scholarly journals Convex Relaxations for Consensus and Non-Minimal Problems in 3D Vision

2019 ◽  
Author(s):  
Thomas Probst ◽  
Danda Pani Paudel ◽  
Ajad Chhatkuli ◽  
Luc Van Gool
Keyword(s):  
Convex Relaxations ◽  
3D Vision ◽  
Minimal Problems

POSTOPERATIVE PERICARDIAL EFFUSION SYNDROME

2012 ◽  
pp. 66-71
Author(s):  
Quang Thuu Le
Keyword(s):  
Pericardial Effusion ◽  
Heart Surgery ◽  
Open Heart Surgery ◽  
Diagnostic Methods ◽  
Open Heart ◽  
Cross Sectional ◽  
Pericardial Drainage ◽  
Results Of Treatment ◽  
Intraoperative Management ◽  
Minimal Problems

Objective: Today, despite many recent improvements in intraoperative management and postoperative care, late pericardial effusions remain an important cause of morbidity after cardiac surgery. Because of widespread use of chronic anticoagulation and increased complexity of operations, the incidence of effusion may be higher. Thus we need to update the information on the symptoms, risk factors, diagnostic methods and treatment of Postoperative pericardial effusion syndrome. Patients and methods: A cross-sectional and prospective study of all patients admitted to hospital because of pericardial effusion after open heart surgery from 1/2010 to 9/2012. Study the clinical characteristics, paraclinicals, evaluate the results of treatment of pericardial effusion after open heart surgery. Results: Symptoms of pericardial effusion are nonspecific. Some patients with pericardial effusion report minimal problems. In the present study, few patients have the classic presentation of tamponade. Echocardiography is the diagnostic accuracy pericardial effusion after open heart surgery. This treatment mainly is pericardial drainage with 100%. Conclusion: Pericardial effusion is a common complication after open-heart surgery, symptoms of pericardial effusion are nonspecific to diagnostic method is echocardiographic surveillance.patients can be treated with internal medicine if has no tamponade and less fliuds. Pericardial drainage is absolute only in patients with pericardial effusion with signs of cardiac tamponade or pericardial many of effusion.

scholarly journals 6D pose estimation with combined deep learning and 3D vision techniques for a fast and accurate object grasping

2021 ◽  
pp. 103775
Author(s):  
Tuan-Tang Le ◽  
Trung-Son Le ◽  
Yu-Ru Chen ◽  
Joel Vidal ◽  
Chyi-Yeu Lin
Keyword(s):  
Deep Learning ◽  
Pose Estimation ◽  
3D Vision

scholarly journals Monocular Depth Estimation with Joint Attention Feature Distillation and Wavelet-Based Loss Function

Sensors ◽  
2020 ◽  
Vol 21 (1) ◽  
pp. 54
Author(s):  
Peng Liu ◽  
Zonghua Zhang ◽  
Zhaozong Meng ◽  
Nan Gao
Keyword(s):  
Joint Attention ◽  
Loss Function ◽  
Depth Estimation ◽  
Depth Information ◽  
3D Vision ◽  
Network Training ◽  
Crucial Component ◽  
Benchmark Datasets ◽  
Ill Posed ◽  
Monocular Depth

Depth estimation is a crucial component in many 3D vision applications. Monocular depth estimation is gaining increasing interest due to flexible use and extremely low system requirements, but inherently ill-posed and ambiguous characteristics still cause unsatisfactory estimation results. This paper proposes a new deep convolutional neural network for monocular depth estimation. The network applies joint attention feature distillation and wavelet-based loss function to recover the depth information of a scene. Two improvements were achieved, compared with previous methods. First, we combined feature distillation and joint attention mechanisms to boost feature modulation discrimination. The network extracts hierarchical features using a progressive feature distillation and refinement strategy and aggregates features using a joint attention operation. Second, we adopted a wavelet-based loss function for network training, which improves loss function effectiveness by obtaining more structural details. The experimental results on challenging indoor and outdoor benchmark datasets verified the proposed method’s superiority compared with current state-of-the-art methods.

scholarly journals An alternative perspective on copositive and convex relaxations of nonconvex quadratic programs

2021 ◽  
Author(s):  
E. Alper Yıldırım
Keyword(s):  
Objective Function ◽  
Convex Relaxation ◽  
Large Family ◽  
Quadratic Program ◽  
Feasible Region ◽  
Recession Cone ◽  
Convex Relaxations ◽  
Quadratic Programs ◽  
Alternative Perspective ◽  
Optimal Value

