基于点元的果实三维重建技术研究
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摘要
针对基于点元果实外观重建过程中的关键技术问题，以田间农产品果实为研究对象，以基于点云的三维重建为理论基础，以计算几何方法为研究工具，以点元模型的数字几何处理流程为研究主线，研究果实点云的重建过程，提出一套用于生长过程中果实重建的流程框架。主要研究工作和结论如下：
（1）针对从杂乱背景点云中提取3D水果形状的计算量大、效率低、结果不准确问题，研究改进的k-邻域自适应细分算法简化点云以降低计算量，基于MLS拟合splats局部曲面以更准确估计几何特征，采用递归的基于几何相似性的增量过程(GSA)解决快速抽取。结果表明，实验选取的最佳分割参数使抽取后的基元数量降为原始扫描点的3.05%，比纯粹的k(4％)邻域分割基元数降低了23.75％。
（2）针对成对变换在参数简化和消除冗余变换方面的不足，研究基于几何描述子从理论上推导坐标系之间的齐次变换模型，优化相邻片间的变换矩阵和参数。实验表明，基于oriented-splat的最优变换策略仅需1对同名点对和5个参数，降低计算复杂性。
（3）针对成对特征配准同名点搜索低效、迭代配准计算复杂和精确性不高等问题，提出结合特征法与迭代法优势的多特征微分逐级搜索法(FDSC)提高成对配准的效率，研究双重误差度量方法以提高配准的准确性。结果表明，FDSC收敛速度更快，使成对配准平移误差比MUMC和4PCS方法减少65％以上，旋转误差减少89％以上，实际误差值减少99％以上。
（4）为解决自由形状水果由于全局配准误差累计而导致配准结果不准确，研究通过基于层次的自动全局配准策略以分散误差的传递性，基于累计误差修正的方法减小误差在层间的传递。结果表明，全局配准平移误差比顺序策略和固定坐标系的4参数法减少55％以上，旋转误差减少65％以上，实际误差值减少99％以上。
（5）基于点元分割坐标，研究用点四叉树简化纹理图片的对应分割问题；研究基于高效的texton特征描述、多粒度自适应morton编码方法和Z－Order线性组织策略降低texton编码的存储空间；研究基于颜色感知、子采样、细分割、过取样和加权平均(PSSOW)解决使视觉效果和存储性能平衡的texton纹理属性计算方法。实验表明，编码空间平均降低1/4，在不失真的前提下，纹理颜色存储空间比直接二维映射法、多分辨率量化方法和颜色视觉模型分别降低了70.3％，55.5％和41.7％以上。
Aiming at the key technical problems of surfel-based fruit reconstruction, a research onthe reconstruction process of fruit is presented and a set of frame for growing fruitreconstruction is proposed by taking the field fruits as the research objects, the point-based3D reconstruction as the theoretical basis, the computation geometric method as research tooland surfel-based digital geometry processing as the research procedure. The maincontributions include:
(1) Expensive computation, low efficiency and inaccuracy remain a long-standingchallenge in extraction of fruit shape from massive background points. Towards theseobjectives, an improved K-neighborhood adaptive subdivision algorithm is proposed tosimplify point clouds for a reduction of calculation; an MLS-based local surface fitting isemployed for more accurate estimation of geometric attributes and a geometricsimilarity-based augmenter (GSA)recursive process is used for rapid extraction. As a result,the optimal segmentation parameters help to reduce the number of extracted cells to3.05%ofthe original points, a23.75%down than the pure K (4%) neighborhood.
(2) As for the defects of pairwise transformation in parameter simplification andredundant transformation elimination, based on geometric descriptor, homogeneoustransformation model between two coordinate systems is theoretically deduced andtransformation matrix and parameters between two neighbor scans is optimized. Theexperiment shows that oriented-splat optimal transformation needs only five parameters andone pair of correspondences to lower the computational complexity.
(3) Due to the low efficiency in finding correspondences associated with feature-basedpairwise registration, complex computation and inaccuracy related to iterative pairwiseregistration, a Feature-Difference based Step-by-step Contraction(FDSC) is presented forenhancing registration efficiency by taking advantage of feature-based and iterative pairwiseregistration, and a duplicato-error metric/verification algorithm is presented for improvingaccuracy. Experiments show that with FDSC having more rapid convergence rate, thetranslation error is decreased by65％than MUMC and4PCS, rotation error by89％, and theerror value by99％.
(4) Global registration inaccuracy associated with error accumulation remains a long-standing challenge in free-form fruits. Towards this objective, a hierarchical automaticglobal registration strategy is proposed to disperse accumulative error, and a cumulative errorcorrection method is employed to reduce the error transfer between the layers. As a result, theglobal translation error is decreased by55％by this method than by sequence strategy or4-parameters of fixed coordinate method. The rotation error is decreased by65％and theaccumulative error value is down by99％.
(5) A point-quadtree method is employed to simplify the corresponding imagesegmentation by taking advantage of surfel splitting positions; the texton descriptor, linearZ-Order and multi-level adaptive morton coding method is employed for saving the memoryspace; the color perception, subsampling, sub-division, oversampling and the weightedaverage (PSSOW) means is employed for saving memory and improving visual effect intexton properties calculation. Results show that multi-level adaptive morton code helps toreduce the memory by1/4than general code. While preventing the texture from distortion,PSSOW makes color memory condensed by70.3％,55.5％and70.3％than direct2Dmapping, Multi-resolution quantization method and color vision model.
