3D Character Model Research Articles

EasySkinning: Target-oriented skinning by mesh contraction and curve editing

Skinning, a critical process in animation that defines how bones influence the vertices of a 3D character model, significantly impacts the visual effect in animation production. Traditional methods are time-intensive and skill-dependent, whereas automatic techniques lack in flexibility and quality. Our research introduces EasySkinning, a user-friendly system applicable to complex meshes. This method comprises three key components: rigid weight initialization through Voronoi contraction, precise weight editing via curve tools, and smooth weight solving for reconstructing target deformations. EasySkinning begins by contracting the input mesh inwards to the skeletal bones, which improves vertex-to-bone mappings, particularly in intricate mesh areas. We also design intuitive curve-editing tools, allowing users to define more precise bone influential regions. The final stage employs advanced deformation algorithms for smooth weight solving, crucial for achieving desired animations. Through extensive experiments, we demonstrate that EasySkinning not only simplifies the creation of high-quality skinning weights but also consistently outperforms existing automatic and interactive skinning methods.

Technology of the development of 3D character models for a computer game

Technology of the development of 3D character models for a computer game

CreatureShop: Interactive 3D Character Modeling and Texturing From a Single Color Drawing.

Creating 3D shapes from 2D drawings is an important problem with applications in content creation for computer animation and virtual reality. We introduce a new sketch-based system, CreatureShop, that enables amateurs to create high-quality textured 3D character models from 2D drawings with ease and efficiency. CreatureShop takes an input bitmap drawing of a character (such as an animal or other creature), depicted from an arbitrary descriptive pose and viewpoint, and creates a 3D shape with plausible geometric details and textures from a small number of user annotations on the 2D drawing. Our key contributions are a novel oblique view modeling method, a set of systematic approaches for producing plausible textures on the invisible or occluded parts of the 3D character (as viewed from the direction of the input drawing), and a user-friendly interactive system. We validate our system and methods by creating numerous 3D characters from various drawings, and compare our results with related works to show the advantages of our method. We perform a user study to evaluate the usability of our system, which demonstrates that our system is a practical and efficient approach to create fully-textured 3D character models for novice users.

Analysis of the Style Characteristics of National Dance Based on 3D Reconstruction.

National dance is an important symbol of national spiritual culture, as it embodies each nation's unique history, living habits, ideology, and culture. Many Chinese ethnic groups have developed their own dance forms and styles, each with their own set of charms. Strengthening our understanding of its style and characteristics is critical to our understanding of the national dance. To begin with, this paper proposes a patch-based multiview stereo reconstruction scheme that can accurately reconstruct 3D character models. The movement capture system then collects national dance movement data and uses them to drive a three-dimensional character model that generates dance visual animation. In the human skeleton model, a spatial-temporal HMM (hidden Markov model) is proposed that not only studies the temporal information of human movements but also the spatial information of adjacent connection points. The recognition rate of this algorithm increases to 95.68 percent when the number of setting points is increased to ten and to 98.28 percent when the number of setting points is increased to twenty, according to the research. The experimental results show that the 3D reconstruction model of ethnic dance developed in this paper is capable of meeting the goal of ethnic dance digitalization while being simple to use, being low in cost, and with a good display effect.

Analysis and Prediction of Microblog Hot Topics Propagation Based on Deep Learning

