基于深度正则化的三维高斯人体重建算法

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中图分类号：TP37 文献标志码：A 文章编号：1001-3695（2025）07-041-2227-07

doi：10. 19734/j. issn. 1001-3695.2024.09.0368

Abstract：Duetothelackofaditionalgeometricconstraintsandpriorknowledge，thereconstructionresultsofexistingmultiview 3D humanbodyreconstruction methods are poor interms ofqualityandcompletenes.In response tothe above problems， this paper proposeda3DGausianreconstructionalgorithmDHGS forsparse views.Firstly，itimproved estimationmethod for humanbodymodelparametersbycombiningmulti-viewjointreprojectionandintersection-over-unionror，utilizedaccurate bodypriors toiitialize3DGaussianmodel.Secondlyitproposedanadaptivedepthadjustmentmodulethatincorpoateddepth estimationmodel，acieveddepthegularizationthroughdiferentiablerasterizationrendering，ndeancedthegeometriconsistencyofthereconstructionbyleveraginghumanbodyanddepthpriorknowledge.Finall，itgeneratedsyntheticpseudo-views duringtheoptimizationprocess toenforceadditional geometricconstraints.ExperimentalresultsontheZJU-MoCap，GeneBody， and DNA-Rendering datasetsshowthatthe DHGS algorithm achieves PSNRof 26.13dB，24.87d，and 25.25dBforimage reconstruction，represented improvements of 27.3% ， 32.6% ，and 17.4% over the original 3DGS algorithm.The experiments validateteeffectivenessofthealgorithm，withtheDHGSmodelbeingcapableoftraininginjust5minutestorenderhighquality 3D human body images in real time.

Keywords：3Dhuman reconstruction；3D Gaussiansplatting；depth regularization；diferentiablerasterizationrendering

0 引言

三维人体重建旨在生成具有真实外观的人体三维模型，该技术在元宇宙、人机交互、虚拟和增强现实、游戏与电影制作等领域有着广泛的应用前景。（剩余17107字）