摘要翻译:
在平面和空间中,我们对3个点和3个正射相机进行了非线性Ullman变换的反演。当Ullman定理保证了3个摄像机和4个点的唯一模反射重建时,我们发现了3个摄像机和3个点的局部唯一重建。显式重建公式允许判断三个摄像机看到三个点的图像数据是否可以实现为点-摄像机配置。
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英文标题:
《On Ullman's theorem in computer vision》
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作者:
Oliver Knill and Jose Ramirez-Herran
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最新提交年份:
2007
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分类信息:
一级分类:Computer Science 计算机科学
二级分类:Computer Vision and Pattern Recognition 计算机视觉与模式识别
分类描述:Covers image processing, computer vision, pattern recognition, and scene understanding. Roughly includes material in ACM Subject Classes I.2.10, I.4, and I.5.
涵盖图像处理、计算机视觉、模式识别和场景理解。大致包括ACM课程I.2.10、I.4和I.5中的材料。
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一级分类:Computer Science 计算机科学
二级分类:Artificial Intelligence 人工智能
分类描述:Covers all areas of AI except Vision, Robotics, Machine Learning, Multiagent Systems, and Computation and Language (Natural Language Processing), which have separate subject areas. In particular, includes Expert Systems, Theorem Proving (although this may overlap with Logic in Computer Science), Knowledge Representation, Planning, and Uncertainty in AI. Roughly includes material in ACM Subject Classes I.2.0, I.2.1, I.2.3, I.2.4, I.2.8, and I.2.11.
涵盖了人工智能的所有领域,除了视觉、机器人、机器学习、多智能体系统以及计算和语言(自然语言处理),这些领域有独立的学科领域。特别地,包括专家系统,定理证明(尽管这可能与计算机科学中的逻辑重叠),知识表示,规划,和人工智能中的不确定性。大致包括ACM学科类I.2.0、I.2.1、I.2.3、I.2.4、I.2.8和I.2.11中的材料。
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英文摘要:
Both in the plane and in space, we invert the nonlinear Ullman transformation for 3 points and 3 orthographic cameras. While Ullman's theorem assures a unique reconstruction modulo a reflection for 3 cameras and 4 points, we find a locally unique reconstruction for 3 cameras and 3 points. Explicit reconstruction formulas allow to decide whether picture data of three cameras seeing three points can be realized as a point-camera configuration.
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PDF链接:
https://arxiv.org/pdf/0708.2438


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