Animated Scenes Research Articles

Scenes of Men in the Seal Impressions of Tell Abu Sha'af from the Iraqi Museum

The research presents and describes the scenes of men on the seal impressions of Tell Abu Sha'af from the Iraqi Museum, which came from the excavations of the Iraqi mission at the Tell Abu Sha'af site in 1978, which lasted for five months, and revealed 800 clay blocks (Bulla) of different shapes, sizes and colors, and the number of impressions found in a building known as the fortified palace. Some of the impressions are damaged, some are broken, and others are clear, bearing different scenes, based on which they were divided into several groups. The results of the excavations were published in the Sumer magazine in a special issue on the excavations of the Hamrin Dam Basin, and the impressions remained preserved in the stores of the Iraqi Museum, and since then they have not received a study that would reveal their nature and importance. Among the 800 clay blocks discovered at the site of Tell Abu Sha'af, (81) pieces of seal impressions (unpublished) were selected and studied in detail. They were dated by comparison to the period of the Sassanid occupation in Mesopotamia. In this study, we relied on the practical, descriptive and analytical method. Accordingly, these impressions were divided into four main groups (the group of scenes of men, the group of decorations and inscriptions, the group of animal scenes, and the group of mythical creatures). Our research is limited to the first group, which includes scenes of men only, and we chose only twelve models from it. In this study, we relied on the practical, descriptive and analytical method as well as comparison.

Spatial Thinking and Movements in Geometry: GeoGebra with a focus on building animated scenarios

Animated Scenarios are constructions created in GeoGebra with mathematical elements and movement, constituting an animated scene. Movement is fundamental to the construction of Animated Sceneries, it is also essential to spatial thinking and spatial abilities. This theoretical essay aims to discuss the potential of building Animated Scenarios in GeoGebra in/for the recognition of flat and spatial geometric objects, articulated with the movements associated with spatial thinking. For this, the House Animated Scenario are considered. Thus, we identified that movements performed during this construction allow rotating and modifying the shape of objects and that these movements are related to spatial abilities. Furthermore, the use of these movements in construction contributes to the recognition of important characteristics that distinguish flat and spatial objects.

Computer Simulation and Innovation of Virtual Reality Technology in Film and Television Animation Scene Construction

One of the artistic mediums of film and television is works of art. They represent a company's and a nation's cultural legacy in the modern period. They have long been the spirits that guide civilization towards affluence and advancement. The advancement of computer technology has led to extraordinary advancements in cinema and television technology, particularly in the field of special effects. When compared to more established real-world film and television technologies, virtual reality (VR) technology offers filmmakers and producers more creative freedom. This research propose novel technique in computer aided system in VR technology in film and television animation scene modelling based on artificial intelligence (AI). Here the virtual reality in film and animation scene has been constructed using machine learning. The 3D graphic design in animation scene modelling is carried out using convolutional generative fuzzy encoder face deformable model. Experimental analysis is carried out based on various animation scene construction dataset in terms of accuracy, precision, RMSE, robustness, F-1 score. This article designs a colour rendering system for 3D animation that is primarily separated into several modules based on various functionalities.

Retraction Note: Immersive animation scene design in animation language under virtual reality

Retraction Note: Immersive animation scene design in animation language under virtual reality

Impact of theta transcranial alternating current stimulation on language production in adult classic galactosemia patients.

Patients with classic galactosemia (CG), an inborn error of galactose metabolism, suffer from impairments in cognition, including language processing. Potential causes are atypical brain oscillations. Recent electroencephalogram (EEG) showed differences in the P300 event-related-potential (ERP) and alterations in the alpha/theta-range during speech planning. This study investigated whether transcranial alternating current stimulation (tACS) at theta-frequency compared to sham can cause a normalization of the ERP post stimulation and improves language performance. Eleven CG patients and fourteen healthy controls participated in two tACS-sessions (theta 6.5 Hz/sham). They were engaged in an active language task, describing animated scenes at three moments, that is, pre/during/post stimulation. Pre and post stimulation, behavior (naming accuracy, voice-onset-times; VOT) and mean-amplitudes of ERP were compared, by means of a P300 time-window analysis and cluster-based-permutation testing during speech planning. The results showed that theta stimulation, not sham, significantly reduced naming error-percentage in patients, not in controls. Theta did not systematically speed up naming beyond a general learning effect, which was larger for the patients. The EEG analysis revealed a significant pre-post stimulation effect (P300/late positivity), in patients and during theta stimulation only. In conclusion, theta-tACS improved accuracy in language performance in CG patients compared to controls and altered the P300 and late positive ERP-amplitude, suggesting a lasting effect on neural oscillation and behavior.

