Computer Animation and Virtual Worlds最新文献

Body Part Segmentation of Anime Characters

IF 0.9 4区计算机科学

Computer Animation and Virtual Worlds Pub Date : 2024-12-17 DOI: 10.1002/cav.2295

Zhenhua Ou, Xueting Liu, Chengze Li, Zhenkun Wen, Ping Li, Zhijian Gao, Huisi Wu

{"title":"Body Part Segmentation of Anime Characters","authors":"Zhenhua Ou, Xueting Liu, Chengze Li, Zhenkun Wen, Ping Li, Zhijian Gao, Huisi Wu","doi":"10.1002/cav.2295","DOIUrl":"https://doi.org/10.1002/cav.2295","url":null,"abstract":"<div>\u0000 \u0000 <p>Semantic segmentation is an important approach to present the perceptual semantic understanding of an image, which is of significant usage in various applications. Especially, body part segmentation is designed for segmenting body parts of human characters to assist different editing tasks, such as style editing, pose transfer, and animation production. Since segmentation requires pixel-level precision in semantic labeling, classic heuristics-based methods generally have unstable performance. With the deployment of deep learning, a great step has been taken in segmenting body parts of human characters in natural photographs. However, the existing models are purely trained on natural photographs and generally obtain incorrect segmentation results when applied on anime character images, due to the large visual gap between training data and testing data. In this article, we present a novel approach to achieving body part segmentation of cartoon characters via a pose-based graph-cut formulation. We demonstrate the use of the acquired body part segmentation map in various image editing tasks, including conditional generation, style manipulation, pose transfer, and video-to-anime.</p>\u0000 </div>","PeriodicalId":50645,"journal":{"name":"Computer Animation and Virtual Worlds","volume":"35 6","pages":""},"PeriodicalIF":0.9,"publicationDate":"2024-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142861507","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Fast and Incremental 3D Model Renewal for Urban Scenes With Appearance Changes

IF 0.9 4区计算机科学

Computer Animation and Virtual Worlds Pub Date : 2024-12-11 DOI: 10.1002/cav.70004

Yuan Xiong, Zhong Zhou

引用次数: 0

Diverse Motions and Responses in Crowd Simulation 人群模拟中的各种运动和反应

IF 0.9 4区计算机科学

Computer Animation and Virtual Worlds Pub Date : 2024-11-26 DOI: 10.1002/cav.70002

Yiwen Ma, Tingting Liu, Zhen Liu

{"title":"Diverse Motions and Responses in Crowd Simulation","authors":"Yiwen Ma, Tingting Liu, Zhen Liu","doi":"10.1002/cav.70002","DOIUrl":"https://doi.org/10.1002/cav.70002","url":null,"abstract":"<div>\u0000 \u0000 <p>A challenge in crowd simulation is to generate diverse pedestrian motions in virtual environments. Nowadays, there is a greater emphasis on the diversity and authenticity of pedestrian movements in crowd simulation, while most traditional models primarily focus on collision avoidance and motion continuity. Recent studies have enhanced realism through data-driven approaches that exploit the movement patterns of pedestrians from real data for trajectory prediction. However, they have not taken into account the body-part motions of pedestrians. Differing from these approaches, we innovatively utilize learning-based character motion and physics animation to enhance the diversity of pedestrian motions in crowd simulation. The proposed method can provide a promising avenue for more diverse crowds and is realized by a novel framework that deeply integrates motion synthesis and physics animation with crowd simulation. The framework consists of three main components: the learning-based motion generator, which is responsible for generating diverse character motions; the hybrid simulation, which ensures the physical realism of pedestrian motions; and the velocity-based interface, which assists in integrating navigation algorithms with the motion generator. Experiments have been conducted to verify the effectiveness of the proposed method in different aspects. The visual results demonstrate the feasibility of our approach.</p>\u0000 </div>","PeriodicalId":50645,"journal":{"name":"Computer Animation and Virtual Worlds","volume":"35 6","pages":""},"PeriodicalIF":0.9,"publicationDate":"2024-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142737568","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Facial Motion Retargeting Pipeline for Appearance Agnostic 3D Characters 面向外观无关 3D 角色的面部运动重定位管道

IF 0.9 4区计算机科学

Computer Animation and Virtual Worlds Pub Date : 2024-11-19 DOI: 10.1002/cav.70001

