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Frontiers of Information Technology & Electronic Engineering
ISSN 2095-9184 (print), ISSN 2095-9230 (online)
2016 Vol.17 No.5 P.422-434
A multiscale-contour-based interpolation framework for generating a time-varying quasi-dense point cloud sequence
Abstract: To speed up the reconstruction of 3D dynamic scenes in an ordinary hardware platform, we propose an efficient framework to reconstruct 3D dynamic objects using a multiscale-contour-based interpolation from multi-view videos. Our framework takes full advantage of spatio-temporal-contour consistency. It exploits the property to interpolate single contours, two neighboring contours which belong to the same model, and two contours which belong to the same view at different times, corresponding to point-, contour-, and model-level interpolations, respectively. The framework formulates the interpolation of two models as point cloud transport rather than non-rigid surface deformation. Our framework speeds up the reconstruction of a dynamic scene while improving the accuracy of point-pairing which is used to perform the interpolation. We obtain a higher frame rate, spatio-temporal-coherence, and a quasi-dense point cloud sequence with color information. Experiments with real data were conducted to test the efficiency of the framework.
Key words: Multi-view video, Free-viewpoint video, Point-pair, Multiscale-contour-based interpolation, Spatio-temporal-contour, Consistency, Time-varying point cloud sequence
创新点:提出基于多尺度轮廓插值生成时变点云模型序列的方法。利用重建对象轮廓的多尺度时空连续性,完成时变三维模型序列的时空维度插值。
方法:首先,采用基于剪影轮廓原理重建物体关键帧的稀疏三维模型。接着,分析三维模型的轮廓点在点级别、轮廓级别、模型级别的连续性,并在该过程中采用距离图插值来增强轮廓的连续性。然后,采用最近点查找方法获得匹配点对,在三个尺度上对匹配点对进行线性密集化。最后,生成具有良好时空一致性的准密集时变三维模型序列。
结论:利用轮廓多尺度时空连续性能够提高重建对象的形变跟踪速度,且时变三维模型序列具有良好的外观质量。
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DOI:
10.1631/FITEE.1500316
CLC number:
TP391.4
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On-line Access:
2024-08-27
Received:
2023-10-17
Revision Accepted:
2024-05-08
Crosschecked:
2016-04-18