CN106683178A - 基于图论的低秩矩阵恢复三维骨架方法 - Google Patents
基于图论的低秩矩阵恢复三维骨架方法 Download PDFInfo
- Publication number
- CN106683178A CN106683178A CN201611256183.9A CN201611256183A CN106683178A CN 106683178 A CN106683178 A CN 106683178A CN 201611256183 A CN201611256183 A CN 201611256183A CN 106683178 A CN106683178 A CN 106683178A
- Authority
- CN
- China
- Prior art keywords
- matrix
- rho
- skeleton
- low
- rank
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 239000011159 matrix material Substances 0.000 title claims abstract description 99
- 238000000034 method Methods 0.000 title claims abstract description 54
- 210000000988 bone and bone Anatomy 0.000 claims abstract description 38
- 230000033001 locomotion Effects 0.000 claims abstract description 28
- 150000001875 compounds Chemical class 0.000 claims abstract description 5
- 230000008439 repair process Effects 0.000 claims abstract description 3
- 238000005457 optimization Methods 0.000 claims description 10
- 230000003416 augmentation Effects 0.000 claims description 9
- 230000002123 temporal effect Effects 0.000 claims description 9
- 238000010586 diagram Methods 0.000 claims description 6
- 230000003190 augmentative effect Effects 0.000 claims description 4
- 238000004883 computer application Methods 0.000 abstract description 2
- 238000012545 processing Methods 0.000 abstract description 2
- 238000011084 recovery Methods 0.000 description 8
- 230000006870 function Effects 0.000 description 5
- 230000006378 damage Effects 0.000 description 3
- 238000013135 deep learning Methods 0.000 description 3
- 230000001771 impaired effect Effects 0.000 description 2
- 238000013528 artificial neural network Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 230000000903 blocking effect Effects 0.000 description 1
- 238000007796 conventional method Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 230000009977 dual effect Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000001914 filtration Methods 0.000 description 1
- 210000005036 nerve Anatomy 0.000 description 1
- 230000007935 neutral effect Effects 0.000 description 1
- 238000003909 pattern recognition Methods 0.000 description 1
- 238000012549 training Methods 0.000 description 1
- 238000012800 visualization Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T17/00—Three dimensional [3D] modelling, e.g. data description of 3D objects
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration
Landscapes
- Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Computer Graphics (AREA)
- Geometry (AREA)
- Software Systems (AREA)
- Processing Or Creating Images (AREA)
Abstract
Description
Claims (3)
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201611256183.9A CN106683178B (zh) | 2016-12-30 | 2016-12-30 | 基于图论的低秩矩阵恢复三维骨架方法 |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201611256183.9A CN106683178B (zh) | 2016-12-30 | 2016-12-30 | 基于图论的低秩矩阵恢复三维骨架方法 |
Publications (2)
Publication Number | Publication Date |
---|---|
CN106683178A true CN106683178A (zh) | 2017-05-17 |
CN106683178B CN106683178B (zh) | 2020-04-28 |
Family
ID=58873401
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN201611256183.9A Active CN106683178B (zh) | 2016-12-30 | 2016-12-30 | 基于图论的低秩矩阵恢复三维骨架方法 |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN106683178B (zh) |
Cited By (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN109886888A (zh) * | 2019-01-28 | 2019-06-14 | 华中科技大学 | 一种基于l1范数最小化模型的神经纤维骨架校正方法 |
CN110415336A (zh) * | 2019-07-12 | 2019-11-05 | 清华大学 | 高精度人体体态重建方法及*** |
CN114913100A (zh) * | 2022-05-16 | 2022-08-16 | 中国烟草总公司四川省公司 | 一种基于图像分析的烟叶烘烤程度检测方法 |
WO2024100709A1 (ja) * | 2022-11-07 | 2024-05-16 | 日本電信電話株式会社 | 最適化装置、最適化方法及びプログラム |
WO2024100707A1 (ja) * | 2022-11-07 | 2024-05-16 | 日本電信電話株式会社 | 雑音除去装置、雑音除去方法及びプログラム |
Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN102222361A (zh) * | 2010-04-06 | 2011-10-19 | 清华大学 | 三维模型的捕捉及重建方法和*** |
CN104867119A (zh) * | 2015-05-21 | 2015-08-26 | 天津大学 | 基于低秩矩阵重建的结构性缺失图像填充方法 |
CN104915978A (zh) * | 2015-06-18 | 2015-09-16 | 天津大学 | 基于体感相机Kinect的真实感动画生成方法 |
CN105957022A (zh) * | 2016-04-05 | 2016-09-21 | 天津大学 | 低秩矩阵重建带有随机值脉冲噪声缺失图像恢复方法 |
US20160371563A1 (en) * | 2015-06-22 | 2016-12-22 | The Johns Hopkins University | System and method for structured low-rank matrix factorization: optimality, algorithm, and applications to image processing |
-
2016
