Robust pattern decoding in shape-coded structured light
Robust pattern decoding in shape-coded structured light
复制标题
形状编码结构光中的鲁棒图案解码
DOI：
10.1016/j.optlaseng.2017.04.008
复制
发表时间：
2017-09
影响因子：
4.6
通讯作者：
Hai Zeng
中科院分区：
文献类型：
--
作者：
Suming Tang;Xu Zhang;Zhan Song;Lifang Song;Hai Zeng
在编码结构光系统中，解码是一个具有挑战性的复杂问题。针对形状编码结构光，提出了一种稳健的图案解码方法，该方法将图案设计为嵌入几何形状的网格形状。在我们的译码方法中，分三个步骤进行改进。首先，提出了一种多模板特征检测算法，检测出每两条正交网格线的交点。其次，将模式元素识别建模为一个有监督的分类问题，并应用深度神经网络技术对模式元素进行精确分类。在此之前，建立了一个训练数据集，其中包含大量具有各种模糊和失真的模式元素。第三，提出了一种基于核线约束、共面约束和拓扑约束的纠错机制来减少误匹配。在实验中，选取了包括人手在内的几个复杂物体来测试该方法的准确性和鲁棒性。实验结果表明，该译码方法不仅具有较高的译码精度，而且对表面颜色和复杂纹理具有较强的鲁棒性。
Decoding is a challenging and complex problem in a coded structured light system. In this paper, a robust pattern decoding method is proposed for the shape-coded structured light in which the pattern is designed as grid shape with embedded geometrical shapes. In our decoding method, advancements are made at three steps. First, a multi-template feature detection algorithm is introduced to detect the feature point which is the intersection of each two orthogonal grid-lines. Second, pattern element identification is modelled as a supervised classification problem and the deep neural network technique is applied for the accurate classification of pattern elements. Before that, a training dataset is established, which contains a mass of pattern elements with various blurring and distortions. Third, an error correction mechanism based on epipolar constraint, coplanarity constraint and topological constraint is presented to reduce the false matches. In the experiments, several complex objects including human hand are chosen to test the accuracy and robustness of the proposed method. The experimental results show that our decoding method not only has high decoding accuracy, but also owns strong robustness to surface color and complex textures.
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单次结构光意味着通过编码颜色和几何特征
影响因子：
8
作者：
Lin Haibo;Nie Lei;Song Zhan
通讯作者：
Song Zhan
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
DOI：
10.1109/crv.2005.1
发表时间：
2005-05
期刊：
The 2nd Canadian Conference on Computer and Robot Vision (CRV'05)
影响因子：
--
作者：
A. Adán;F. Molina;A. Vázquez;Luis Morena
通讯作者：
A. Adán;F. Molina;A. Vázquez;Luis Morena