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首页> 外文会议>Sixth International Conference on Quality Control by Artificial Vision May 19-22, 2003 Gatlinburg, Tennessee, USA >Modeling 3D objects from range maps and color images using a warping - based approach
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Modeling 3D objects from range maps and color images using a warping - based approach

机译：使用基于变形的方法从距离图和彩色图像建模3D对象

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摘要

In this paper we describe a new method for the modeling of objects with known generic shape such as human faces from video and range data. The method combines the strengths of active laser scanning and passive Shape from Motion techniques. Our approach consists of first reconstructing a few feature-points that can be reliably tracked throughout a video sequence of the object. These features are mapped to corresponding 3D points in a generic 3D model reconstructed from dense and accurate range data acquired only once. The resulting 3D-3D set of matches is used to warp the generic model into the actual object visible in the video stream using thin-plate splines interpolation. Our method avoids the problems of dense matching encountered in stereo algorithms. Furthermore, in the case of face reconstruction, this method provides dense models while not requiring the invasive laser scanning of faces.
机译：在本文中，我们描述了一种用于对具有已知通用形状的对象（例如来自视频和距离数据的人脸）进行建模的新方法。该方法结合了主动激光扫描和Motion技术提供的被动Shape的优势。我们的方法包括首先重建几个可以在整个对象视频序列中可靠跟踪的特征点。这些特征被映射到通用3D模型中的相应3D点，该3D模型是从仅获取一次的密集而精确的范围数据中重建的。所得的3D-3D匹配集用于使用薄板样条插值将通用模型变形为视频流中可见的实际对象。我们的方法避免了立体算法中遇到的密集匹配问题。此外，在人脸重建的情况下，该方法可提供密集模型，而无需对人脸进行侵入式激光扫描。

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