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نتیجه جستجو - Stereo vision

تعداد مقالات یافته شده: 20
ردیف عنوان نوع
1 Research on evaluation method of stereo vision measurement system based on parameter-driven
تحقیق در مورد روش ارزیابی سیستم اندازه گیری دید استریو بر اساس پارامتر محور-2021
Stereo vision measurement system is widely used in aerospace manufacturing, intelligent robot and other fields because of its unique advantages. However, when using the stereo vision measurement system for measurement, there is no guidance for the parameter configuration of the measurement system for the scene and task constraints, resulting in the stereo vision measurement system cannot play the maximum performance. In this paper, from two aspects of local measurement of camera parameters and global measurement of system parameters, the relevant model is established to analyze the measurement performance of a single independent camera and the performance of the whole stereo vision measurement system. Firstly, the relationship between single camera calibration parameters and measurement accuracy is analyzed; secondly, the relationship between stereo measurement system parameters and measurement accuracy is analyzed; finally, the stereo vision measurement error function is established to guide the design of measurement system parameters. According to the actual measurement experiment, the correctness of the analysis and the accuracy of the established function are verified, it is efficiently used for guiding the parameter design and camera selection of the measurement system in different measurement scene and task.
Keywords: Vision measurement | Stereo vision | Error analysis | Parameter-driven
مقاله انگلیسی
2 Stereo disparity optimization with depth change constraint based on a continuous video
بهینه سازی اختلاف استریو با محدودیت تغییر عمق بر اساس یک فیلم مداوم-2021
Three-dimensional reconstruction based on stereo vision technology is an important research direction in the field of computer vision, and has a wide range of applications in industrial measurement, medical image reconstruction, cultural relic preservation, robot navigation, virtual reality and other fields. However, the three- dimensional reconstruction of moving objects usually has poor accuracy, low efficiency and poor visualization effect due to the image noise, motion blur, complex and time-consuming calculation etc. In this article, a disparity optimization method based on depth change constraint is proposed, which utilizes the correlation of the adjacent frames in the continuous video sequence to eliminate mismatches and correct the wrong disparity values by introducing a depth change constraint threshold. The experiments on the video images which are taken by a binocular stereo vision system demonstrate that our method of removing incorrect matches bears satisfactory results and it can greatly improve the effect of the three-dimensional reconstruction of the moving objects.
Keywords: Disparity optimization | Three-dimensional reconstruction | Depth change constraint | Video images
مقاله انگلیسی
3 Stereo disparity optimization with depth change constraint based on a continuous video
بهینه سازی اختلاف استریو با محدودیت تغییر عمق بر اساس یک فیلم مداوم-2021
Three-dimensional reconstruction based on stereo vision technology is an important research direction in the field of computer vision, and has a wide range of applications in industrial measurement, medical image reconstruction, cultural relic preservation, robot navigation, virtual reality and other fields. However, the three-dimensional reconstruction of moving objects usually has poor accuracy, low eciency and poor visualization eect due to the image noise, motion blur, complex and time-consuming calculation etc. In this article, a disparity optimization method based on depth change constraint is proposed, which utilizes the correlation of the adjacent frames in the continuous video sequence to eliminate mismatches and correct the wrong disparity values by introducing a depth change constraint threshold. The experiments on the video images which are taken by a binocular stereo vision system demonstrate that our method of removing incorrect matches bears satisfactory results and it can greatly improve the eect of the three-dimensional reconstruction of the moving objects.
Keywords: Disparity optimization | Three-dimensional reconstruction | Depth change constraint | Video images
مقاله انگلیسی
4 A measurement method of motion parameters in aircraft ground tests using computer vision
روش اندازه گیری پارامترهای حرکت در آزمایش های زمینی هواپیماها با استفاده از بینایی ماشین-2021
The purpose of this work is aiming at the problem of high precision and large-scale measurement of motion parameters of aircraft ground test. Based on the traditional vision measurement method of motion parameters, a new measurement method of motion parameters based on intersected planes is discussed. Firstly, the measurement of 3D coordinates of laser spots was performed using the 3 D vision technique combined with plane constraints of curtain wall, the images of laser spot projected on the parallel curtain wall were processed using the centroid method, the calibration of multi-coordinates were unified by the unique coordinate system method, then the pose was solved using the proposed method that the normal vector of the intersect plane fixed on the vehicle is used. Finally, according to the measurement principle, the influence of spot center positioning, camera parameter calibration and target geometric error on the calculation results of aircraft motion parameters is analyzed, and the error propagation model is given. The experimental results show that in the measurement range of 8000 mm × 4000 mm × 4000 mm, the measurement error of attitude parameters is less than 0.14◦, and the measurement error of position parameters is less than 2 mm. Compared with binocular stereo vision, the accuracy of attitude angle measurement is improved by 100%. Therefore, the measurement method proposed in this paper can achieve high precision and large-scale measurement of the motion parameters of the test aircraft.
