scholarly journals Pose Estimation under Visual Sensing Technology and Its Application in Art Design

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Bing Song ◽  
Meng Li ◽  
Liping Lou
Keyword(s):  
Pose Estimation ◽  
Vision System ◽  
Three Dimensional ◽  
Human Motion ◽  
Environmental Art ◽  
Visual Sensing ◽  
Sensing Technology ◽  
Binocular Stereo Vision ◽  
Binocular Stereo ◽  
Art Design

The study is aimed at solving the problem of large measurement errors caused by the binocular camera in traditional 3D art design, which leads to inaccurate 3D information of the target. The contour information extraction in the process of human motion pose reconstruction is easily affected by the noise in the image. Therefore, a binocular stereo vision system is built first and it integrates image acquisition, camera calibration, and image processing. The dedistortion method is used to process the image because it can reduce errors. Second, a three-dimensional human motion pose reconstruction model is implemented, the Gaussian template is used to remove the noise in the image frame, and the change detection template (CDM) is used to solve the problem of background “exposure” and “occlusion.” Finally, simulation experiments are designed to verify the system and model designed. Since the research on the application of pose estimation based on visual sensing technology in art design is still blank, such research has great significance and provides a reference for the research in the field. The literature analysis is used to expound and analyze the application of pose estimation based on visual sensing technology in visual communication design and environmental art design: (1) although the binocular stereo vision system causes some errors in the measurement, the overall error is controlled within 2% and the accuracy is high, which proves that it can be applied to the acquisition of three-dimensional information of the target in art design; (2) there is a high degree of fitting between the video sequence data created by the three-dimensional human motion pose reconstruction model designed and the real motion data, which indicates that this method has high accuracy in processing image sequences and the feasibility of applying it to human pose reconstruction in three-dimensional art design is high; (3) through the analysis of the existing literature, it is found that most of the current visual-based attitude assessment studies are carried out by using network cameras combined with computers, and the quality of the obtained images is low. The combination of binocular stereo sensor and attitude estimation technology can be applied to the design of advertising, animation, games, and packaging, making the behavior of virtual characters in animation and games more vivid. The combination provides convenience for the collection of environmental spatial information and object attitude information, the formulation of a design scheme, and real-time monitoring of construction in environmental art design. The purpose of this study is to provide an important theoretical basis for the technical upgrading of art design.

System Design of Crane Robot Based on Binocular Stereo Vision

2013 ◽  
Vol 303-306 ◽  
pp. 1691-1694
Author(s):  
Zhi Kun Chen ◽  
Hong Yan Wang ◽  
Wen Hui Wang ◽  
Fu Bin Wang
Keyword(s):  
Stereo Vision ◽  
Production Efficiency ◽  
High Efficiency ◽  
Vision System ◽  
Three Dimensional ◽  
System Structure ◽  
Mature Stage ◽  
Security Risks ◽  
Binocular Stereo Vision ◽  
Binocular Stereo

In order to improve the safety, high efficiency and stability in the process of the crane hoisting, this paper applied binocular stereo vision technology which has developed into a rather mature stage recently. Binocular stereo vision system could efficiently identify and accurately position various targets, so that it could decrease the crane driver’s working intensity, reduce security risks and improve the production efficiency. In order to experiments was convenient, developing the crane robot system could simulate the processes of crane work, establishing the relevant system structure model for the motion. According to the three-dimensional measuring principle of binocular stereo vision, this paper is proposed to identify and position for the targets, and experimental results show the error is ±10mm.

Vision-Based Aerial Refueling Docking Based on SURF Algorithm

2011 ◽  
Vol 130-134 ◽  
pp. 3102-3106
Author(s):  
Si Yuan Qin ◽  
Jian Guo Yan
Keyword(s):  
Vision System ◽  
Three Dimensional ◽  
Spatial Position ◽  
Target Point ◽  
Feature Points ◽  
Aerial Refueling ◽  
Matching Algorithm ◽  
Binocular Stereo Vision ◽  
Binocular Stereo ◽  
Left And Right

For the Boom and Receptacle Air Refueling, in order to locate the spatial position of the refueling receptacle, an object locating method is developed based on Speeded-up Robust Feature (SURF) algorithm. Firstly, SURF feature vector matching algorithm is used to detect and collect suitable SURF feature points in left and right images produced by binocular stereo vision system separately. Then the point that shows the same spatial position in both left and right images can be located through process such as deleting wrong matching points and calculating the image coordinate of the target point. Finally, the three-dimensional coordinates of the target points could be rebuilt in the camera’s coordinate system. According to the results of experiments, this method has good robustness and practicability.

