Depth estimation algorithm based on data-driven approach and depth cues for stereo conversion in three-dimensional displays

2016 ◽  
Vol 55 (12) ◽  
pp. 123106 ◽  
Author(s):  
Huihui Xu ◽  
Mingyan Jiang ◽  
Fei Li
Keyword(s):  
Three Dimensional ◽  
Depth Estimation ◽  
Estimation Algorithm ◽  
Data Driven ◽  
Depth Cues ◽  
Data Driven Approach

scholarly journals Sustainable City Planning: A Data-Driven Approach for Mitigating Urban Heat

2021 ◽  
Vol 6 ◽  
Author(s):  
Andrew MacLachlan ◽  
Eloise Biggs ◽  
Gareth Roberts ◽  
Bryan Boruff
Keyword(s):  
Urban Areas ◽  
City Planning ◽  
Climate Models ◽  
Global Climate ◽  
Three Dimensional ◽  
Global Climate Models ◽  
Data Driven ◽  
Climate Data ◽  
Data Driven Approach ◽  
Urban Heat

Urban areas are expected to triple by 2030 in order to accommodate 60% of the global population. Anthropogenic landscape modifications expand coverage of impervious surfaces inducing the urban heat island (UHI) effect, a critical twenty first century challenge associated with increased economic expenditure, energy consumption, and adverse health impacts. Yet, omission of UHI measures from global climate models and metropolitan planning methodologies precludes effective sustainable development governance. We present an approach that integrates Earth observation and climate data with three-dimensional urban models to determine optimal tree placement (per square meter) within proposed urban developments to enable more effective localized UHI mitigation. Such data-driven planning decisions will enhance the future sustainability of our cities to align with current global urban development agendas.

scholarly journals Optimal Missing Value Estimation Algorithm for Groundwater Levels

Proceedings ◽  
2018 ◽  
Vol 2 (11) ◽  
pp. 698 ◽  
Author(s):  
Klemen Kenda ◽  
Filip Koprivec ◽  
Dunja Mladenić
Keyword(s):  
Missing Data ◽  
Missing Values ◽  
Estimation Algorithm ◽  
Data Driven ◽  
Data Imputation ◽  
Missing Data Imputation ◽  
Groundwater Levels ◽  
Data Driven Approach ◽  
Value Estimation ◽  
Missing Value Estimation

In this study an algorithm for missing data imputation is presented. The algorithm uses measurements from neighboring sensors to estimate the missing values. Data-driven approach is used and methodology chooses the optimal available combination of modeling algorithm and available measurements to produce an estimate from the model with lowest error. The methodology was tested on Ljubljana polje aquifer data and has produced close to perfect results.

Depth Analogy: Data-Driven Approach for Single Image Depth Estimation Using Gradient Samples

2015 ◽  
Vol 24 (12) ◽  
pp. 5953-5966 ◽  
Author(s):  
Sunghwan Choi ◽  
Dongbo Min ◽  
Bumsub Ham ◽  
Youngjung Kim ◽  
Changjae Oh ◽  
...  
Keyword(s):  
Depth Estimation ◽  
Data Driven ◽  
Single Image ◽  
Data Driven Approach ◽  
Image Depth

scholarly journals Event-based stereo matching using semiglobal matching

2018 ◽  
Vol 15 (1) ◽  
pp. 172988141775275 ◽  
Author(s):  
Zhen Xie ◽  
Jianhua Zhang ◽  
Pengfei Wang
Keyword(s):  
Stereo Matching ◽  
Dynamic Range ◽  
Three Dimensional ◽  
Depth Estimation ◽  
Estimation Algorithm ◽  
Frame Rate ◽  
Estimation Accuracy ◽  
High Temporal Resolution ◽  
Stereo Pair ◽  
Event Based

In this article, we focus on the problem of depth estimation from a stereo pair of event-based sensors. These sensors asynchronously capture pixel-level brightness changes information (events) instead of standard intensity images at a specified frame rate. So, these sensors provide sparse data at low latency and high temporal resolution over a wide intrascene dynamic range. However, new asynchronous, event-based processing algorithms are required to process the event streams. We propose a fully event-based stereo three-dimensional depth estimation algorithm inspired by semiglobal matching. Our algorithm considers the smoothness constraints between the nearby events to remove the ambiguous and wrong matches when only using the properties of a single event or local features. Experimental validation and comparison with several state-of-the-art, event-based stereo matching methods are provided on five different scenes of event-based stereo data sets. The results show that our method can operate well in an event-driven way and has higher estimation accuracy.

