摘要
在三维动画应用日益广泛的背景下,研究三维动画数据压缩方法对其数据的存储、传播和渲染技术至关重要。基于图像数据的结构化特征,计算机视觉领域提出了一系列高效图像压缩技术。鉴于三维动画数据与图像数据结构的差异,探讨三维动画数据结构化方法,进而探索改进图像算法以实现一种新的三维动画数据压缩方法。具体而言,首先研究对三维模型顶点序列进行优化调整;进而基于图像压缩算法的模块研究动画数据的子块尺寸优化以及图像压缩算法量化矩阵优化方法;最后,通过采用不同类型动画数据进行测试,实验结果表明优化图像压缩算法在压缩比和时效均得到有效提升和保障。
With the increasingly wide applications of 3D animation,the compression methods of 3D animation data have become significant for the technologies in data storage,transmission,and rendering.There are multiple efficient technologies for 2D image compression in the domain of computer vision.Based on the structural differences between t3D animation data and 2D image data,the improvement of the image compression algorithm was explored for a new method of 3D animation compression.Specifically,the optimal vertex sequence of the 3D model towards compression was first computed.Then,based on the classical image compression algorithm flow,the sub-block size optimization and the quantization matrix optimization was formulated to improve compression.Finally,with different types of animation,experimental results show that the optimized image compression algorithm can guarantee both effectiveness and efficiency for the compression.
作者
罗国亮
王贺
赵昕
曹义亲
黄晓生
邬昌兴
冼楚华
LUO Guo-liang;WANG He;ZHAO Xin;CAO Yi-qin;HUANG Xiao-sheng;WU Chang-xing;XIAN Chu-hua(School of Software,East China Jiaotong University,Nanchang Jiangxi 330013,China;School of Computer Science and Engineering,South China University of Technology,Guangzhou Guangdong 510641,China)
出处
《图学学报》
CSCD
北大核心
2021年第2期182-189,共8页
Journal of Graphics
基金
国家自然科学基金项目(61962021)
江西省自然科学基金重点项目(20202ACBL202008)
中国博士后科学基金(2020T130264)
江西省研究生创新专项资金项目(YC2020-S353)。
关键词
压缩
三维动画
图像压缩算法
聚类
离散卷积变换系数
compression
3D animation
image compression algorithm
clustering
discrete convolution transform coefficients