Altered neural oscillations in classical galactosaemia during sentence production.

Classical galactosaemia (CG) is a hereditary disease in galactose metabolism that despite dietary treatment is characterized by a wide range of cognitive deficits, among which is language production. CG brain functioning has been studied with several neuroimaging techniques, which revealed both structural and functional atypicalities. In the present study, for the first time, we compared the oscillatory dynamics, especially the power spectrum and time-frequency representations (TFR), in the electroencephalography (EEG) of CG patients and healthy controls while they were performing a language production task. Twenty-one CG patients and 19 healthy controls described animated scenes, either in full sentences or in words, indicating two levels of complexity in syntactic planning. Based on previous work on the P300 event related potential (ERP) and its relation with theta frequency, we hypothesized that the oscillatory activity of patients and controls would differ in theta power and TFR. With regard to behavior, reaction times showed that patients are slower, reflecting the language deficit. In the power spectrum, we observed significant higher power in patients in delta (1-3 Hz), theta (4-7 Hz), beta (15-30 Hz) and gamma (30-70 Hz) frequencies, but not in alpha (8-12 Hz), suggesting an atypical oscillatory profile. The time-frequency analysis revealed significantly weaker event-related theta synchronization (ERS) and alpha desynchronization (ERD) in patients in the sentence condition. The data support the hypothesis that CG language difficulties relate to theta-alpha brain oscillations.

Artistic Creation and Animation Scene Designing using Hierarchical Spatio-Temporal Graph Convolutional Neural Network Optimized with Gazelle Optimization Algorithm

Artistic Creation and Animation Scene Designing using Hierarchical Spatio-Temporal Graph Convolutional Neural Network Optimized with Gazelle Optimization Algorithm

Intelligent Construction of Animation Scenes and Dynamic Optimization of Character Images by Computer Vision

Intelligent Construction of Animation Scenes and Dynamic Optimization of Character Images by Computer Vision

A proposed reconstruction method of a 3D animation scene based on a fuzzy long and short-term memory algorithm.

With the development of computer technology leading to a broad range of virtual technology implementations, the construction of virtual tasks has become highly demanded and has increased rapidly, especially in animation scenes. Constructing three-dimensional (3D) animation characters utilizing properties of actual characters could provide users with immersive experiences. However, a 3D face reconstruction (3DFR) utilizing a single image is a very demanding operation in computer graphics and vision. In addition, limited 3D face data sets reduce the performance improvement of the proposed approaches, causing a lack of robustness. When datasets are large, face recognition, transformation, and animation implementations are relatively practical. However, some reconstruction methods only consider the one-to-one processes without considering the correlations or differences in the input images, resulting in models lacking information related to face identity or being overly sensitive to face pose. A face model composed of a convolutional neural network (CNN) regresses 3D deformable model coefficients for 3DFR and alignment tasks. The manuscript proposes a reconstruction method for 3D animation scenes employing fuzzy LSMT-CNN (FLSMT-CNN). Multiple collected images are employed to reconstruct 3D animation characters. First, the serialized images are processed by the proposed method to extract the features of face parameters and then improve the conventional deformable face modeling (3DFDM). Afterward, the 3DFDM is utilized to reconstruct animation characters, and finally, high-precision reconstructions of 3D faces are achieved. The FLSMT-CNN has enhanced both the precision and strength of the reconstructed 3D animation characters, which provides more opportunities to be applied to other animation scenes.

