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DOI:
Journal of Software:2010.21(zk):165-172

视点选择Benchmark 的设计与应用
杨利明,韩红雷
(中国科学院 软件研究所 计算机科学国家重点实验室,北京 100190; 中国科学院 研究生院,北京 100049;中国科学院 软件研究所 计算机科学国家重点实验室,北京 100190; 中国科学院 研究生院,北京 100049; 中国传媒大学 动画学院,北京 100024)
Viewpoint Selection Benchmark Design and Application
YANG Li-Ming,HAN Hong-Lei
(State Key Laboratory of Computer Science, Institute of Software, The Chinese Academy of Sciences, Beijing 100190, China; Graduate University, The Chinese Academy of Sciences, Beijing 100049, China;State Key Laboratory of Computer Science, Institute of Software, The Chinese Academy of Sciences, Beijing 100190, China; Graduate University, The Chinese Academy of Sciences, Beijing 100049, China; Animation School, Communication University of China, Beij)
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Received:July 20, 2010    Revised:November 03, 2010
> 中文摘要: 视点选择是图形学的一个重要研究方向,它通过分析模型特征,计算得到符合人类观察习惯并包含更多模型重要信息的视点.近年来,人们提出了很多视点选择算法,然而对这些算法结果的评价仍然停留在感性阶段.设计实现了一个视点选择Benchmark,对视点选择结果进行量化分析:首先,采集30 个测试者对45 个模型的视点选择结果,借以确立真人视点选择的基准视点;接着,以基准视点为参考,分析真人视点选择的一致性和稳定性;最后,应用5 个(共3 类)代表性的算法进行视点选择,并比较其结果与基准视点的差别,得到各视点选择算法的质量及时间效率.实验结果表明,真人视点选择整体具有较好的一致性和稳定性,但对不同特征类型模型,一致性的表现有较大差异;已有视点选择算法对45 个测试模型的结果整体差异不大,相对来说,基于互信息的方法和视平面上特征计算的方法较好,各类视点选择算法对不同特征类型模型结果互有优劣.
中文关键词: 视点选择  对比基准
Abstract:Viewpoint selection is an important research field in computer graphics, which analyses a model and generates viewpoints. These viewpoints fit well with human preferences, and contain as much as possible salient model features. But until now, the evaluation of viewpoint selection results has not yet been quantized. This paper designs and implements a quantized viewpoint selection benchmark. At first, it collects human viewpoint selection results of 30 persons observing 45 models, and defines the standard-human-viewpoint of each model according to these results. Then, it analyzes the consistence and stability of human viewpoint selection. At last, it implements five (three kinds) representative viewpoint selection algorithms, analyze and compare their results with standardhuman- viewpoints. It also analyzes the performance differences between each kind of algorithm dealing various types of models. The experimental results show that human viewpoint selection has good consistence and stability, and differs on various types of models. All tested algorithms don’t have great performance difference, but mutual information based method and viewing plane feature measurement method are a little better than others. Each kind of algorithm performs best at different type of models.
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基金项目:Supported by the National Natural Science Foundation of China under Grant Nos.60773026, 60873182, 60833007 (国家自然科学基金) Supported by the National Natural Science Foundation of China under Grant Nos.60773026, 60873182, 60833007 (国家自然科学基金)
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杨利明,韩红雷.视点选择Benchmark 的设计与应用.软件学报,2010,21(zk):165-172

YANG Li-Ming,HAN Hong-Lei.Viewpoint Selection Benchmark Design and Application.Journal of Software,2010,21(zk):165-172