Sina Microblog, China’s most popular social media platform, has a massive amount of data and users. The prediction of microblog forwarding has become a hot research topic in the current academic circle. The majority of current microblog forwarding research relies on traditional models that only use certain data properties or statistical features akin to term frequency-inverse document frequency (TF-IDF) for training but fail to extract microblog semantic-level information. In light of the popularity of evolutionary analysis and forecasting your own research only on particular moment popularity or predict popularity, finally, we only analyzed the influence of different factors on the final popularity, without considering the various factors in the popularity of the role played by different evolutionary stages and the popularity of evolutionary problems such as insufficient understanding. This article proposes a three-dimensional feature model. Average, trend, and cycle were used to fit and predict the prevalence, as well as the prevalence prediction method based on deep learning. We analyzed the hot topic evolvement popularity and defined a 3D character model. Regarding average, trend, and cycle and based on 3D feature model to create time series model to fit hot subject popularity evolution and forecast the short-term popularity of hot topic evolution, comparing Spike M and SH model, this work puts forward the model fit and greater accuracy. From the analysis and quantification of influencing factors in the three key stages of epidemic evolution, outbreak, peak, and decline, a prediction model of the epidemic based on a deep neural network was proposed, the different effects of each influencing factor in the evolution process of the epidemic were analyzed in detail, and the active period of the epidemic was predicted. In comparison with the Spike M and SVR models, the proposed technique has a greater effect and performance in terms of predictability and timeliness.

Real-time deep dynamic characters

We propose a deep videorealistic 3D human character model displaying highly realistic shape, motion, and dynamic appearance learned in a new weakly supervised way from multi-view imagery. In contrast to previous work, our controllable 3D character displays dynamics, e.g., the swing of the skirt, dependent on skeletal body motion in an efficient data-driven way, without requiring complex physics simulation. Our character model also features a learned dynamic texture model that accounts for photo-realistic motion-dependent appearance details, as well as view-dependent lighting effects. During training, we do not need to resort to difficult dynamic 3D capture of the human; instead we can train our model entirely from multi-view video in a weakly supervised manner. To this end, we propose a parametric and differentiable character representation which allows us to model coarse and fine dynamic deformations, e.g., garment wrinkles, as explicit spacetime coherent mesh geometry that is augmented with high-quality dynamic textures dependent on motion and view point. As input to the model, only an arbitrary 3D skeleton motion is required, making it directly compatible with the established 3D animation pipeline. We use a novel graph convolutional network architecture to enable motion-dependent deformation learning of body and clothing, including dynamics, and a neural generative dynamic texture model creates corresponding dynamic texture maps. We show that by merely providing new skeletal motions, our model creates motion-dependent surface deformations, physically plausible dynamic clothing deformations, as well as video-realistic surface textures at a much higher level of detail than previous state of the art approaches, and even in real-time.

Real-time deep dynamic characters

We propose a deep videorealistic 3D human character model displaying highly realistic shape, motion, and dynamic appearance learned in a new weakly supervised way from multi-view imagery. In contrast to previous work, our controllable 3D character displays dynamics, e.g., the swing of the skirt, dependent on skeletal body motion in an efficient data-driven way, without requiring complex physics simulation. Our character model also features a learned dynamic texture model that accounts for photo-realistic motion-dependent appearance details, as well as view-dependent lighting effects. During training, we do not need to resort to difficult dynamic 3D capture of the human; instead we can train our model entirely from multi-view video in a weakly supervised manner. To this end, we propose a parametric and differentiable character representation which allows us to model coarse and fine dynamic deformations, e.g., garment wrinkles, as explicit spacetime coherent mesh geometry that is augmented with high-quality dynamic textures dependent on motion and view point. As input to the model, only an arbitrary 3D skeleton motion is required, making it directly compatible with the established 3D animation pipeline. We use a novel graph convolutional network architecture to enable motion-dependent deformation learning of body and clothing, including dynamics, and a neural generative dynamic texture model creates corresponding dynamic texture maps. We show that by merely providing new skeletal motions, our model creates motion-dependent surface deformations, physically plausible dynamic clothing deformations, as well as video-realistic surface textures at a much higher level of detail than previous state of the art approaches, and even in real-time.