Animation Scene Generation Based on Deep Learning of CAD Data

Animation Scene Generation Based on Deep Learning of CAD Data

The expression of multimedia animation art design in the era of artificial intelligence

Abstract Aesthetic rules are the basis of animation art design, combined with the user-centered design method is a new form of multimedia animation art design. This paper combines the existing three-dimensional animation art forms of expression, the use of points, lines, and surfaces to generate three-dimensional animation three-dimensional space, and selected virtual reality technology to achieve three-dimensional animation conversion. Based on ray tracing algorithm and radiance global illumination technology, to optimize animation scene realism, analyze the difficulties of rendering image styles. Combined with the Canny edge extraction algorithm to extract the target area contour, homogenization processing of local area coloring, fusion of the extracted contour and coloring area, the formation of animation style rendering, constituting the design of this paper three-dimensional animation art design expression. Analyze the rendering data of trees in a typical natural scene and use design evaluation indexes to assess the performance impact of animation scene art design. The average score for the animation scene expressing information content, the average score for the animation matching with the information, and the average score for the animation effect art and beauty are 7.672, 7.027, and 7.474, respectively. The scores indicate that the animation art design expression proposed in this paper can provide a more accurate depiction of the aesthetics of animation art.

Stereoscopic Image Enabled Animation Art Design Exploration

Abstract With the emergence of movie art, many related art forms were born. Animation art has gained a large number of audiences due to its exaggerated expression. In order to improve the problems of character image overlapping and scene distortion that may occur in the original two-dimensional space, this paper constructs a semi-global stereo image matching algorithm based on the use of point cloud matching in the animation screen for the determination of the screen position and the morphology of the animated character. To compensate for the radiation difference in the stereo image matching algorithm, object-square geometric constraints are proposed to improve the matching cost calculation process. After calculating the matching cost, the original animation model is optimized or rebuilt by creating a depth space image. Taking Disney animation characters as an example, the number of joints required for the reconstruction of the “Snow White” character is 2.9 times more than that of the “Mickey” character, but the reconstruction time of the skeleton is only 12 times longer than that of the “Mickey” character. However, the skeleton reconstruction time is only 12.1 seconds longer than that of the “Mickey” character, which indicates that the algorithm proposed in this paper does not produce a large difference in reconstruction time due to the difference in characters. For the construction of animated indoor scenes, in the eight experimental scenes, the maximum number of grids can be divided into 42365412, and the processing time required is 276.413 seconds. It shows that the algorithm in this paper is capable of subregionally refining the indoor space of the animation. The proposed semi-global stereo image matching-based pan can quickly reconstruct animated character models and animated scenes, as can be seen.

Artistic Characteristics and Innovative Application of Ink Animation in Animation Scenes in the Age of Artificial Intelligence

Abstract This paper discusses the artistic characteristics and innovative applications of ink animation in the era of artificial intelligence, mainly including the preprocessing of ink works, the Extraction of stylistic feature analysis, the internal haloing technique, and the simulation technique of ink painting features. The research methods include image segmentation, object contour and internal separation, and the application of ink stylization techniques. The results show that the improved CIE1976L*a*b* color space transformation and the “kernel-free” region growing method have successfully realized the efficient processing and stylistic feature extraction of ink works. The experiments use the gray scale co-production matrix for texture characterization, and the results show that the extracted stylistic features have a high degree of consistency with the traditional artistic features of ink animation. In addition, the practical expression of terrain ink style is realized by 3D ink rendering technology, which demonstrates the innovative application of ink animation in modern technology.

Intelligent Recognition and Classification of 3D Animation Styles - Based on AIGC Technology Application

Abstract The study of style identification in 3D animation not only enhances the artistry of animation scenes but also has a profound significance on the development of 3D animation works. In this paper, we first sorted out the art style expressions of 3D animation and explored the innovation path of 3D animation art style and related influencing factors. Based on the generative adversarial network in AIGC technology, the discriminator and generator are trained. The 3D animation style intelligent recognition and classification model is established by combining the GAN network and SoftMax classifier, and the loss function of the model is optimized. Using crawler technology to obtain 3D animation-related images and crop them to 128*128 size for dataset construction, 3D animation style recognition and classification experiments were designed to verify the application effectiveness of the 3D-GAN model. It is found that the 3D-GAN model reaches the peak of IS index 9.222 after 60*103 iterations, which is 12.85% higher than the ALGAN model. The average classification accuracy of the 3D-GAN model is 91.42%, which is 6.01 percentage points higher than that of the sub-optimal CycleGAN model. Conducting intelligent recognition and classification of 3D animation styles based on AIGC technology can provide a new direction for innovating 3D animation styles and optimizing scene design.