Research on Cotton Row Detection Algorithm Based on Binocular Vision

2014 ◽  
Vol 670-671 ◽  
pp. 1222-1227 ◽  
Author(s):  
Zhong Xiang Zhu ◽  
Yan He ◽  
Zhi Qiang Zhai ◽  
Jin Yi Liu ◽  
En Rong Mao
Keyword(s):  
Stereo Vision ◽  
Vision System ◽  
Three Dimensional ◽  
Measuring Method ◽  
Detection Algorithm ◽  
High Accuracy ◽  
Depth Information ◽  
Automatic Navigation ◽  
Binocular Stereo Vision ◽  
Binocular Stereo

As a relative locating method, machine vision is generally used for automatic navigation of cotton cultivator or cotton insecticide sprayer. However, it is difficult to achieve reliable and stable recognition of crop row with monocular stereo vision system, because it neither can access directly to the depth information of the image, which leads to massive time-consuming calculation, nor possess high-accuracy recognition or a good anti-noise property. This paper presents an algorithm for cotton row detection based on binocular stereo vision to be used for automatic navigation of cotton cultivator. The Zhang's plane calibration is used to obtain the internal and external parameters of the binocular stereo vision. Preprocessing means are applied to distinguish the cotton from soil, stereoscopic match is conducted according to the SIFT operators after the preprocessing of images, after which cotton space three-dimensional coordinates are acquired by parallax distance measuring method, with the elevation information combination of Hough transform, cotton lines are finally detected. The detection results indicate that this method has an accuracy higher than 90%, which primarily meets the need of automatic navigation for cotton cultivator.

scholarly journals High-Accuracy Recognition and Localization of Moving Targets in an Indoor Environment Using Binocular Stereo Vision

2021 ◽  
Vol 10 (4) ◽  
pp. 234
Author(s):  
Jing Ding ◽  
Zhigang Yan ◽  
Xuchen We
Keyword(s):  
Stereo Vision ◽  
Stereo Matching ◽  
Three Dimensional ◽  
Target Localization ◽  
Parallel Structure ◽  
Moving Target ◽  
Target Area ◽  
Moving Targets ◽  
Binocular Stereo Vision ◽  
Binocular Stereo

To obtain effective indoor moving target localization, a reliable and stable moving target localization method based on binocular stereo vision is proposed in this paper. A moving target recognition extraction algorithm, which integrates displacement pyramid Horn–Schunck (HS) optical flow, Delaunay triangulation and Otsu threshold segmentation, is presented to separate a moving target from a complex background, called the Otsu Delaunay HS (O-DHS) method. Additionally, a stereo matching algorithm based on deep matching and stereo vision is presented to obtain dense stereo matching points pairs, called stereo deep matching (S-DM). The stereo matching point pairs of the moving target were extracted with the moving target area and stereo deep matching point pairs, then the three dimensional coordinates of the points in the moving target area were reconstructed according to the principle of binocular vision’s parallel structure. Finally, the moving target was located by the centroid method. The experimental results showed that this method can better resist image noise and repeated texture, can effectively detect and separate moving targets, and can match stereo image points in repeated textured areas more accurately and stability. This method can effectively improve the effectiveness, accuracy and robustness of three-dimensional moving target coordinates.

<i>A Binocular Stereo Vision System of Fruits Picking Robots Based on Embedded System </i>

2020 ◽  
Author(s):  
Pengcheng Wang ◽  
Zenghong Ma ◽  
Xiaoqiang Du ◽  
Wenwu Lu ◽  
Wensong Xing ◽  
...  
Keyword(s):  
Embedded System ◽  
Stereo Vision ◽  
Vision System ◽  
Stereo Vision System ◽  
Binocular Stereo Vision ◽  
Binocular Stereo

A New Model of Binocular Stereo Coordinate Measurement System Based on Skew Ray Tracing

2004 ◽  
Vol 126 (1) ◽  
pp. 102-114 ◽  
Author(s):  
Psang Dain Lin ◽  
Te-tan Liao
Keyword(s):  
Ray Tracing ◽  
Stereo Vision ◽  
Vision System ◽  
System Modeling ◽  
Formation Theory ◽  
Coordinate Measurement ◽  
Reading Errors ◽  
Binocular Stereo Vision ◽  
Binocular Stereo ◽  
Tracing Method

Two-CCD binocular stereo vision systems using pinhole model are attracting research interest in many important fields such as 3-D coordinate measurement. However, new system modeling is difficult because of lack of fundamental imaging formation theory. In this paper, in order to measure a 3-D surface, we demonstrate how a binocular stereo vision system can be modeled by the proposed skew ray tracing method to study the geometric relations between the binocular camera images and the 3-D surface. In order to investigate the overall accuracy and resolution of this system, the influence of infinitesimal camera reading errors on measured coordinate errors is determined by sensitivity analysis. Experimental verification demonstrates that the performance of the proposed system is excellent.

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