华中科技大学学报（自然科学版）2025，Vol.53Issue(3)：48-55,8.DOI:10.13245/j.hust.250643
面向六自由度视频应用的动态场景重建
Dynamic scene reconstruction for six degrees of freedom video applications
摘要
Abstract
The six-degree-of-freedom video reconstruction method based on neural radiance fields requires the training and rendering of numerous multilayer perceptrons and relies on implicit representations,leading to high memory consumption and slow rendering speeds.To address these issues,a compact dynamic volumetric representation and an efficient sampling network were proposed.First,a sampling network was used to predict sparse points for accelerating volume rendering.Next,the dynamic volume was decomposed into six planes:three spatial planes and three spatiotemporal planes,and the feature vectors extracted from each plane were fused to compute the features of the sampled points.Then,the fused feature vectors were decoded into color features using spherical harmonic coefficients.In the process of volume decomposition,the deformations and topological changes of objects in dynamic scenes were considered from the perspective of tensors.The dynamic volume was decomposed using tensor decomposition into the sum of outer products of corresponding matrix factors,thus saving memory.Experimental results show that,compared to other methods,the proposed approach renders higher-quality novel views and recovers more details on complex and challenging dynamic datasets,all while using less memory.关键词
神经辐射场/六自由度/体渲染/球谐系数/张量分解Key words
neural radiance fields/six-degree-of-freedom/volume rendering/spherical harmonic coefficients/tensor decomposition分类
计算机与自动化引用本文复制引用
陈芬,陈学煌,李旭,张华波..面向六自由度视频应用的动态场景重建[J].华中科技大学学报（自然科学版）,2025,53(3):48-55,8.基金项目
国家自然科学基金资助项目(62371081) （62371081）
重庆市自然科学基金资助项目(cstc2021jcyj-msxmX0411,CSTB2022NSCQ-MSX0873) （cstc2021jcyj-msxmX0411,CSTB2022NSCQ-MSX0873）
重庆理工大学科研创新团队(2023TDZ003) （2023TDZ003）
重庆市研究生科研创新项目(CYS240700) （CYS240700）
重庆理工大学研究生教育高质量发展项目(gzlcx20242032). （gzlcx20242032）