Keywords: Machine vision | Aircraft ground test | Intersected planes | Motion parameters | Muti-coordinate system calibration
مقاله انگلیسی
5 A mobile stereo vision system with variable baseline distance for three-dimensional coordinate measurement in large FOV
یک سیستم دید استریو متحرک با فاصله پایه متغیر برای اندازه گیری مختصات سه بعدی در FOV بزرگ-2021
A novel mobile stereo vision system (MSVS) with variable baseline distance for three-dimensional (3D) coordinate measurement in large field of view (FOV) is established herein. Each independent mobile camera can rotate in the horizontal and vertical directions, and the position of the cameras are obtained by differential GPS in real time. In order to achieve rapid camera calibration in large FOV, a simplified model of MSVS based on differential GPS is constructed in this paper. A six-point method is proposed to quickly estimate the camera’s initial parameters (i.e. focal length, initial roll, pitch, and yaw angles) in the situation that the approximate value of the initial yaw angle is unknown. Moreover, the camera’s roll angle is equivalent to its approximate value measured by a high-precision inclinometer during the movement, and the unknown extrinsic parameters of each camera are reduced to the pitch and yaw angles after the camera moves. The refined pitch and yaw angles are eventually estimated by only using a single control point, which makes it possible that the 3D coordinate can be measured online after the camera moves. The computer simulation verifies the effectiveness of the extrinsic parameters calibration method using a single control point. The quantitative results demonstrate that the standard deviation of the focal length of the camera does not exceed 0.028 mm, and the mobile camera’s pitch angle and yaw angle estimated by a single control point is extremely close to the reference values. In addition, the average error of the 3D coordinate on each axis after the camera moves is smaller than 0.08 m in the measuring distance of 100 m, and that on X-axis and Z-axis is comparable and does not exceed 0.35 m. The proposed methods are suitable for the occasions that high accuracy is not required in the field of 3D coordinate measurement in large FOV.
Keywords: Mobile stereo vision system | Variable baseline distance | Initial parameters | Extrinsic parameters | Large field of view
مقاله انگلیسی
6 A portable three-component displacement measurement technique using an unmanned aerial vehicle (UAV) and computer vision: A proof of concept
تکنیک اندازه گیری جابجایی سه جزء قابل حمل با استفاده از هواپیمای بدون سرنشین (UAV) و بینایی ماشین: اثبات مفهوم-2021
This study proposes a new remote sensing technique to measure three-component (3C) dynamic displacement of three-dimensional (3D) structures. A sensing system with a UAV platform and contact-free sensors (e.g., optical and infrared (IR) cameras) is employed to provide a portable and convenient alternative to conventional approaches that require sensor installation on a structure. The original contributions of this study include (1) integrating both optical and IR cameras with a UAV platform to measure dynamic structural response, and (2) developing new data post-processing algorithms (based on target identification, Direct Linear Transformation, and active stereo vision) to simultaneously extract the 3C displacement of a 3D structure from optical and IR videos, which presents a unique advantage compared to the existing UAV-based displacement measurement techniques that allow the measurements in only one or two directions using optical cameras or laser sensors. The efficacy of the proposed technique is validated through laboratory experiments.
Keywords: Computer vision | Structural health monitoring (SHM) | Unmanned aerial vehicle (UAV) | Dynamic displacement | Bridge inspection
مقاله انگلیسی
7 Uncalibrated stereo vision with deep learning for 6-DOF pose estimation for a robot arm system
دید استریو کالیبره نشده با یادگیری عمیق برای برآورد 6-DOF برای سیستم بازوی ربات-2021
This paper proposes a novel method for six degrees of freedom pose estimation of objects for the application of robot arm pick and place. It is based on the use of a stereo vision system, which does not require calibration. Using both cameras, four corner points of the object are detected. A deep-neural- network (DNN) is trained for the prediction of the 6 DOF pose of the object from the four detected corner points’ coordinates in each image of both cameras. The stereo vision used is a low-end vision system placed in a custom-made setup. Before the training phase of the DNN, the robot is set to auto collect data in a predefined workspace. This workspace is defined dependently on the spatial feasibility of the robot arm and the shared field of view of the stereo vision system. The collected data represent images of a 2D marker attached to the robot arm gripper. The 2D marker is used for data collection to ease the detection of the four corner points. The proposed method succeeds in estimating the six degrees of freedom pose of the object, without the need for the determination of neither the intrinsic nor the extrinsic parameters of the stereo vision system. The optimum design of the proposed DNN is obtained after comparing different activation functions and optimizers associated with the DNN. The proposed uncalibrated DNN-based method performance is compared to that of the traditional calibration-based method. In the calibration-based method, the rotational matrix relating the robot coordinates to the stereo vision coordinates is computed using two approaches. The first approach uses Singular Value Decomposition (SVD) while the second approach uses a novel proposed modification of particle swarm optimization (PSO) called Hyper particle Scouts optimization (HPSO). HPSO outperforms other metaheuristic optimization algorithms such as PSO and genetic algorithm (GA).Exhaustive tests are performed, and the proposed DNN-based method is shown to outperform all tested alternatives.© 2021 Elsevier B.V. All rights reserved.
