 times faster. Besides, our workflow achieved superior synthesis performance compared with alternative approaches. To stimulate further research in this direction, our code will be publicly available soon. [ABSTRACT FROM AUTHOR]

Three-dimensional (3D) face reconstruction technology is a key issue in the field of computer vision and computer graphics. The image-based 3D face reconstruction method is the mainstream technology of 3D face reconstruction. This paper uses the 3D face reconstruction algorithm to analyze the 3D reconstruction of a static image face and the structure and realization of the computer standardized management system. In the process of high-resolution two-channel matching, combined with multilevel reconstruction technology, a better initial disparity map is obtained by comparison. Then, the improved disparity map optimization algorithm is used to optimize the initial value, so that the result of the cloud point is smoother on the model surface while maintaining good detail accuracy. The AdaBoost face detection algorithm based on embedded images is used to obtain the image representing the region, and grayscale conversion and normalization processing are performed. Finally, the Poisson surface reconstruction algorithm is used to reconstruct a 3D high-precision face model. The experimental results in this paper show that the AdaBoost face detection algorithm can effectively separate and express face features, reduce the feature dimensions to compactly represent the data and correctly classify expressions. The 3D face reconstruction technology based on static images can increase the recognition rate of a face by 24% and can also increase the texture mapping effect of the local area of the face by 13%. [ABSTRACT FROM AUTHOR]

Due to the evolution of graphics processors over recent decades it has now become possible to produce high-quality, realistic three-dimensional scenes. However, aliasing occurs during the sampling process performed during rasterization, which causes a serrated effect around the edges of the objects presented in the scene, highlighting an unreal aspect of the image and causing displeasure to the viewer. This paper aims to develop an anti-aliasing treatment based on rotated spatial filtering. It undertakes edge detection by applying spatial filtering with a simple linear regression technique. A smoothing spatial filter is then rotated to match the direction of the inspected edge and is applied to the affected regions. Testing was performed on an OpenGL application, processing the rendered image from the framebuffer, and Blender, a 3D modeling software that enables scenes with more complex graphics. The results have demonstrated the effectiveness of the proposed method in smoothing aliasing with good quality while preserving the details of the scene. Hence, the problem was managed effectively with a post-filtering approach and without oversampling. The running time of the algorithm is O(n), and the memory used is O(n). [ABSTRACT FROM AUTHOR]

An introduction is presented in which editor discusses the various articles presented in the Computational Visual Media Conference 2013 and 3-dimensional Object Retrieval workshop on topics including computer graphics, image processing and machine learning.

Physically based modeling of deformable curves and surfaces has been widely used in computer graphics to meet the needs of both geometry and physics. In this paper, the weighted sum of the first and higher order generalized thin-plate spline-surface energies is introduced for the construction of transition surface. We derive the necessary and sufficient condition that the energy functional of a transition surface reaches its minimum, by which the positions of movable control points can be fully determined within the constraints imposed by the controls and continuity constraints. Furthermore, based on the excellent properties of Bernstein basis functions, we present a simple algorithm to compute energy-minimizing transition surfaces if the given two disjoint tensor product surfaces are in Bézier form. The feasibility of the method is validated by several examples. Compared with previous modeling methods, various physical characteristics are imparted on the modeling of transition surfaces in this paper, thus various energy-minimizing transition surfaces with different characteristics can be obtained. [ABSTRACT FROM AUTHOR]

An introduction is presented in which the article discusses various reports within the issue on topics including the Artificial Intelligence and Pattern Recognition, Computer Graphics and Computer Architecture and Systems.

Face analysis has been a hot research field in computer vision for decades. The dataset is of vital importance for modern machine learning methods. The paper proposes a flexible CG (Computer Graphics) rendering pipe-line for creating facial image datasets together with automatic ground truth labelling. The proposed pipe-line could produce a huge amount of labelled data fast and in low cost compared to traditional dataset creation methods which need high cost hardware and longtime manual ground truth labelling. The paper also proposes a data capture setup in the CG environment for creating the dataset for facial landmark localization. The effectiveness of the proposed method is verified by cross validation with Multi-PIE dataset. For creating a high quality training dataset, some of the varying factors of the dataset should be considered. The paper analyzes a few varying factors for accurate eye landmark localization, such as eye closure levels, eye and eyebrow shapes and wearing glasses. Based on the benefits of the proposed CG rendering pipe-line, the paper implemented a facial landmark localization system across large face rotation by integrating off-the-shelves algorithms. The experiments on Multi-PIE and real persons show that the implemented system could localize facial landmarks accurately across [−90°, +90°] in yaw rotation in real time. [ABSTRACT FROM AUTHOR]

Generative Adversarial Networks (GAN) show excellent performance in various problems of computer vision, computer graphics, and machine learning, but require large amounts of data and huge computational resources. There is also the issue of unstable training. If the generator and discriminator diverge during the training process, the GAN is subsequently difficult to converge. In order to tackle these problems, various transfer learning methods have been introduced; however, mode collapse, which is a form of overfitting, often arises. Moreover, there were limitations in learning the distribution of the training data. In this paper, we provide a comprehensive review of the latest transfer learning methods as a solution to the problem, propose the most effective method of fixing some layers of the generator and discriminator, and discuss future prospects. The model to be used for the experiment is StyleGAN, and the performance evaluation uses Fréchet Inception Distance (FID), coverage, and density. Results of the experiment revealed that the proposed method did not overfit. The model was able to learn the distribution of the training data relatively well compared to the previously proposed methods. Moreover, it outperformed existing methods at the Stanford Cars, Stanford Dogs, Oxford Flower, Caltech-256, CUB-200–2011, and Insect-30 datasets. [ABSTRACT FROM AUTHOR]