ChangAn Zhu, Chris Joslin

{"title":"A Facial Motion Retargeting Pipeline for Appearance Agnostic 3D Characters","authors":"ChangAn Zhu, Chris Joslin","doi":"10.1002/cav.70001","DOIUrl":"https://doi.org/10.1002/cav.70001","url":null,"abstract":"<p>3D facial motion retargeting has the advantage of capturing and recreating the nuances of human facial motions and speeding up the time-consuming 3D facial animation process. However, the facial motion retargeting pipeline is limited in reflecting the facial motion's semantic information (i.e., meaning and intensity), especially when applied to nonhuman characters. The retargeting quality heavily relies on the target face rig, which requires time-consuming preparation such as 3D scanning of human faces and modeling of blendshapes. In this paper, we propose a facial motion retargeting pipeline aiming to provide fast and semantically accurate retargeting results for diverse characters. The new framework comprises a target face parameterization module based on face anatomy and a compatible source motion interpretation module. From the quantitative and qualitative evaluations, we found that the proposed retargeting pipeline can naturally recreate the expressions performed by a motion capture subject in equivalent meanings and intensities, such semantic accuracy extends to the faces of nonhuman characters without labor-demanding preparations.</p>","PeriodicalId":50645,"journal":{"name":"Computer Animation and Virtual Worlds","volume":"35 6","pages":""},"PeriodicalIF":0.9,"publicationDate":"2024-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cav.70001","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142674057","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Enhancing Front-End Security: Protecting User Data and Privacy in Web Applications 加强前端安全：在网络应用程序中保护用户数据和隐私

IF 0.9 4区计算机科学

Computer Animation and Virtual Worlds Pub Date : 2024-11-13 DOI: 10.1002/cav.70003

Oleksandr Tkachenko, Vadim Goncharov, Przemysław Jatkiewicz

{"title":"Enhancing Front-End Security: Protecting User Data and Privacy in Web Applications","authors":"Oleksandr Tkachenko, Vadim Goncharov, Przemysław Jatkiewicz","doi":"10.1002/cav.70003","DOIUrl":"https://doi.org/10.1002/cav.70003","url":null,"abstract":"<div>\u0000 \u0000 <p>Conducting research on this subject remains relevant in light of the rapid development of technology and the emergence of new threats in cybersecurity, requiring constant updating of knowledge and protection methods. The purpose of the study is to identify effective front-end security methods and technologies that help ensure the protection of user data and their privacy when using web applications or sites. A methodology that defines the steps and processes for effective front-end security and user data protection is developed. The research identifies the primary security threats, including cross-site scripting (XSS), cross-site request forgery (CSRF), and SQL injections, and evaluates existing front-end security methods such as Content Security Policy (CSP), HTTPS, authentication, and authorization mechanisms. The findings highlight the effectiveness of these measures in mitigating security risks, providing a clear assessment of their advantages and limitations. Key recommendations for developers include the integration of modern security protocols, regular updates, and comprehensive security training. This study offers practical insights to improve front-end security and enhance user data protection in an evolving digital landscape.</p>\u0000 </div>","PeriodicalId":50645,"journal":{"name":"Computer Animation and Virtual Worlds","volume":"35 6","pages":""},"PeriodicalIF":0.9,"publicationDate":"2024-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142641927","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Virtual Roaming of Cultural Heritage Based on Image Processing 基于图像处理的文化遗产虚拟漫游

IF 0.9 4区计算机科学

Computer Animation and Virtual Worlds Pub Date : 2024-11-10 DOI: 10.1002/cav.70000

Junzhe Chen, Xing She, Yuanxin Fan, Wenwen Shao

引用次数: 0

PainterAR: A Self-Painting AR Interface for Mobile Devices PainterAR：移动设备的自绘 AR 界面

IF 0.9 4区计算机科学

Computer Animation and Virtual Worlds Pub Date : 2024-11-07 DOI: 10.1002/cav.2296

Yuan Ma, Yinghan Shi, Lizhi Zhao, Xuequan Lu, Been-Lirn Duh, Meili Wang

{"title":"PainterAR: A Self-Painting AR Interface for Mobile Devices","authors":"Yuan Ma, Yinghan Shi, Lizhi Zhao, Xuequan Lu, Been-Lirn Duh, Meili Wang","doi":"10.1002/cav.2296","DOIUrl":"https://doi.org/10.1002/cav.2296","url":null,"abstract":"<div>\u0000 \u0000 <p>Painting is a complex and creative process that involves the use of various drawing skills to create artworks. The concept of training artificial intelligence models to imitate this process is referred to as neural painting. To enable ordinary people to engage in the process of painting, we propose PainterAR, a novel interface that renders any paintings stroke-by-stroke in an immersive and realistic augmented reality (AR) environment. PainterAR is composed of two components: the neural painting model and the AR interface. Regarding the neural painting model, unlike previous models, we introduce the Kullback–Leibler divergence to replace the original Wasserstein distance existed in the baseline paint transformer model, which solves an important problem of encountering different scales of strokes (big or small) during painting. We then design an interactive AR interface, which allows users to upload an image and display the creation process of the neural painting model on the virtual drawing board. Experiments demonstrate that the paintings generated by our improved neural painting model are more realistic and vivid than previous neural painting models. The user study demonstrates that users prefer to control the painting process interactively in our AR environment.</p>\u0000 </div>","PeriodicalId":50645,"journal":{"name":"Computer Animation and Virtual Worlds","volume":"35 6","pages":""},"PeriodicalIF":0.9,"publicationDate":"2024-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142641515","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Decoupled Edge Physics Algorithms for Collaborative XR Simulations 用于 XR 协作模拟的解耦边缘物理算法