AbstractWe study convex relaxations of nonconvex quadratic programs. We identify a family of so-called feasibility preserving convex relaxations, which includes the well-known copositive and doubly nonnegative relaxations, with the property that the convex relaxation is feasible if and only if the nonconvex quadratic program is feasible. We observe that each convex relaxation in this family implicitly induces a convex underestimator of the objective function on the feasible region of the quadratic program. This alternative perspective on convex relaxations enables us to establish several useful properties of the corresponding convex underestimators. In particular, if the recession cone of the feasible region of the quadratic program does not contain any directions of negative curvature, we show that the convex underestimator arising from the copositive relaxation is precisely the convex envelope of the objective function of the quadratic program, strengthening Burer’s well-known result on the exactness of the copositive relaxation in the case of nonconvex quadratic programs. We also present an algorithmic recipe for constructing instances of quadratic programs with a finite optimal value but an unbounded relaxation for a rather large family of convex relaxations including the doubly nonnegative relaxation.

Human skill integrated motion planning of assembly manipulation for 6R industrial robot

2019 ◽  
Vol 46 (1) ◽  
pp. 171-180
Author(s):  
Yi Liu ◽  
Ming Cong ◽  
Hang Dong ◽  
Dong Liu
Keyword(s):  
Deep Learning ◽  
Motion Planning ◽  
Industrial Robot ◽  
Robotic Assembly ◽  
3D Vision ◽  
Content Type ◽  
Human Skill ◽  
Depth Images ◽  
Positioning Method ◽  
Assembly Technology

Purpose The purpose of this paper is to propose a new method based on three-dimensional (3D) vision technologies and human skill integrated deep learning to solve assembly positioning task such as peg-in-hole. Design/methodology/approach Hybrid camera configuration was used to provide the global and local views. Eye-in-hand mode guided the peg to be in contact with the hole plate using 3D vision in global view. When the peg was in contact with the workpiece surface, eye-to-hand mode provided the local view to accomplish peg-hole positioning based on trained CNN. Findings The results of assembly positioning experiments proved that the proposed method successfully distinguished the target hole from the other same size holes according to the CNN. The robot planned the motion according to the depth images and human skill guide line. The final positioning precision was good enough for the robot to carry out force controlled assembly. Practical implications The developed framework can have an important impact on robotic assembly positioning process, which combine with the existing force-guidance assembly technology as to build a whole set of autonomous assembly technology. Originality/value This paper proposed a new approach to the robotic assembly positioning based on 3D visual technologies and human skill integrated deep learning. Dual cameras swapping mode was used to provide visual feedback for the entire assembly motion planning process. The proposed workpiece positioning method provided an effective disturbance rejection, autonomous motion planning and increased overall performance with depth images feedback. The proposed peg-hole positioning method with human skill integrated provided the capability of target perceptual aliasing avoiding and successive motion decision for the robotic assembly manipulation.

scholarly journals A Coarse-to-Fine Method for Estimating the Axis Pose Based on 3D Point Clouds in Robotic Cylindrical Shaft-in-Hole Assembly

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4064
Author(s):  
Can Li ◽  
Ping Chen ◽  
Xin Xu ◽  
Xinyu Wang ◽  
Aijun Yin
Keyword(s):  
Pose Estimation ◽  
Point Clouds ◽  
Geometric Constraints ◽  
Admittance Control ◽  
3D Vision ◽  
Axis Orientation ◽  
3D Point Clouds ◽  
Object Pose Estimation ◽  
Traditional Approaches ◽  
Coarse To Fine

In this work, we propose a novel coarse-to-fine method for object pose estimation coupled with admittance control to promote robotic shaft-in-hole assembly. Considering that traditional approaches to locate the hole by force sensing are time-consuming, we employ 3D vision to estimate the axis pose of the hole. Thus, robots can locate the target hole in both position and orientation and enable the shaft to move into the hole along the axis orientation. In our method, first, the raw point cloud of a hole is processed to acquire the keypoints. Then, a coarse axis is extracted according to the geometric constraints between the surface normals and axis. Lastly, axis refinement is performed on the coarse axis to achieve higher precision. Practical experiments verified the effectiveness of the axis pose estimation. The assembly strategy composed of axis pose estimation and admittance control was effectively applied to the robotic shaft-in-hole assembly.

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