The optimal multi-degree reduction of ball Said–Ball curves is an unsolved and knotty important technique in computer aided design (CAD) and computer graphics (CG) and is potentially used in many engineering fields involving geometric modeling. In this paper, an improved chimp optimization algorithm (ICHOA, for short) is used to solve the degree reduction of BSB curves. Firstly, the multi-degree reduction of BSB curves is mathematically an optimization problem that can be efficiently dealt with by a swarm intelligence algorithm. In this regard, a novel enhanced version of CHOA called ICHOA, combined with the proportional weight, dimension learning-based hunting search and fractional order strategies, is developed to enhance its capability of jumping out of the local minima and improve the calculation accuracy of the native algorithm. Furthermore, the superiority of the ICHOA is verified by comparing it with standard CHOA, other improved CHOA and popular nature-inspired optimization algorithms on 23 classical benchmark functions, the CEC'17 test suite and five engineering optimization problems, respectively. Secondly, the optimization models of multi-degree reduction for the center curve and radius function of BSB curves are established, respectively; meanwhile, the proposed ICHOA is utilized to solve the established optimization models, and the optimal center curve and radius function with a minimum distance of the approximating BSB curves of lower degree are also obtained. Finally, experimental results illustrate the ability of the proposed ICHOA to effectively solve the optimization problems of multi-degree reduction of BSB curves in terms of precision, robustness, and convergence characteristics. [ABSTRACT FROM AUTHOR]

Visuospatial representations of numbers and their relationships are widely used in mathematics education. These include drawn images, models constructed with concrete manipulatives, enactive/embodied forms, computer graphics, and more. This paper addresses the analytical limitations and ethical implications of methodologies that use broad categorizations of representations and argues the benefits of dynamic qualitative analysis of arithmetical-representational strategy across multiple semi-independent aspects of display, calculation, and interaction. It proposes an alternative methodological approach combining the structured organization of classification with the detailed nuance of description and describes a systematic but flexible framework for analysing nonstandard visuospatial representations of early arithmetic. This approach is intended for use by researchers or practitioners, for interpretation of multimodal and nonstandard visuospatial representations, and for identification of small differences in learners' developing arithmetical-representational strategies, including changes over time. Application is illustrated using selected data from a microanalytic study of struggling students' multiplication and division in scenario tasks. [ABSTRACT FROM AUTHOR]

In this paper, we focus on pointwise and weighted approximation properties of newly defined Stancu variant of λ -Schurer operators. We establish a direct local approximation theorem and obtain a global approximation formula. These newly defined operators reduce to classical Schurer, Bernstein, Stancu, λ -Bernstein, λ -Stancu, λ -Schurer operators for the special cases of parameters. Certain illustrative and numerical examples are given to verify the convergence behavior and accuracy of the proposed operators. The numerical evaluations that obtained in this study may facilitate understanding and interpreting main results of this paper for the reader. [ABSTRACT FROM AUTHOR]

In Earth science, original data elaboration is often very complex and the results are generally provided in the form of (computer-made) maps, a qualitative representation. The aim of this paper is to illustrate a graphic method of analysis that allows the reverse: tracing back, on scientific bases, quantitative data from computer-mapped information, by using widely-available graphic tools, including an estimate of the precision of the numerical outcomes. That may be needed, e.g., for independent evaluation of published data or, for comparison with new elaborations. A NASA video was used as an example, reconstructing the maps of the Earth surface yearly from 1998 to 2017. Static frames were extracted from it and used to obtain numerical data on the evolution of the min/max snow/ice-covered land/sea surfaces, separately for the two hemispheres. The use of the proposed method allows concerned scientists to obtain the quantitative values of the relevant data, including an uncertainty estimate, e.g., in order to compare them with those found in the literature and on websites. The paper focuses on the map-analysis method, and on the metrological evaluation of the uncertainty of the retrieved data. Finally, some quantitative results are commented and found consistent with literature data on the same subject matter. [ABSTRACT FROM AUTHOR]

This paper is dedicated to the analysis of the existing approaches to video codecs comparisons. It includes the revealed drawbacks of popular comparison methods and proposes new techniques. The performed analysis of user-generated videos collection showed that two of the most popular open video collections from media.xiph.org which are widely used for video-codecs analysis and development do not cover real-life videos complexity distribution. A method for creating representative video sets covering all segments of user videos the spatial and temporal complexity is also proposed. One of the sections discusses video quality estimation algorithms used for video codec comparisons and shows the disadvantages of popular methods VMAF and NIQE. Also, the paper describes the drawbacks of the BD-rate – generally used method for video codecs final ranking during comparisons. A new ranking method called BSQ-rate which considers the identified issues is proposed. The results of this investigation were obtained during the series of research conducted as part of the annual video-codecs comparisons organized by video group of computer graphics and multimedia laboratory at Moscow State University. [ABSTRACT FROM AUTHOR]