scholarly journals Selective Segmentation for Global Optimization of Depth Estimation in Complex Scenes

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Sheng Liu ◽  
Haiqiang Jin ◽  
Xiaojun Mao ◽  
Binbin Zhai ◽  
Ye Zhan ◽  
...  
Keyword(s):  
Global Optimization ◽  
Stereo Matching ◽  
Cost Optimization ◽  
Depth Estimation ◽  
Optimization Method ◽  
Optimization Approach ◽  
Real Scene ◽  
Complex Scenes ◽  
Matching Cost ◽  
Image Pairs

This paper proposes a segmentation-based global optimization method for depth estimation. Firstly, for obtaining accurate matching cost, the original local stereo matching approach based on self-adapting matching window is integrated with two matching cost optimization strategies aiming at handling both borders and occlusion regions. Secondly, we employ a comprehensive smooth term to satisfy diverse smoothness request in real scene. Thirdly, a selective segmentation term is used for enforcing the plane trend constraints selectively on the corresponding segments to further improve the accuracy of depth results from object level. Experiments on the Middlebury image pairs show that the proposed global optimization approach is considerably competitive with other state-of-the-art matching approaches.

Optimization of Heating Temperature History for Anisotropic Conductive Film Interconnection

2012 ◽  
Vol 134 (1) ◽  
Author(s):  
Yasutada Nakagawa ◽  
Ryohei Yokoyama
Keyword(s):  
Global Optimization ◽  
Heating Temperature ◽  
Optimization Method ◽  
Temperature History ◽  
Optimization Approach ◽  
Anisotropic Conductive Film ◽  
Conductive Film ◽  
Optimization Parameters ◽  
Connection Length ◽  
Conductive Particles

Anisotropic conductive film (ACF) interconnection is used for mounting electronic components, because this method can decrease the mounting area and electric connection length, as well as the thermal stress in the connecting area. An ACF comprises thermosetting resin and conductive particles. The resin is heated and its curing rate and viscosity changes complexly with the heating temperature during the process. There are several requirements for the heating temperature history from the industrial viewpoint such as the reliability of adhesion and energy efficiency. These requirements are related to the curing rate and the viscosity of the resin. A global optimization method proposed for nonlinear programming problems is adopted to optimize the values of the curing reaction parameters and the temperature history. First, the values of parameters in the functions determining the curing rate and viscosity are identified, and the curing rate and viscosity calculated using the values of the parameters agree well with the experimental data. Then, several optimization examples clarify features of the optimum heating temperature history. It is possible to increase the final curing rate to ensure adhesion and to control the viscosity in the bubble-removing process. The period in which bubbles are removed can be changed by the setting of the optimization parameters. It is also possible to minimize the heat input and ensure the required final curing rate. These results clarify that the temperature history for ACF interconnection can be determined accurately by the presented global optimization approach.

scholarly journals Improved Cost Computation and Adaptive Shape Guided Filter for Local Stereo Matching of Low Texture Stereo Images

2020 ◽  
Vol 10 (5) ◽  
pp. 1869
Author(s):  
Hua Liu ◽  
Rui Wang ◽  
Yuanping Xia ◽  
Xiaoming Zhang
Keyword(s):  
Cost Function ◽  
Stereo Matching ◽  
Guided Filter ◽  
Disparity Map ◽  
Cost Aggregation ◽  
Dense Stereo Matching ◽  
Gradient Based ◽  
Matching Cost ◽  
Cost Measurement ◽  
Image Pairs