Animation of virtual medical system under the background of virtual reality technology

AbstractVirtual reality technology is a technology that uses a variety of scientific technologies such as computer systems, image displays, and sensors to perform human–computer interaction. Since the advent of virtual reality technology, the virtual reality + medical model has been highly expected. At present, three‐dimensional (3D) animation technology can be used in combination with virtual reality technology in medical systems. 3D animation technology can transform the transformed human medical image into a 3D character model, and animate the corresponding bones, and observe the model on the screen and operate the model like real surgery, completing virtual medical content learning, virtual medical skill training, virtual surgery preview. Applying 3D animation technology to virtual reality surgery training can effectively bypass the limitations of traditional surgery training modes, form multiple interactive real‐time effects, and bring a rich perceptual experience to the audience. Based on the above background, the research content of this article is the study of virtual medical system animation under the background of virtual reality technology. This paper analyzes the feasibility of virtual reality technology and 3D animation modeling, and designs a virtual medical system based on this. Finally, through experimental simulations, the results show that the gap h is getting larger and larger after the first approximation, and the gap between the Euler explicit method and the true value is larger, while the implicit method is more stable, and the gap does not increases too quickly with the increase of h. Hence choosing the implicit method to calculate Δt to obtain a larger value will not affect the stability of the solution.

Augmented Reality Character Topeng Malang Dewi as an Effort to Improve the Quality of Student Learning Media

The preservation of the cultural and artistic heritage of our ancestors is important for us to persevere as a species. The purpose of this research was to introduce Indonesian culture, especially Topeng Malang, to the Indonesian society, particularly the teenagers, using 3D character media, implemented through augmented reality. The study followed the development research method of Borg WR and Gall MD. 3D characters were designed using the low poly subdivision surface technique, with a minimum number of poly but maintaining the detail of the character. Based on the results of the data analysis, the following essential points were obtained: (1) The character design of the Topeng Malang adopted the figures of Dewi Sekartaji and Dewi Walangwati. (2) The character design of the Topeng Malang character represented the posture, nature, and characteristics of the style. The result of this design was the implementation of 3-dimensional masks and character transformation in augmented reality media. Based on the results and the questionnaires used by the author to gather users’ knowledge of the character shape of the augmented reality media of the mask, 49.3% of the responses were found to be very good and 46.4% good. These results certainly add to the positive values of utilizing the 3D character media as a medium to introduce Wayang Topeng Malangan.
 Keywords: Topeng Malang, 3D character model

Sketch-based Synthesis of Facial Expression for 3D Character Models

CGによる3Dキャラクタの表現は映画やアニメ，ゲームなど多くの場面で用いられており，感情の表現や自然な演出のために表情アニメーションが実現されている．しかし，そのような自然な表情の生成は容易ではなく，手作業により時間をかけて作成しているのが現状である．そのため，その作業を軽減する手法が数多く開発されている．しかし，それらの各手法は3Dソフトに関する知識や技術を熟知していなければ，思い通りの表情を作成することは難しい．そこで本研究では，ユーザにより与えられる2Dスケッチから3Dキャラクタの表情を生成する手法を提案する．ユーザは，目的とする口や目の形をスケッチとして与えるだけで，3Dモデルを操作することなく，さまざまな表情を作成することができる．

A Virtual Reality Simulation Method for Crowd Evacuation in a Multiexit Indoor Fire Environment

Evacuation simulations in virtual indoor fire scenes hold great significance for public safety. However, existing evacuation simulation methods are inefficient and provide poor visualized when applied to virtual reality (VR) simulations. Additionally, the influences of the interaction of evacuation processes on the choice of multiple exits have not been fully considered. In the paper, we propose a VR simulation method for crowd evacuation in a multiexit indoor fire environment. An indoor 3D scene model and character model, for studying the environmental factors that affect the multiexit selection of personnel during the fire process, are combined with environmental factors to enhance the evacuation route planning algorithm to improve the efficiency of the VR simulation of evacuation in the scene. In addition, a prototype system that supports multiple experience modes is proposed, and case experiment analyses are performed. The results show that the method described in this paper can effectively support the real-time simulation of indoor fire evacuations in virtual scenes, providing both reliable simulation results and good visualization effects.

