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Image-based three-dimensional model reconstruction for Chinese treasure-Jadeite Cabbage with Insects

机译:基于图像的昆虫珍宝白菜三维模型重构

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摘要

This paper presents a novel 3D reconstruction system for the famous Chinese treasure, Jadeite Cabbage with Insects, from uncalibrated image sequences. There are two major challenges for this 3D model reconstruction problem. The first is the difficult image registration problem due to the semi-diaphaneity and the highly specular property of jadeite materials. Secondly, the unknown camera information, including the intrinsic (calibration) and extrinsic (position and orientation) parameters, to be recovered from the uncalibrated image sequences makes the 3D reconstruction problem very challenging. The proposed 3D modeling process first recovers the camera information as well as sparse 3D structure by using a robust structure from motion algorithm. Then an approximate 3D object model is recovered from the silhouettes at the corresponding multiple views by using the visual hull technique. The final process refines the 3D model by further integrating the 3D information extracted from dense correspondences between image patches of different views. In the proposed 3D reconstruction system, we successfully combine the structure from motion and visual hull techniques to accomplish this challenging task of reconstructing an accurate 3D model for jadeite object from uncalibrated multi-view images. Finally, we assess the 3D reconstruction results for the Chinese jadeite treasure and simulated data by using the proposed 3D reconstruction system.
机译:本文从未经校准的图像序列中,提出了一种新颖的3D重建系统,用于著名的中国珍宝“带昆虫的白菜”。此3D模型重建问题有两个主要挑战。首先是由于翡翠材料的半透明性和高镜面性质而导致的图像配准困难。其次,要从未校准的图像序列中恢复的未知相机信息(包括固有(校准)和外部(位置和方向)参数)使3D重构问题非常具有挑战性。所提出的3D建模过程首先通过使用运动算法中的稳健结构来恢复相机信息以及稀疏3D结构。然后,通过使用视觉外壳技术从对应的多个视图处的轮廓中恢复近似的3D对象模型。最终过程通过进一步集成从不同视图的图像块之间的密集对应关系中提取的3D信息来完善3D模型。在提出的3D重建系统中,我们成功地结合了运动和视觉船体技术的结构,以完成这项艰巨的任务,即从未经校准的多视图图像中为玉器对象重建准确的3D模型。最后,我们使用提出的3D重建系统评估中国翡翠宝藏的3D重建结果和模拟数据。

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