Research on 3D Animation Scene Plane Design Based on Deep Learning

Abstract At present, most graphic design methods of 3D animation scenes only get a small part of 3D animation scenes, and all of them are in a 3D coordinate system, with observers as the core, so it is difficult to express the depth information of 3D animation scenes. This project intends to study a plane design method for 3D animation scenes based on deep learning. CNN (Convolutional Neural Network) is used to build a multi-view 3D animation scene generation network, and 3D geometry and structure of objects are reconstructed through multiple or a group of images. On this basis, the feature extraction method of 3D animation scenes is studied, and the collaborative learning model of multiple networks is established to improve the modeling accuracy of 3D animation scenes. The experimental results show that the network model is superior to the method based on multi-view and 0-1 voxel in detecting retrieval performance, and the accuracy rate can reach 91.725%. The multi-view 3D animation scene generation method in this paper has achieved better results than the current advanced methods, which proves that the multi-view feature fusion network proposed in this paper is a more reasonable method to fuse multi-view image features.

Research on animation performance based on virtual reality technology

Abstract In this study, we utilize the acquisition device from Open Pose to capture the joint points of human posture. Subsequent to data collection, each joint point undergoes a coordinate regularization process, using the neck coordinates as a reference, to derive human skeleton data. This processed data facilitates the extraction of angles and relative distances among all human body limbs, effectively capturing characteristic feature information. This information is subsequently imported into the Iclone software, where it is refined using a fitting tool to develop a bespoke character model. Following the character's construction, the study leverages NURBS curve modeling and Polygon polygon modeling technologies within the 3D software MAYA to achieve precise scene modeling. This approach culminates in the production of an animated performance that integrates virtual reality technology, with its effects thoroughly analyzed. During Action A, the animation method developed in this study yielded an average running frame rate of 96.54 frames per second, and the average texture size was 6.39 MB. These metrics significantly surpass those achieved by comparative methods. Moreover, the efficiency of animation scene production in this study (0.134339 seconds) substantially exceeds that of the control method (0.273984 seconds), thereby enhancing the level of animation design technology and presenting a more lifelike 3D virtual animation.

Research on the Visual Effect of Contemporary Northeast Red Cultural Elements in Digital Animation Creation

Abstract This paper analyzes the value and characteristics of the red cultural elements of the Northeast, as well as the characteristics of the integration of the red culture of the Northeast and the creation of animation, and discusses the application of the red cultural elements of the Northeast in the animation transmission. Northeast Red Digital Animation began to do the preliminary preparatory work. The preparatory work includes determining the main content of the animation and according to the main content of the narration and text script creation, the production of the activity storyboards, and the design work of the information elements needed in the video. The subdivision modeling method in Maya software is used to construct the animation scene. Path planning is a very important link in the production of group behavior animation, by changing to the artificial fish school algorithm to optimize the animation path. The path data obtained is imported into the Maya scene. Then the final digital animation results can be obtained with the help of the animation generation method provided by Maya. Setting the model parameters and research objects, the animation creation for integrating the red culture of Northeast China is researched and analyzed. For the optimal time, this paper’s algorithm runs for 20.9109s less than the time used by the GA algorithm. The mean value of the visual effect of the animation integrating the red culture of the Northeast is 3.47, which indicates that the designed animation brings the user a more satisfactory visual experience, and it is necessary to let the audience understand the spirit and sentiment behind the red culture in order to effectively improve the visual effect of the animation integrating the red culture of the Northeast.

Parametric Design Algorithm Guided by Machine Vision in Animation Scene Design

Parametric Design Algorithm Guided by Machine Vision in Animation Scene Design

Animation Scene Object Recognition and Modeling Based on Computer Vision Technology

Animation Scene Object Recognition and Modeling Based on Computer Vision Technology

Animation Scene Design and Machine Vision Rendering Optimization Combining Generative Models

Animation Scene Design and Machine Vision Rendering Optimization Combining Generative Models