Absolute Depth Measurement of Objects Based on Monocular Vision

2020 ◽  
Vol 29 (07n08) ◽  
pp. 2040011
Author(s):  
Zhongsheng Wang ◽  
Yufeng Lai ◽  
Sen Yang ◽  
Jiaqiong Gao
Keyword(s):  
Measurement Method ◽  
Three Dimensional ◽  
Target Object ◽  
Measurement Methods ◽  
Monocular Vision ◽  
Depth Information ◽  
Depth Measurement ◽  
Comparison Results ◽  
Feature Information ◽  
The Absolute

With the continuous development of computer vision technology and the continuous upgrading of digital imaging equipment, image depth measurement method is widely used in the fields of intelligent robotics, traffic assistance, three-dimensional modeling and three dimensional video production. The following are the drawbacks of the traditional depth information measurement method: the operation is complex, the cost is high, and the measuring equipment occupies a large space and the load. In this paper, based on the Harris-SIFT corner detection algorithm, a technique is proposed to measure the absolute depth information of the object in the image using monocular vision. First of all, after the monocular camera is used to obtain the image of the target object, the image segmentation algorithm based on the LBF model is used to preprocess the image. Then, Harris algorithm in multi-scale space and SFIT algorithm to reconstruct feature descriptors are used to extract feature information in the image. Finally, by comparing the feature information between image groups, the depth information of target object is calculated by using the formula of convex hull principle and camera imaging principle. The test platform is applied to carry out measurement tests for different depth measurement methods, and the actual depth data and measurement data of the target object are compared, so as to evaluate the accuracy of the measurement method. The comparison results show that the error rate between the actual distance and the measured distance is less than 3.5%, which can accurately measure the absolute depth of the object in static and short distance, and is superior to other measurement methods.

scholarly journals A novel method of 3D motion object’s position perception

2018 ◽  
Vol 246 ◽  
pp. 03020
Author(s):  
Tan Wei ◽  
Xuan Liu ◽  
Chen Yi ◽  
Erfu Yang
Keyword(s):  
Measurement Method ◽  
Moving Objects ◽  
Target Object ◽  
Monocular Vision ◽  
Position Information ◽  
Sorting Method ◽  
3D Objects ◽  
The Disabled ◽  
Novel Method ◽  
Location Measurement

With the development of industrial automation, location measurement of 3D objects is becoming more and more important, especially as it can provide necessary positional parameters for the manipulator to grasp the object accurately. In view of the disabled object which is in widespread use currently, its image is captured to obtain positional parameters and transmitted to manipulators in industry. The above process is delayed, affecting the work efficiency of the manipulator. A method for calculating the position information of target object in motion is proposed. This method uses monocular vision technology to track 3D moving objects，then uses contour sorting method to extract the minimum constrained contour rectangle, and combines the video alignment technology to realize the tracking. Thus, the measurement error is reduced. The experimental results and analysis show that the adopted measurement method is effective.

scholarly journals 3-D Point Cloud Registration Algorithm Based on Greedy Projection Triangulation

2018 ◽  
Vol 8 (10) ◽  
pp. 1776 ◽  
Author(s):  
Jian Liu ◽  
Di Bai ◽  
Li Chen
Keyword(s):  
Machine Vision ◽  
Point Cloud ◽  
Three Dimensional ◽  
Target Object ◽  
Initial Alignment ◽  
Registration Accuracy ◽  
Point Cloud Registration ◽  
Registration Algorithm ◽  
Feature Information ◽  
Complex Target

To address the registration problem in current machine vision, a new three-dimensional (3-D) point cloud registration algorithm that combines fast point feature histograms (FPFH) and greedy projection triangulation is proposed. First, the feature information is comprehensively described using FPFH feature description and the local correlation of the feature information is established using greedy projection triangulation. Thereafter, the sample consensus initial alignment method is applied for initial transformation to implement initial registration. By adjusting the initial attitude between the two cloud points, the improved initial registration values can be obtained. Finally, the iterative closest point method is used to obtain a precise conversion relationship; thus, accurate registration is completed. Specific registration experiments on simple target objects and complex target objects have been performed. The registration speed increased by 1.1% and the registration accuracy increased by 27.3% to 50% in the experiment on target object. The experimental results show that the accuracy and speed of registration have been improved and the efficient registration of the target object has successfully been performed using the greedy projection triangulation, which significantly improves the efficiency of matching feature points in machine vision.

scholarly journals Real-Time 3D Reconstruction Method Based on Monocular Vision

Sensors ◽  
2021 ◽  
Vol 21 (17) ◽  
pp. 5909
Author(s):  
Qingyu Jia ◽  
Liang Chang ◽  
Baohua Qiang ◽  
Shihao Zhang ◽  
Wu Xie ◽  
...  
Keyword(s):  
3D Reconstruction ◽  
Real Time ◽  
Visual Information ◽  
Three Dimensional ◽  
Position Estimation ◽  
Monocular Vision ◽  
Cluster Center ◽  
Reconstruction Method ◽  
The Real ◽  
Depth Measurement