Dense stereo matching has been widely used in photogrammetry and computer vision applications. Even though it has a long research history, dense stereo matching is still challenging for occluded, textureless and discontinuous regions. This paper proposed an efficient and effective matching cost measurement and an adaptive shape guided filter-based matching cost aggregation method to improve the stereo matching performance for large textureless regions. At first, an efficient matching cost function combining enhanced image gradient-based matching cost and improved census transform-based matching cost is introduced. This proposed matching cost function is robust against radiometric variations and textureless regions. Following this, an adaptive shape cross-based window is constructed for each pixel and a modified guided filter based on this adaptive shape window is implemented for cost aggregation. The final disparity map is obtained after disparity selection and multiple steps disparity refinement. Experiments were conducted on the Middlebury benchmark dataset to evaluate the effectiveness of the proposed cost measurement and cost aggregation strategy. The experimental results demonstrated that the average matching error rate on Middlebury standard image pairs is 9.40%. Compared with the traditional guided filter-based stereo matching method, the proposed method achieved a better matching result in textureless regions.

scholarly journals The Design and Implementation of Postprocessing for Depth Map on Real-Time Extraction System

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Zhiwei Tang ◽  
Bin Li ◽  
Huosheng Li ◽  
Zheng Xu
Keyword(s):  
Real Time ◽  
Stereo Matching ◽  
Depth Map ◽  
Depth Estimation ◽  
Consistency Check ◽  
Key Technology ◽  
Design And Implementation ◽  
Depth Maps ◽  
Matching Cost

Depth estimation becomes the key technology to resolve the communications of the stereo vision. We can get the real-time depth map based on hardware, which cannot implement complicated algorithm as software, because there are some restrictions in the hardware structure. Eventually, some wrong stereo matching will inevitably exist in the process of depth estimation by hardware, such as FPGA. In order to solve the problem a postprocessing function is designed in this paper. After matching cost unique test, the both left-right and right-left consistency check solutions are implemented, respectively; then, the cavities in depth maps can be filled by right depth values on the basis of right-left consistency check solution. The results in the experiments have shown that the depth map extraction and postprocessing function can be implemented in real time in the same system; what is more, the quality of the depth maps is satisfactory.

scholarly journals Synthesis of Strategic Games with Multiple Nash Equilibria - A Global Optimization Approach

2019 ◽  
Author(s):  
Hime Oliveira
Keyword(s):  
Global Optimization ◽  
Nash Equilibrium ◽  
Nash Equilibria ◽  
Optimization Method ◽  
Optimization Techniques ◽  
Optimization Approach ◽  
Strategic Games ◽  
Finite State ◽  
Payoff Functions ◽  
Multiple Nash Equilibria

This paper presents an extension of the resuts obtained in previous work by the author concerning the application of global optimization techniques to the design of finite strategic games with mixed strategies. In that publication the Fuzzy ASA global optimization method was applied to many examples of synthesis of strategic games with one previously specified Nash equilibrium, evidencing its ability in finding payoff functions whose respective games present those equilibria, possibly among others. That is to say, it was shown it is possible to establish in advance a Nash equilibrium for a generic finite state strategic game and to compute payoff functions that will make it feasible to reach the chosen equilibrium, allowing players to converge to the desired profile, considering that it is an equilibrium of the game as well. Going beyond this state of affairs, the present article shows that it is possible to "impose" multiple Nash equilibria to finite strategic games by following the same reasoning as before, but with a slight change: using the same fundamental theorem of Richard D. McKelvey, modifying the original prescribed objective function and globally minimizing it. The proposed method, in principle, is able to find payoff functions that result in games featuring an arbitrary number of Nash equiibria, paving the way to a substantial number of potential applications.

scholarly journals Optimization Approach for Long-Term Planning of Charging Infrastructure for Fixed-Route Transportation Systems

2021 ◽  
Vol 12 (4) ◽  
pp. 258
Author(s):  
Benjamin Daniel Blat Belmonte ◽  
Stephan Rinderknecht
Keyword(s):  
Critical Role ◽  
Cost Optimization ◽  
Optimization Method ◽  
Transportation Systems ◽  
Limiting Factors ◽  
Mixed Integer ◽  
Optimization Approach ◽  
Charging Infrastructure ◽  
Term Operation

