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一个对象数据库的可变形的三维重建
Deformable 3D Reconstruction with an Object Database |
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| 课程网址: |
http://videolectures.net/bmvc2012_alcantarilla_deformable_deconst...
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| 主讲教师: |
Pablo Alcantarilla
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| 开课单位: |
奥弗涅大学
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| 开课时间: |
2012-10-09
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| 课程语种: |
英语
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| 中文简介: |
来自2D图像的可变形3D重建需要关于场景结构的先验知识。无模板方法使用通用的先验知识，例如分段平滑，但需要具有显着基线的多个图像。基于模板的方法仅需要一个图像，但只处理一个他们需要特定先验知识的对象，即3D模板。我们在这里提出了一种新方法，它减轻了无模板和基于模板的方法的强大假设：我们的方法使用多个模板来实现仅从一个图像和多个对象的可变形3D重建。它使用对象识别来自动发现输入图像中可见的对象，并为可变形3D重建选择合适的模板。对象数据库是脱机构建的。至关重要的是，该数据库不仅包含现有对象识别框架中的外观描述符，还包含便于可变形3D重建的材料属性。我们用各种材料制成的物体展示了成功的实验结果，如纸，布和塑料。
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| 课程简介: |
Deformable 3D reconstruction from 2D images requires prior knowledge on the scene structure. Template-free methods use generic prior knowledge such as piecewise smoothness but require multiple images with significant baseline. Template-based methods require only one image but handle only one object for which they need specific prior knowledge, namely a 3D template. We here propose a novel method that alleviates the strong assumptions of both the template-free and template-based methods: our method uses multiple templates to achieve deformable 3D reconstruction from only one image and for multiple objects. It uses object recognition to automatically discover what objects are visible in the input image and to select the appropriate templates for deformable 3D reconstruction. The object database is built offline. Crucially, this database does not only contain appearance descriptors as in existing object recognition frameworks, but also material properties to facilitate deformable 3D reconstruction. We show successful experimental results with objects made of various materials such as paper, cloth and plastic.
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| 关 键 词: |
三维重建; 二维图像; 3D模板; 建立离线; 目标识别框架
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| 课程来源: |
视频讲座网
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| 最后编审: |
2020-06-29：zyk
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| 阅读次数: |
68
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