- 2016-12-30 CN CN201611256183.9A patent/CN106683178B/zh active Active
Patent Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN102222361A (zh) * | 2010-04-06 | 2011-10-19 | 清华大学 | 三维模型的捕捉及重建方法和*** |
CN104867119A (zh) * | 2015-05-21 | 2015-08-26 | 天津大学 | 基于低秩矩阵重建的结构性缺失图像填充方法 |
CN104915978A (zh) * | 2015-06-18 | 2015-09-16 | 天津大学 | 基于体感相机Kinect的真实感动画生成方法 |
US20160371563A1 (en) * | 2015-06-22 | 2016-12-22 | The Johns Hopkins University | System and method for structured low-rank matrix factorization: optimality, algorithm, and applications to image processing |
CN105957022A (zh) * | 2016-04-05 | 2016-09-21 | 天津大学 | 低秩矩阵重建带有随机值脉冲噪声缺失图像恢复方法 |
Cited By (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN109886888A (zh) * | 2019-01-28 | 2019-06-14 | 华中科技大学 | 一种基于l1范数最小化模型的神经纤维骨架校正方法 |
CN110415336A (zh) * | 2019-07-12 | 2019-11-05 | 清华大学 | 高精度人体体态重建方法及*** |
CN114913100A (zh) * | 2022-05-16 | 2022-08-16 | 中国烟草总公司四川省公司 | 一种基于图像分析的烟叶烘烤程度检测方法 |
CN114913100B (zh) * | 2022-05-16 | 2023-09-15 | 中国烟草总公司四川省公司 | 一种基于图像分析的烟叶烘烤程度检测方法 |
WO2024100709A1 (ja) * | 2022-11-07 | 2024-05-16 | 日本電信電話株式会社 | 最適化装置、最適化方法及びプログラム |
WO2024100707A1 (ja) * | 2022-11-07 | 2024-05-16 | 日本電信電話株式会社 | 雑音除去装置、雑音除去方法及びプログラム |
Also Published As
Publication number | Publication date |
---|---|
CN106683178B (zh) | 2020-04-28 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN106683178A (zh) | 基于图论的低秩矩阵恢复三维骨架方法 | |
CN109389671B (zh) | 一种基于多阶段神经网络的单图像三维重建方法 | |
CN110148146B (zh) | 一种利用合成数据的植物叶片分割方法及*** | |
CN105184861B (zh) | 一种自动人体三维重建*** | |
CN104915978B (zh) | 基于体感相机Kinect的真实感动画生成方法 | |
CN111161364B (zh) | 一种针对单视角深度图的实时形状补全和姿态估计方法 | |
CN110766746B (zh) | 一种基于联合2d-3d神经网络的3d驾驶员姿态估计方法 | |
CN108647639A (zh) | 实时人体骨骼关节点检测方法 | |
CN108549844A (zh) | 一种基于多层分形网络和关节亲属模式的多人姿态估计方法 | |
CN111062326B (zh) | 一种基于几何驱动的自监督人体3d姿态估计网络训练方法 | |
CN110738161A (zh) | 一种基于改进生成式对抗网络的人脸图像矫正方法 | |
CN113205595B (zh) | 一种3d人体姿态估计模型的构建方法及其应用 | |
CN102622766A (zh) | 多目标优化的多镜头人体运动跟踪方法 | |
CN105989625A (zh) | 数据处理的方法和装置 | |
CN111914618B (zh) | 基于对抗式相对深度约束网络的三维人体姿态估计方法 | |
CN110930500A (zh) | 一种基于单视角视频的动态头发建模方法 | |
Yang et al. | Spatio-temporal reconstruction for 3D motion recovery | |
CN106296610A (zh) | 基于低秩矩阵分析的三维骨架修复方法 | |
CN107862733A (zh) | 基于视线更新算法的大规模场景实时三维重建方法和*** | |
CN113255487A (zh) | 一种三维实时人体姿态识别方法 | |
CN103839280B (zh) | 一种基于视觉信息的人体姿态跟踪方法 | |
CN111428555A (zh) | 一种分关节的手部姿态估计方法 | |
CN113284249A (zh) | 一种基于图神经网络的多视角三维人体重建方法及*** | |
CN113139432A (zh) | 基于人体骨架和局部图像的工业包装行为识别方法 | |
CN116797640A (zh) | 一种面向智能伴行巡视器的深度及3d关键点估计方法 |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
GR01 | Patent grant | ||
GR01 | Patent grant | ||
TR01 | Transfer of patent right |
Effective date of registration: 20200715 Address after: 411, block a, Zhizao street, Zhongguancun, No. 45, Chengfu Road, Haidian District, Beijing 100080 Patentee after: Beijing Youke Nuclear Power Technology Development Co.,Ltd. Address before: 300072 Tianjin City, Nankai District Wei Jin Road No. 92 Patentee before: Tianjin University |
|
TR01 | Transfer of patent right | ||
TR01 | Transfer of patent right | ||
TR01 | Transfer of patent right |
Effective date of registration: 20201010 Address after: 100094 Beijing city Haidian District Cui Hunan loop 13 Hospital No. 7 Building 7 room 701 Patentee after: Beijing lingyunguang Technology Group Co.,Ltd. Address before: 411, block a, Zhizao street, Zhongguancun, No. 45, Chengfu Road, Haidian District, Beijing 100080 Patentee before: Beijing Youke Nuclear Power Technology Development Co.,Ltd. |
|
CP01 | Change in the name or title of a patent holder | ||
CP01 | Change in the name or title of a patent holder |
Address after: 100094 701, 7 floor, 7 building, 13 Cui Hunan Ring Road, Haidian District, Beijing. Patentee after: Lingyunguang Technology Co.,Ltd. Address before: 100094 701, 7 floor, 7 building, 13 Cui Hunan Ring Road, Haidian District, Beijing. Patentee before: Beijing lingyunguang Technology Group Co.,Ltd. |
|
TR01 | Transfer of patent right | ||
TR01 | Transfer of patent right |
Effective date of registration: 20210114 Address after: 518000 room 1101, 11th floor, building 2, C District, Nanshan Zhiyuan, Nanshan District, Shenzhen City, Guangdong Province Patentee after: Shenzhen Lingyun Shixun Technology Co.,Ltd. Address before: 100094 701, 7 floor, 7 building, 13 Cui Hunan Ring Road, Haidian District, Beijing. Patentee before: Lingyunguang Technology Co.,Ltd. |