Exploring 3D Character Modeling Technique in Malaysian Short Animated Film

Exploring 3D Character Modeling Technique in Malaysian Short Animated Film

Applying augmented reality in physical education on motor skills learning

ABSTRACT Physical education is a course that integrates knowledge of sports with skill drilling. Augmented Reality (AR)-assisted instruction has infrequently been applied in sport skill drilling. Video-assisted instruction has frequently applied to physical sports; however, it neither involves interactive practice nor embodies both textbook learning and the practice of sporting skills simultaneously. As a complement to video-assisted instruction, AR can apply virtual messages to learning objects so that 3-dimensional models can be superimposed into textbooks, which allows learners to read books while operating 3D character models. To verify the effects of learning outcomes, motor skills, and learning motivation with AR-assisted instruction and the effects of different difficulty levels on instruction materials, two experimental studies were implemented. Simple and basic running actions and more difficult Mark exercise actions were chosen as the teaching content. The experiments adopted a quasi-experimental design. The findings indicate that AR-assisted instruction is more effective than video-assisted instruction, and the effects are better for more difficult motor skills learning.

3D modeling and animating of characters in educational game

Bahasa is an identity of the Indonesian nation which grow very fast for the unifying tool of ethnic groups so that it can increase of foreigners’ interest in learning Bahasa as a tool to achieve, politics, trade, art and culture, and tourism goals. Many foreigners want to learn Bahasa Indonesia by the following program of BIPA (Bahasa Indonesia untuk Penutur Asing). However, the learning program of BIPA class is still conventional. Games can be used as an alternative educational media for BIPA learning in changing conventional learning methods so that they can visualize real problems. An Android-based game called “Asiknya Berbahasa” is an educational game of BIPA basic level material which has 3 stages; easy, medium and difficult stage and be completed with 3D character models along with the animation. 3D modeling and character animation referring to the Game Development Life Cycle (GDLC) method consists of several stages of initiation, pre-production, production, testing, beta, and release. Testing on 3D models and character animation using a Likert scale shows approval of the average value result test

Research and application of personalized human body simplification and fusion method

In crowd simulation, 3D (three-dimensional) character modeling is an important topic since the appropriate character models are helpful to improve the efficiency and realism of crowd simulation. The reconstructed 3D character model based on Kinect has a strong sense of reality and low cost. However, these models are all complex and cannot be applied to large-scale crowd simulation directly. In this paper, we propose a novel personalized human body modeling method for mass crowd simulation based on Kinect. The human modeling process is divided into head modeling and torso modeling, and then they are fused into each other to build a personalized human body model. This method can be divided into two parts: In the first part, a simplified method is presented based on edge curvature and area of error. In addition, to preserve the detail characteristics of model, the way of interactive operation is introduced. In the second part, the automatic fusion for the simplified head model and body model is made by using the improved FCF (fusion control function) fusion method. Finally, a hierarchical database for the personalized human body models is built. The experiment results show that the method proposed in this paper has high efficiency and good robustness in practical applications.

Gesture3D

Artists routinely use gesture drawings to communicate ideated character poses for storyboarding and other digital media. During subsequent posing of the 3D character models, they use these drawing as a reference, and perform the posing itself using 3D interfaces which require time and expert 3D knowledge to operate. We propose the first method for automatically posing 3D characters directly using gesture drawings as an input, sidestepping the manual 3D posing step. We observe that artists are skilled at quickly and effectively conveying poses using such drawings, and design them to facilitate a single perceptually consistent pose interpretation by viewers. Our algorithm leverages perceptual cues to parse the drawings and recover the artist-intended poses. It takes as input a vector-format rough gesture drawing and a rigged 3D character model, and plausibly poses the character to conform to the depicted pose. No other input is required. Our contribution is two-fold: we first analyze and formulate the pose cues encoded in gesture drawings; we then employ these cues to compute a plausible image space projection of the conveyed pose and to imbue it with depth. Our framework is designed to robustly overcome errors and inaccuracies frequent in typical gesture drawings. We exhibit a wide variety of character models posed by our method created from gesture drawings of complex poses, including poses with occlusions and foreshortening. We validate our approach via result comparisons to artist-posed models generated from the same reference drawings, via studies that confirm that our results agree with viewer perception, and via comparison to algorithmic alternatives.