Improving the Accuracy of Depth Estimation in Binocular Vision for Robotic Applications

2013 ◽  
Vol 284-287 ◽  
pp. 1862-1866 ◽  
Author(s):  
Kuan Yu Chen ◽  
Cheng Chin Chien ◽  
Chien Te Tseng
Keyword(s):  
Binocular Vision ◽  
Stereo Vision ◽  
Computational Models ◽  
Stereo Matching ◽  
Focal Length ◽  
Three Dimensional ◽  
Estimation Method ◽  
Depth Estimation ◽  
Estimation Algorithm ◽  
Dimensional Structure

Binocular vision or stereo vision for extraction of three-dimensional information from stereo images has been widely used in many applications like robot navigation, recovering the three-dimensional structure of a scene, and optical inspection systems. More recently, the majority of research in binocular vision has focused on the establishment of stereo matching. However, to date, there has been relatively little research conducted on the effect of computational models of binocular vision with variable focal length of lens. In this paper, a modified computational model of binocular vision is presented to develop a new depth estimation algorithm with no effect of changes in focal length. This method provides an obvious advantage in accuracy of depth estimation by reducing the effect of changing the lens focal length. The experimental results show that the proposed depth estimation method in binocular vision provides better accuracy than conventional method. Finally, we apply the new depth estimation method to a stereo-vision-based automatic docking system for a mobile robot to verify its accuracy.

scholarly journals A three-dimensional model for rain-wind induced vibration of stay cables in cable-stayed bridges

2020 ◽  
Vol 14 (1) ◽  
pp. 15-27
Author(s):  
Nguyen Thi Hai Nhu ◽  
Tran Anh Binh ◽  
Ha Manh Hung
Keyword(s):  
Elastic Moduli ◽  
Heterogeneous Media ◽  
Effective Properties ◽  
Spherical Inclusion ◽  
Three Dimensional ◽  
Main Idea ◽  
Data Driven ◽  
Effective Elastic Moduli ◽  
Three Dimensional Model ◽  
Data Driven Approach

The most rigorous effective medium approximations for elastic moduli are elaborated for matrix composites made from an isotropic continuous matrix and isotropic inclusions associated with simple shapes such as circles or spheres. In this paper, we focus specially on the effective elastic moduli of the heterogeneous composites with arbitrary inclusion shapes. The main idea of this paper is to replace those inhomogeneities by simple equivalent circular (spherical) isotropic inclusions with modified elastic moduli. Available simple approximations for the equivalent circular (spherical) inclusion media then can be used to estimate the effective properties of the original medium. The data driven technique is employed to estimate the properties of equivalent inclusions and the Extended Finite Element Method is introduced to modeling complex inclusion shapes. Robustness of the proposed approach is demonstrated through numerical examples with arbitrary inclusion shapes. Keywords: data driven approach; equivalent inclusion, effective elastic moduli; heterogeneous media; artificial neural network.

scholarly journals Three-Dimensional Reconstruction of Light Field Based on Phase Similarity

Sensors ◽  
2021 ◽  
Vol 21 (22) ◽  
pp. 7734
Author(s):  
Wei Feng ◽  
Junhui Gao ◽  
Tong Qu ◽  
Shiqi Zhou ◽  
Daxing Zhao
Keyword(s):  
3D Reconstruction ◽  
Light Field ◽  
Three Dimensional ◽  
Ground Truth ◽  
Depth Estimation ◽  
Estimation Algorithm ◽  
Morphological Processing ◽  
Disparity Estimation ◽  
Reconstruction Method ◽  
Disparity Map

Light field imaging plays an increasingly important role in the field of three-dimensional (3D) reconstruction because of its ability to quickly obtain four-dimensional information (angle and space) of the scene. In this paper, a 3D reconstruction method of light field based on phase similarity is proposed to increase the accuracy of depth estimation and the scope of applicability of epipolar plane image (EPI). The calibration method of the light field camera was used to obtain the relationship between disparity and depth, and the projector calibration was removed to make the experimental procedure more flexible. Then, the disparity estimation algorithm based on phase similarity was designed to effectively improve the reliability and accuracy of disparity calculation, in which the phase information was used instead of the structure tensor, and the morphological processing method was used to denoise and optimize the disparity map. Finally, 3D reconstruction of the light field was realized by combining disparity information with the calibrated relationship. The experimental results showed that the reconstruction standard deviation of the two objects was 0.3179 mm and 0.3865 mm compared with the ground truth of the measured objects, respectively. Compared with the traditional EPI method, our method can not only make EPI perform well in a single scene or blurred texture situations but also maintain good reconstruction accuracy.

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