（1）针对从杂乱背景点云中提取3D水果形状的计算量大、效率低、结果不准确问题，研究改进的k-邻域自适应细分算法简化点云以降低计算量，基于MLS拟合splats局部曲面以更准确估计几何特征，采用递归的基于几何相似性的增量过程(GSA)解决快速抽取。结果表明，实验选取的最佳分割参数使抽取后的基元数量降为原始扫描点的3.05%，比纯粹的k(4％)邻域分割基元数降低了23.75％。
（2）针对成对变换在参数简化和消除冗余变换方面的不足，研究基于几何描述子从理论上推导坐标系之间的齐次变换模型，优化相邻片间的变换矩阵和参数。实验表明，基于oriented-splat的最优变换策略仅需1对同名点对和5个参数，降低计算复杂性。
（3）针对成对特征配准同名点搜索低效、迭代配准计算复杂和精确性不高等问题，提出结合特征法与迭代法优势的多特征微分逐级搜索法(FDSC)提高成对配准的效率，研究双重误差度量方法以提高配准的准确性。结果表明，FDSC收敛速度更快，使成对配准平移误差比MUMC和4PCS方法减少65％以上，旋转误差减少89％以上，实际误差值减少99％以上。
（4）为解决自由形状水果由于全局配准误差累计而导致配准结果不准确，研究通过基于层次的自动全局配准策略以分散误差的传递性，基于累计误差修正的方法减小误差在层间的传递。结果表明，全局配准平移误差比顺序策略和固定坐标系的4参数法减少55％以上，旋转误差减少65％以上，实际误差值减少99％以上。
（5）基于点元分割坐标，研究用点四叉树简化纹理图片的对应分割问题；研究基于高效的texton特征描述、多粒度自适应morton编码方法和Z－Order线性组织策略降低texton编码的存储空间；研究基于颜色感知、子采样、细分割、过取样和加权平均(PSSOW)解决使视觉效果和存储性能平衡的texton纹理属性计算方法。实验表明，编码空间平均降低1/4，在不失真的前提下，纹理颜色存储空间比直接二维映射法、多分辨率量化方法和颜色视觉模型分别降低了70.3％，55.5％和41.7％以上。
Aiming at the key technical problems of surfel-based fruit reconstruction, a research onthe reconstruction process of fruit is presented and a set of frame for growing fruitreconstruction is proposed by taking the field fruits as the research objects, the point-based3D reconstruction as the theoretical basis, the computation geometric method as research tooland surfel-based digital geometry processing as the research procedure. The maincontributions include:
(1) Expensive computation, low efficiency and inaccuracy remain a long-standingchallenge in extraction of fruit shape from massive background points. Towards theseobjectives, an improved K-neighborhood adaptive subdivision algorithm is proposed tosimplify point clouds for a reduction of calculation; an MLS-based local surface fitting isemployed for more accurate estimation of geometric attributes and a geometricsimilarity-based augmenter (GSA)recursive process is used for rapid extraction. As a result,the optimal segmentation parameters help to reduce the number of extracted cells to3.05%ofthe original points, a23.75%down than the pure K (4%) neighborhood.
(2) As for the defects of pairwise transformation in parameter simplification andredundant transformation elimination, based on geometric descriptor, homogeneoustransformation model between two coordinate systems is theoretically deduced andtransformation matrix and parameters between two neighbor scans is optimized. Theexperiment shows that oriented-splat optimal transformation needs only five parameters andone pair of correspondences to lower the computational complexity.
(3) Due to the low efficiency in finding correspondences associated with feature-basedpairwise registration, complex computation and inaccuracy related to iterative pairwiseregistration, a Feature-Difference based Step-by-step Contraction(FDSC) is presented forenhancing registration efficiency by taking advantage of feature-based and iterative pairwiseregistration, and a duplicato-error metric/verification algorithm is presented for improvingaccuracy. Experiments show that with FDSC having more rapid convergence rate, thetranslation error is decreased by65％than MUMC and4PCS, rotation error by89％, and theerror value by99％.
(4) Global registration inaccuracy associated with error accumulation remains a long-standing challenge in free-form fruits. Towards this objective, a hierarchical automaticglobal registration strategy is proposed to disperse accumulative error, and a cumulative errorcorrection method is employed to reduce the error transfer between the layers. As a result, theglobal translation error is decreased by55％by this method than by sequence strategy or4-parameters of fixed coordinate method. The rotation error is decreased by65％and theaccumulative error value is down by99％.
(5) A point-quadtree method is employed to simplify the corresponding imagesegmentation by taking advantage of surfel splitting positions; the texton descriptor, linearZ-Order and multi-level adaptive morton coding method is employed for saving the memoryspace; the color perception, subsampling, sub-division, oversampling and the weightedaverage (PSSOW) means is employed for saving memory and improving visual effect intexton properties calculation. Results show that multi-level adaptive morton code helps toreduce the memory by1/4than general code. While preventing the texture from distortion,PSSOW makes color memory condensed by70.3％,55.5％and70.3％than direct2Dmapping, Multi-resolution quantization method and color vision model.
引文
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