An improved loop subdivision to coordinate the smoothness and the number of faces via multi-objective optimization

IF 5.8 2区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Yaqian Liang, Fazhi He, Xiantao Zeng, Jinkun Luo
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引用次数: 55

Abstract

3D mesh subdivision is essential for geometry modeling of complex surfaces, which benefits many important applications in the fields of multimedia such as computer animation. However, in the ordinary adaptive subdivision, with the deepening of the subdivision level, the benefits gained from the improvement of smoothness cannot keep pace with the cost caused by the incremental number of faces. To mitigate the gap between the smoothness and the number of faces, this paper devises a novel improved mesh subdivision method to coordinate the smoothness and the number of faces in a harmonious way. First, this paper introduces a variable threshold, rather than a constant threshold used in existing adaptive subdivision methods, to reduce the number of redundant faces while keeping the smoothness in each subdivision iteration. Second, to achieve the above goal, a new crack-solving method is developed to remove the cracks by refining the adjacent faces of the subdivided area. Third, as a result, the problem of coordinating the smoothness and the number of faces can be formulated as a multi-objective optimization problem, in which the possible threshold sequences constitute the solution space. Finally, the Non-dominated sorting genetic algorithm II (NSGA-II) is improved to efficiently search the Pareto frontier. Extensive experiments demonstrate that the proposed method consistently outperforms existing mesh subdivision methods in different settings.
一种改进的环细分方法,通过多目标优化来协调平滑度和面数
三维网格细分是复杂曲面几何建模的基础,在计算机动画等多媒体领域有着重要的应用。然而,在普通的自适应细分中,随着细分层次的加深,平滑度的提高所带来的收益跟不上人脸数量增加所带来的成本。为了缓解平滑度与面数之间的差距,本文设计了一种改进的网格细分方法,使平滑度与面数协调一致。首先,本文引入可变阈值,以减少冗余面数量,同时保持每次细分迭代的平滑性,而不是现有自适应细分方法中使用的恒定阈值;其次,为了实现上述目标,提出了一种新的裂缝求解方法,通过细化细分区域的相邻面来去除裂缝。第三,将光滑性与面数的协调问题表述为一个多目标优化问题,其中可能的阈值序列构成解空间。最后,改进了非支配排序遗传算法II (NSGA-II),实现了Pareto边界的高效搜索。大量的实验表明,在不同的环境下,该方法始终优于现有的网格细分方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Integrated Computer-Aided Engineering
Integrated Computer-Aided Engineering 工程技术-工程:综合
CiteScore
9.90
自引率
21.50%
发文量
21
审稿时长
>12 weeks
期刊介绍: Integrated Computer-Aided Engineering (ICAE) was founded in 1993. "Based on the premise that interdisciplinary thinking and synergistic collaboration of disciplines can solve complex problems, open new frontiers, and lead to true innovations and breakthroughs, the cornerstone of industrial competitiveness and advancement of the society" as noted in the inaugural issue of the journal. The focus of ICAE is the integration of leading edge and emerging computer and information technologies for innovative solution of engineering problems. The journal fosters interdisciplinary research and presents a unique forum for innovative computer-aided engineering. It also publishes novel industrial applications of CAE, thus helping to bring new computational paradigms from research labs and classrooms to reality. Areas covered by the journal include (but are not limited to) artificial intelligence, advanced signal processing, biologically inspired computing, cognitive modeling, concurrent engineering, database management, distributed computing, evolutionary computing, fuzzy logic, genetic algorithms, geometric modeling, intelligent and adaptive systems, internet-based technologies, knowledge discovery and engineering, machine learning, mechatronics, mobile computing, multimedia technologies, networking, neural network computing, object-oriented systems, optimization and search, parallel processing, robotics virtual reality, and visualization techniques.
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