Keywords: Deep learning | Pose estimation | Robot vision | Stereo vision | Optimization techniques | Levenberg–Marquardt algorithm
مقاله انگلیسی
8 Artificial intelligence quality inspection of steel bars installation by integrating mask R-CNN and stereo vision
بازرسی کیفیت هوش مصنوعی نصب میله های فولادی با ادغام ماسک R-CNN و دید استریو-2021
Contractors should conduct strict quality inspection of the steel bars used in concrete structures and need to automate the process of quality inspection. The objective of this study is to develop an Artificial Intelligence Quality Inspection Model (AI-QIM) that can execute quality inspection on steel bars at the construction site. The proposed AI-QIM is built on the Mask Region-based Convolutional Neural Network (Mask R-CNN) technique, which can perform instance segmentation of steel bars. This object detection technique is integrated with a stereo vision camera to generate information on steel bar installation. A contractor can use the proposed AI-QIM to estimate the quantity, spacing, diameter, and length of steel bars during quality inspection. A sample case study indicated that the AI-QIM yielded a maximum relative error of 3% when measuring steel bar spacing and a maximum relative error of 8% when measuring steel bar lengths within a range of 1–2 m from a stereo camera.
Keywords: Steel bar | Quality inspection | Artificial intelligence | Convolutional Neural Network (CNN) | Mask R-CNN | Stereo vision | Object detection | Object mask | Instance segmentation
مقاله انگلیسی
9 Neural markers of suppression in impaired binocular vision
نشانگرهای عصبی سرکوب در اختلال بینایی دو چشمی-2021
Even after conventional patching treatment, individuals with a history of amblyopia typically lack good stereo vision. This is often attributed to atypical suppression between the eyes, yet the specific mechanism is still un- clear. Guided by computational models of binocular vision, we tested explicit predictions about how neural responses to contrast might differ in individuals with impaired binocular vision. Participants with a history of amblyopia (N = 25), and control participants with typical visual development (N = 19) took part in the study. Neural responses to different combinations of contrast in the left and right eyes, were measured using both electro encephalography (EEG) and functional magnetic resonance imaging (fMRI). Stimuli were sinusoidal gratings with a spatial frequency of 3c/deg, flickering at 4 Hz. In the fMRI experiment, we also ran population receptive field and retinotopic mapping sequences, and a phase-encoded localizer stimulus, to identify voxels in primary visual cortex (V1) sensitive to the main stimulus. Neural responses in both modalities increased monotonically with stimulus contrast. When measured with EEG, responses were attenuated in the weaker eye, consistent with a fixed tonic suppression of that eye. When measured with fMRI, a low contrast stimulus in the weaker eye substantially reduced the response to a high contrast stimulus in the stronger eye. This effect was stronger than when the stimulus-eye pairings were reversed, consistent with unbalanced dynamic suppression between the eyes. Measuring neural responses using different methods leads to different conclusions about visual differences in individuals with impaired binocular vision. Both of the atypical suppression effects may relate to binocular perceptual deficits, e.g. in stereopsis, and we anticipate that these measures could be informative for monitoring the progress of treatments aimed at recovering binocular vision.
Keywords: Dichoptic | fMRI | Interocular suppression | SSVEP | V1
مقاله انگلیسی
10 Application of integrated binocular stereo vision measurement and wireless sensor system in athlete displacement test
استفاده از سیستم اندازه گیری دید استریو بصری یکپارچه و سیستم حسگر بی سیم در آزمون جابجایی ورزشکاران-2021
Based on binocular stereo vision measurement and wireless sensing theory, this paper studies the measurement and analysis methods of athletes’ movement displacement parameters. The main purpose is to explore the relationship between sports biomechanical parameters. The analysis reveals the laws of athletes ’movements, and provides theoretical guidance on athletes’ attitude recognition and physical training. Based on the principle of binocular stereo vision, a noncontact displacement measurement system was developed. The displacement measurement system uses template matching to extract the image coordinates of the measurement points and restore the spatial coordinates of the measurement points through European 3D reconstruction, which improves the practicality of the measurement system. In the cantilever beam vibration test, the traditional displacement sensor and binocular image displacement measurement system are used to simultaneously measure the cantilever beam displacement. The experimental results show that the integrated displacement measurement system in this paper has higher accuracy and better stability.
KEYWORDS: Binocular stereo vision | Non-contact measurement | Mobile control | Node displacement | Wireless sensor system
مقاله انگلیسی
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