A single-shot structured light means by encoding both color and geometrical features
A single-shot structured light means by encoding both color and geometrical features
复制标题
单次结构光意味着通过编码颜色和几何特征
DOI：
10.1016/j.patcog.2015.12.013
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发表时间：
2016-06
影响因子：
8
通讯作者：
Song Zhan
中科院分区：
文献类型：
--
作者：
Lin Haibo;Nie Lei;Song Zhan
彩色编码结构光是实现单次三维重建的重要手段。本文提出了一种基于伪随机阵列的结构光方法。所提出的图案由四种颜色组成，并在颜色元素上嵌入一个几何形状，将编码元素从四个扩展到八个。结果，可以获得大小为2×2的相对较小的编码窗口。每两个相邻阵列元素之间的网格点被定义为阵列特征。提出了一种改进的特征检测器，以实现稳健、准确的网格点定位。将网格点分为两种类型，并用拓扑结构表示。解码过程分两步进行，形状解码和颜色解码。最后，通过引入核线约束和邻域约束来提高译码的可靠性。通过实验验证了该方法的准确性和稳健性。通过对包括人脸在内的真实物体的重建，验证了结构光方法的三维重建质量。
Color encoded structured light is an important means for single-shot 3D reconstruction. In this article, we present a pseudorandom array-based structured light method. The proposed pattern is composed with four colors, and one geometric shape is inlaid to the color elements to extend the coding element from four to eight. As a result, a relatively small coding window with the size of 2×2 can be obtained. Grid-point between each two adjacent pattern elements is defined as the pattern feature. And an improved feature detector is proposed for the robust and accurate grid-point localization. The grid-points are divided into two types and represented by a topological structure. The decoding procedure is performed in two steps, the shape decoding and color decoding. Finally, the epipolar constraint and neighboring constraint are introduced to improve the decoding reliability. Accuracy and robustness of the proposed method are evaluated in the experiments. Some real objects including human face are reconstructed to demonstrate the 3D reconstruction quality of the proposed structured light method.
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DOI：
10.1109/icip.2008.4712165
发表时间：
2008
期刊：
2008 15th IEEE International Conference on Image Processing
影响因子：
--
作者：
Zhan Song;R. Chung
通讯作者：
Zhan Song;R. Chung
DOI：
10.1023/b:visi.0000029664.99615.94
发表时间：
2004-11-01
影响因子：
19.5
作者：
Lowe, DG
通讯作者：
Lowe, DG
DOI：
10.1109/cvprw.2010.5543556
发表时间：
2010-06
期刊：
2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops
影响因子：
--
作者：
Ali O. Ulusoy;Fatih Calakli;G. Taubin
通讯作者：
Ali O. Ulusoy;Fatih Calakli;G. Taubin
DOI：
10.1109/iccv.2007.4408982
发表时间：
2007-12
期刊：
2007 IEEE 11th International Conference on Computer Vision
影响因子：
--
作者：
Chadi Albitar;P. Graebling;C. Doignon
通讯作者：
Chadi Albitar;P. Graebling;C. Doignon
影响因子：
10.6
作者：
Chen, S. Y.;Li, Y. F.;Zhang, Jianwei
通讯作者：
Zhang, Jianwei