3D Character Animation: A Brief Review

The Augmented Reality (AR) and Virtual Reality (VR) tech -nologies provide many contents that we can barely experience in reality. Further, the developments in performance of comput-er and GPU are based on putting virtual environment into our reality efficiently. The core technologies in developing contents of AR and VR are 3D character modeling and 3D character ani -mation. These are used in various areas such as 3D film, game industry, Physics, Medical simulation and Educational contents. In this review, we discuss the method of animating contents in the virtual reality. There are two topics of 3D character animation, namely, Fa-cial animation and Body animation. Facial animation implies the representation of natural facial expressions. There are two methods of producing this type of animation. One is the Geom-etry-based approach which is based on control point in 3D char-acter face mesh and the other is Blend shape model-based ap-proach which utilizes 3D facial expression template blending. The tree-structured skeleton is usually used for animating body motion. In addition, to achieve more realistic character move-ments, not only physics but also non-rigid deformation of skin or clothes are adopted. In this paper, we discuss Geometry- and Blend shape model-based of facial animation as well as Skeleton- and Physics-based of body animation.

Efficient sketch‐based creation of detailed character models through data‐driven mesh deformations

AbstractCreation of detailed character models is a very challenging task in animation production. Sketch‐based character model creation from a 3D template provides a promising solution. However, how to quickly find correct correspondences between user's drawn sketches and the 3D template model, how to efficiently deform the 3D template model to exactly match user's drawn sketches, and realize real‐time interactive modeling is still an open topic. In this paper, we propose a new approach and develop a user interface to effectively tackle this problem. Our proposed approach includes using user's drawn sketches to retrieve a most similar 3D template model from our dataset and marrying human's perception and interactions with computer's highly efficient computing to extract occluding and silhouette contours of the 3D template model and find correct correspondences quickly. We then combine skeleton‐based deformation and mesh editing to deform the 3D template model to fit user's drawn sketches and create new and detailed 3D character models. The results presented in this paper demonstrate the effectiveness and advantages of our proposed approach and usefulness of our developed user interface. Copyright © 2015 John Wiley & Sons, Ltd.

Online motion synthesis using sequential Monte Carlo

We present a Model-Predictive Control (MPC) system for online synthesis of interactive and physically valid character motion. Our system enables a complex (36-DOF) 3D human character model to balance in a given pose, dodge projectiles, and improvise a get up strategy if forced to lose balance, all in a dynamic and unpredictable environment. Such contact-rich, predictive and reactive motions have previously only been generated offline or using a handcrafted state machine or a dataset of reference motions, which our system does not require. For each animation frame, our system generates trajectories of character control parameters for the near future --- a few seconds --- using Sequential Monte Carlo sampling. Our main technical contribution is a multimodal, tree-based sampler that simultaneously explores multiple different near-term control strategies represented as parameter splines. The strategies represented by each sample are evaluated in parallel using a causal physics engine. The best strategy, as determined by an objective function measuring goal achievement, fluidity of motion, etc., is used as the control signal for the current frame, but maintaining multiple hypotheses is crucial for adapting to dynamically changing environments.

Animation of 3D Human Model Using Markerless Motion Capture Applied To Sports

Markerless motion capture is an active research in 3D virtualization. In proposed work we presented a system for markerless motion capture for 3D human character animation, paper presents a survey on motion and skeleton tracking techniques which are developed or are under development. The paper proposed a method to transform the motion of a performer to a 3D human character (model), the 3D human character performs similar movements as that of a performer in real time. In the proposed work, human model data will be captured by Kinect camera, processed data will be applied on 3D human model for animation. 3D human model is created using open source software (MakeHuman). Anticipated dataset for sport activity is considered as input which can be applied to any HCI application.