As the electrification of the transportation sector advances, fleet operators have to rethink their approach regarding fleet management against the background of limiting factors, such as a reduced range or extended recharging times. Charging infrastructure plays a critical role, and it is worthwhile to consider its planning as an integral part for the long-term operation of an electric vehicle fleet. In the category of fixed route transportation systems, the predictable character of the routes can be exploited when planning charging infrastructure. After a prior categorization of stakeholders and their respective optimization objectives in the sector coupling domain, a cost optimization framework for fixed route transportation systems is presented as the main contribution of this work. We confirm previous literature in that there is no one-fits-all optimization method for this kind of problem. The method is tested on seven scenarios for the public transport operator of Darmstadt, Germany. The core optimization is formulated as a mixed integer linear programming (MILP) problem. All scenarios are terminated by the criterion of a maximum solving time of 48 h and provide feasible solutions with a relative MIP-gap between 7 and 24%.

The Application of the Combination of Monte Carlo Optimization Method based QSAR Modeling and Molecular Docking in Drug Design and Development

2020 ◽  
Vol 20 (14) ◽  
pp. 1389-1402 ◽  
Author(s):  
Maja Zivkovic ◽  
Marko Zlatanovic ◽  
Nevena Zlatanovic ◽  
Mladjan Golubović ◽  
Aleksandar M. Veselinović
Keyword(s):  
Monte Carlo ◽  
Molecular Docking ◽  
Computer Calculation ◽  
Molecular Graph ◽  
Optimization Method ◽  
Docking Studies ◽  
Optimization Approach ◽  
Qsar Modeling ◽  
Monte Carlo Optimization ◽  
Molecular Docking Studies

In recent years, one of the promising approaches in the QSAR modeling Monte Carlo optimization approach as conformation independent method, has emerged. Monte Carlo optimization has proven to be a valuable tool in chemoinformatics, and this review presents its application in drug discovery and design. In this review, the basic principles and important features of these methods are discussed as well as the advantages of conformation independent optimal descriptors developed from the molecular graph and the Simplified Molecular Input Line Entry System (SMILES) notation compared to commonly used descriptors in QSAR modeling. This review presents the summary of obtained results from Monte Carlo optimization-based QSAR modeling with the further addition of molecular docking studies applied for various pharmacologically important endpoints. SMILES notation based optimal descriptors, defined as molecular fragments, identified as main contributors to the increase/ decrease of biological activity, which are used further to design compounds with targeted activity based on computer calculation, are presented. In this mini-review, research papers in which molecular docking was applied as an additional method to design molecules to validate their activity further, are summarized. These papers present a very good correlation among results obtained from Monte Carlo optimization modeling and molecular docking studies.

scholarly journals A Kriging-Assisted Multi-Objective Constrained Global Optimization Method for Expensive Black-Box Functions

Mathematics ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 149
Author(s):  
Yaohui Li ◽  
Jingfang Shen ◽  
Ziliang Cai ◽  
Yizhong Wu ◽  
Shuting Wang
Keyword(s):  
Global Optimization ◽  
Pareto Frontier ◽  
Kriging Model ◽  
Optimization Method ◽  
Function Evaluation ◽  
Sampling Point ◽  
Constrained Global Optimization ◽  
Multi Objective ◽  
Sample Data ◽  
Sampling Points

The kriging optimization method that can only obtain one sampling point per cycle has encountered a bottleneck in practical engineering applications. How to find a suitable optimization method to generate multiple sampling points at a time while improving the accuracy of convergence and reducing the number of expensive evaluations has been a wide concern. For this reason, a kriging-assisted multi-objective constrained global optimization (KMCGO) method has been proposed. The sample data obtained from the expensive function evaluation is first used to construct or update the kriging model in each cycle. Then, kriging-based estimated target, RMSE (root mean square error), and feasibility probability are used to form three objectives, which are optimized to generate the Pareto frontier set through multi-objective optimization. Finally, the sample data from the Pareto frontier set is further screened to obtain more promising and valuable sampling points. The test results of five benchmark functions, four design problems, and a fuel economy simulation optimization prove the effectiveness of the proposed algorithm.

Sign in / Sign up

Export Citation Format

Share Document