Real-time 3D reconstruction is one of the current popular research directions of computer vision, and it has become the core technology in the fields of virtual reality, industrialized automatic systems, and mobile robot path planning. Currently, there are three main problems in the real-time 3D reconstruction field. Firstly, it is expensive. It requires more varied sensors, so it is less convenient. Secondly, the reconstruction speed is slow, and the 3D model cannot be established accurately in real time. Thirdly, the reconstruction error is large, which cannot meet the requirements of scenes with accuracy. For this reason, we propose a real-time 3D reconstruction method based on monocular vision in this paper. Firstly, a single RGB-D camera is used to collect visual information in real time, and the YOLACT++ network is used to identify and segment the visual information to extract part of the important visual information. Secondly, we combine the three stages of depth recovery, depth optimization, and deep fusion to propose a three-dimensional position estimation method based on deep learning for joint coding of visual information. It can reduce the depth error caused by the depth measurement process, and the accurate 3D point values of the segmented image can be obtained directly. Finally, we propose a method based on the limited outlier adjustment of the cluster center distance to optimize the three-dimensional point values obtained above. It improves the real-time reconstruction accuracy and obtains the three-dimensional model of the object in real time. Experimental results show that this method only needs a single RGB-D camera, which is not only low cost and convenient to use, but also significantly improves the speed and accuracy of 3D reconstruction.

A Three-Dimensional Measurement Method by Combining Binocular and Monocular Vision Systems

2008 ◽  
Vol 28 (7) ◽  
pp. 1338-1342 ◽  
Author(s):  
雷彦章 Lei Yanzhang ◽  
赵慧洁 Zhao Huijie ◽  
姜宏志 Jiang Hongzhi
Keyword(s):  
Measurement Method ◽  
Three Dimensional ◽  
Monocular Vision ◽  
Vision Systems ◽  
Dimensional Measurement ◽  
Three Dimensional Measurement

scholarly journals Characteristic of Motor Control in Three-Dimensional Circular Tracking Movements during Monocular Vision

2019 ◽  
Vol 2019 ◽  
pp. 1-16 ◽  
Author(s):  
Woong Choi ◽  
Liang Li ◽  
Jongho Lee
Keyword(s):  
Motor Control ◽  
Three Dimensional ◽  
Monocular Vision ◽  
Polar Coordinates ◽  
Depth Information ◽  
Visually Guided ◽  
The Subject ◽  
Tracking Movements ◽  
The Difference ◽  
Tracking Movement

Analysis of visually guided tracking movements is an important component of understanding human visuomotor control system. The aim of our study was to investigate the effects of different target speeds and different circular tracking planes, which provide different visual feedback of depth information, on temporal and spatial tracking accuracy. In this study, we analyze motor control characteristic of circular tracking movements during monocular vision in three-dimensional space using a virtual reality system. Three parameters in polar coordinates were analyzed: ΔR, the difference in the distance from the fixed pole; Δθ, the difference in the position angle; and Δω, the difference in the angular velocity. We compare the accuracy of visually guided circular tracking movements during monocular vision in two conditions: (1) movement in the frontal plane relative to the subject that requires less depth information and (2) movement in the sagittal plane relative to the subject that requires more depth information. We also examine differences in motor control at four different target speeds. The results show that depth information affects both spatial and temporal accuracy of circular tracking movement, whereas target speed only affects temporal accuracy of circular tracking movement. This suggests that different strategies of feedforward and feedback controls are performed in the tracking of movements.

scholarly journals Children’s outdoor active mobility behaviour and neighbourhood safety: a systematic review in measurement methods and future research directions

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Roula Zougheibe ◽  
Jianhong (Cecilia) Xia ◽  
Ashraf Dewan ◽  
Ori Gudes ◽  
Richard Norman
Keyword(s):  
Three Dimensional ◽  
Measurement Methods ◽  
Future Research ◽  
Inclusion Criteria ◽  
Eligibility Criteria ◽  
Research Directions ◽  
Spatial Locality ◽  
Mobility Behaviour ◽  
Health Studies ◽  
Future Research Directions

Abstract Background Numerous studies have examined the association between safety and primary school-aged children’s forms of active mobility. However, variations in studies’ measurement methods and the elements addressed have contributed to inconsistencies in research outcomes, which may be forming a barrier to advancing researchers’ knowledge about this field. To assess where current research stands, we have synthesised the methodological measures in studies that examined the effects of neighbourhood safety exposure (perceived and measured) on children’s outdoor active mobility behaviour and used this analysis to propose future research directions. Method A systematic search of the literature in six electronic databases was conducted using pre-defined eligibility criteria and was concluded in July 2020. Two reviewers screened the literature abstracts to determine the studies’ inclusion, and two reviewers independently conducted a methodological quality assessment to rate the included studies. Results Twenty-five peer-reviewed studies met the inclusion criteria. Active mobility behaviour and health characteristics were measured objectively in 12 out of the 25 studies and were reported in another 13 studies. Twenty-one studies overlooked spatiotemporal dimensions in their analyses and outputs. Delineations of children’s neighbourhoods varied within 10 studies’ objective measures, and the 15 studies that opted for subjective measures. Safety perceptions obtained in 22 studies were mostly static and primarily collected via parents, and dissimilarities in actual safety measurement methods were present in 6 studies. The identified schematic constraints in studies’ measurement methods assisted in outlining a three-dimensional relationship between ‘what’ (determinants), ‘where’ (spatial) and ‘when’ (time) within a methodological conceptual framework. Conclusions The absence of standardised measurement methods among relevant studies may have led to the current diversity in findings regarding active mobility, spatial (locality) and temporal (time) characteristics, the neighbourhood, and the representation of safety. Ignorance of the existing gaps and heterogeneity in measures may impact the reliability of evidence and poses a limitation when synthesising findings, which could result in serious biases for policymakers. Given the increasing interest in children’s health studies, we suggested alternatives in the design and method of measures that may guide future evidence-based research for policymakers who aim to improve children’s active mobility and safety.

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