MRF Optimization by Graph Approximation [PDF]
2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015 Graph cuts-based algorithms have achieved great success in energy minimization for many computer vision applications. These algorithms provide approximated solutions for multi-label energy functions via move-making approach.
Kim, Wonsik, Lee, Kyoung Mu
core +2 more sources
Automatic Extrinsic Calibration of 3D LIDAR and Multi-Cameras Based on Graph Optimization [PDF]
Sensors, 2022 In recent years, multi-sensor fusion technology has made enormous progress in 3D reconstruction, surveying and mapping, autonomous driving, and other related fields, and extrinsic calibration is a necessary condition for multi-sensor fusion applications.
Jinshun Ou +4 more
doaj +2 more sources
Extremal Optimization for Graph Partitioning [PDF]
Physical Review E, 2001 Extremal optimization is a new general-purpose method for approximating solutions to hard optimization problems. We study the method in detail by way of the NP-hard graph partitioning problem.
A. K. Hartmann +44 more
core +3 more sources
Graph Optimization Model Fusing BLE Ranging with Wi-Fi Fingerprint for Indoor Positioning [PDF]
Sensors, 2022 To improve the user’s positioning accuracy of a Wi-Fi fingerprint-based positioning algorithm, this study proposes a graph optimization model based on the framework of g2o that fuses a Wi-Fi fingerprint and Bluetooth Low Energy (BLE) ranging technologies.
Rong Zhou +3 more
doaj +2 more sources
Crowdsourcing-Based Indoor Semantic Map Construction and Localization Using Graph Optimization [PDF]
Sensors, 2022 The advancement of smartphones with multiple built-in sensors facilitates the development of crowdsourcing-based indoor map construction and localization.
Chao Li +3 more
doaj +2 more sources
A LiDAR/Visual SLAM Backend with Loop Closure Detection and Graph Optimization
Remote Sensing, 2021 LiDAR (light detection and ranging), as an active sensor, is investigated in the simultaneous localization and mapping (SLAM) system. Typically, a LiDAR SLAM system consists of front-end odometry and back-end optimization modules.
Shoubin Chen +4 more
doaj +3 more sources
DiT-SLAM: Real-Time Dense Visual-Inertial SLAM with Implicit Depth Representation and Tightly-Coupled Graph Optimization [PDF]
Sensors, 2022 Recently, generating dense maps in real-time has become a hot research topic in the mobile robotics community, since dense maps can provide more informative and continuous features compared with sparse maps. Implicit depth representation (e.g., the depth
Mingle Zhao +4 more
doaj +2 more sources
A Study on Graph Optimization Method for GNSS/IMU Integrated Navigation System Based on Virtual Constraints [PDF]
SensorsIn GNSS/IMU integrated navigation systems, factors like satellite occlusion and non-line-of-sight can degrade satellite positioning accuracy, thereby impacting overall navigation system results.
Haiyang Qiu +3 more
doaj +2 more sources
DOT-SLAM: A Stereo Visual Simultaneous Localization and Mapping (SLAM) System with Dynamic Object Tracking Based on Graph Optimization [PDF]
SensorsMost visual simultaneous localization and mapping (SLAM) systems are based on the assumption of a static environment in autonomous vehicles. However, when dynamic objects, particularly vehicles, occupy a large portion of the image, the localization ...
Yuan Zhu +5 more
doaj +2 more sources
GNSS/INS/LiDAR-SLAM Integrated Navigation System Based on Graph Optimization
Remote Sensing, 2019 A Global Navigation Satellite System (GNSS)/Inertial Navigation System (INS)/Light Detection and Ranging (LiDAR)-Simultaneous Localization and Mapping (SLAM) integrated navigation system based on graph optimization is proposed and implemented in this ...
Le Chang +4 more
doaj +3 more sources