IF 0.9 4区计算机科学

Computer Animation and Virtual Worlds Pub Date : 2024-11-03 DOI: 10.1002/cav.2294

George Kokiadis, Antonis Protopsaltis, Michalis Morfiadakis, Nick Lydatakis, George Papagiannakis

{"title":"Decoupled Edge Physics Algorithms for Collaborative XR Simulations","authors":"George Kokiadis, Antonis Protopsaltis, Michalis Morfiadakis, Nick Lydatakis, George Papagiannakis","doi":"10.1002/cav.2294","DOIUrl":"https://doi.org/10.1002/cav.2294","url":null,"abstract":"<div>\u0000 \u0000 <p>This work proposes a novel approach to transform any modern game engine pipeline, for optimized performance and enhanced user experiences in extended reality (XR) environments decoupling the physics engine from the game engine pipeline and using a client-server <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mi>N</mi>\u0000 <mo>−</mo>\u0000 <mn>1</mn>\u0000 </mrow>\u0000 <annotation>$$ N-1 $$</annotation>\u0000 </semantics></math> architecture creates a scalable solution, efficiently serving multiple graphics clients on head-mounted displays (HMDs) with a single physics engine on edge-cloud infrastructure. This approach ensures better synchronization in multiplayer scenarios without introducing overhead in single-player experiences, maintaining session continuity despite changes in user participation. Relocating the Physics Engine to an edge or cloud node reduces strain on local hardware, dedicating more resources to high-quality rendering and unlocking the full potential of untethered HMDs. We present four algorithms that decouple the physics engine, increasing frame rates and Quality of Experience (QoE) in VR simulations, supporting advanced interactions, numerous physics objects, and multiuser sessions with over 100 concurrent users. Incorporating a Geometric Algebra interpolator reduces inter-calls between dissected parts, maintaining QoE and easing network stress. Experimental validation, with more than 100 concurrent users, 10,000 physics objects, and softbody simulations, confirms the technical viability of the proposed architecture, showcasing transformative capabilities for more immersive and collaborative XR applications without compromising performance.</p>\u0000 </div>","PeriodicalId":50645,"journal":{"name":"Computer Animation and Virtual Worlds","volume":"35 6","pages":""},"PeriodicalIF":0.9,"publicationDate":"2024-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142579688","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

VTSIM: Attention-Based Recurrent Neural Network for Intersection Vehicle Trajectory Simulation VTSIM：用于交叉路口车辆轨迹模拟的基于注意力的递归神经网络

IF 0.9 4区计算机科学

Computer Animation and Virtual Worlds Pub Date : 2024-11-03 DOI: 10.1002/cav.2298

Jingyao Liu, Tianlu Mao, Zhaoqi Wang

{"title":"VTSIM: Attention-Based Recurrent Neural Network for Intersection Vehicle Trajectory Simulation","authors":"Jingyao Liu, Tianlu Mao, Zhaoqi Wang","doi":"10.1002/cav.2298","DOIUrl":"https://doi.org/10.1002/cav.2298","url":null,"abstract":"<div>\u0000 \u0000 <p>Simulating vehicle trajectories at intersections is one of the challenging tasks in traffic simulation. Existing methods are often ineffective due to the complexity and diversity of lane topologies at intersections, as well as the numerous interactions affecting vehicle motion. To address this issue, we propose a deep learning based vehicle trajectory simulation method. First, we employ a vectorized representation to uniformly extract features from traffic elements such as pedestrians, vehicles, and lanes. By fusing all factors that influence vehicle motion, this representation makes our method suitable for a variety of intersections. Second, we propose a deep learning model, which has an attention network to dynamically extract features from the surrounding environment of the vehicles. To address the issue of vehicles continuously entering and exiting the simulation scene, we employ an asynchronous recurrent neural network for the extraction of temporal features. Comparative evaluations against existing rule-based and deep learning-based methods demonstrate our model's superior simulation accuracy. Furthermore, experimental validation on public datasets demonstrates that our model can simulate vehicle trajectories among the urban intersections with different topologies including those not present in the training dataset.</p>\u0000 </div>","PeriodicalId":50645,"journal":{"name":"Computer Animation and Virtual Worlds","volume":"35 6","pages":""},"PeriodicalIF":0.9,"publicationDate":"2024-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142579689","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Training Climbing Roses by Constrained Graph Search 通过受限图谱搜索训练攀爬玫瑰

IF 0.9 4区计算机科学

Computer Animation and Virtual Worlds Pub Date : 2024-10-15 DOI: 10.1002/cav.2297

Wataru Umezawa, Tomohiko Mukai

引用次数: 0