scholarly journals High-precision Cone Center Point Extraction Method Based on Stereo Vision Feature Matching

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2528
Author(s):  
Songlin Bi ◽  
Yonggang Gu ◽  
Jiaqi Zou ◽  
Lianpo Wang ◽  
Chao Zhai ◽  
...  

A high precision optical tracking system (OTS) based on near infrared (NIR) trinocular stereo vision (TSV) is presented in this paper. Compared with the traditional OTS on the basis of binocular stereo vision (BSV), hardware and software are improved. In the hardware aspect, a NIR TSV platform is built, and a new active tool is designed. Imaging markers of the tool are uniform and complete with large measurement angle (>60°). In the software aspect, the deployment of extra camera brings high computational complexity. To reduce the computational burden, a fast nearest neighbor feature point extraction algorithm (FNNF) is proposed. The proposed method increases the speed of feature points extraction by hundreds of times over the traditional pixel-by-pixel searching method. The modified NIR multi-camera calibration method and 3D reconstruction algorithm further improve the tracking accuracy. Experimental results show that the calibration accuracy of the NIR camera can reach 0.02%, positioning accuracy of markers can reach 0.0240 mm, and dynamic tracking accuracy can reach 0.0938 mm. OTS can be adopted in high-precision dynamic tracking.


2019 ◽  
Vol 16 (6) ◽  
pp. 172988141989351
Author(s):  
Xi Zhang ◽  
Yuanzhi Xu ◽  
Haichao Li ◽  
Lijing Zhu ◽  
Xin Wang ◽  
...  

For the purpose of obtaining high-precision in stereo vision calibration, a large-size precise calibration target, which can cover more than half of the field of view is vital. However, large-scale calibration targets are very difficult to fabricate. Based on the idea of error tracing, a high-precision calibration method for vision system with large field of view by constructing a virtual 3-D calibration target with a laser tracker was proposed in this article. A virtual 3-D calibration target that covers the whole measurement space can be established flexibly and the measurement precision of the vision system can be traceable to the laser tracker. First, virtual 3-D targets by calculating rigid body transformation with unit quaternion method were constructed. Then, the high-order distortion camera model was taken into consideration. Besides, the calibration parameters were solved with Levenberg–Marquardt optimization algorithm. In the experiment, a binocular stereo vision system with the field of view of 4 × 3 × 2 m3 was built for verifying the validity and precision of the proposed calibration method. It is measured that the accuracy with the proposed method can be greatly improved comparing with traditional plane calibration method. The method can be widely used in industrial applications, such as in the field of calibrating large-scale vision-based coordinate metrology, and six-degrees of freedom pose tracking system for dimensional measurement of workpiece, as well as robotics geometrical accuracy detection and compensation.


Sensors ◽  
2019 ◽  
Vol 19 (12) ◽  
pp. 2671 ◽  
Author(s):  
Chunsheng Liu ◽  
Yu Guo ◽  
Shuang Li ◽  
Faliang Chang

You Only Look Once (YOLO) deep network can detect objects quickly with high precision and has been successfully applied in many detection problems. The main shortcoming of YOLO network is that YOLO network usually cannot achieve high precision when dealing with small-size object detection in high resolution images. To overcome this problem, we propose an effective region proposal extraction method for YOLO network to constitute an entire detection structure named ACF-PR-YOLO, and take the cyclist detection problem to show our methods. Instead of directly using the generated region proposals for classification or regression like most region proposal methods do, we generate large-size potential regions containing objects for the following deep network. The proposed ACF-PR-YOLO structure includes three main parts. Firstly, a region proposal extraction method based on aggregated channel feature (ACF) is proposed, called ACF based region proposal (ACF-PR) method. In ACF-PR, ACF is firstly utilized to fast extract candidates and then a bounding boxes merging and extending method is designed to merge the bounding boxes into correct region proposals for the following YOLO net. Secondly, we design suitable YOLO net for fine detection in the region proposals generated by ACF-PR. Lastly, we design a post-processing step, in which the results of YOLO net are mapped into the original image outputting the detection and localization results. Experiments performed on the Tsinghua-Daimler Cyclist Benchmark with high resolution images and complex scenes show that the proposed method outperforms the other tested representative detection methods in average precision, and that it outperforms YOLOv3 by 13.69 % average precision and outperforms SSD by 25.27 % average precision.


2014 ◽  
Vol 687-691 ◽  
pp. 3765-3768
Author(s):  
Nan Wang

A new edge extraction method was put forward based on the SUSAN operator, according to the problems of poor anti-noise ability and edge detection incomplete of the conventional differential detection operator. The circular template and the center of the circle (template nuclear) were used in this method, the numbers of pixels was calculated through the comparison pixels value of template with the other points of pixels in the template circle, and then compared with the threshold, so as to the edge of images was extracted. The results showed that this method had high precision, and could be able to fully extract the edge of images. It is an effective method of extracting the edge of images.


2013 ◽  
Vol 373-375 ◽  
pp. 619-623
Author(s):  
Yun Zhou Zhang ◽  
Shou Shuai Xu ◽  
Liang Gao ◽  
Shan Bao Yang ◽  
Xiao Lin Su

In both industrial field and office building, the accurate statistic of people who enter or leave the elevator has important practical meaning in security and analysis of passenger flow. We present a binocular vision system to count the people pass by. The camera is set in the height of 2.45 meters to monitor the people overhead in order to reduce the overlap of pedestrians. The object segment and tracking method proposed in this paper show good result with the disparity map gained by the dual-camera. Dynamic promotion of threshold is used in the object segmentation. Feature matching is used to track the moving objects. The system can get the number of people accurate and timely. Experiment results show that our system has good performance under relatively complex circumstance.


2012 ◽  
Vol 424-425 ◽  
pp. 1070-1074
Author(s):  
Kai Peng ◽  
Xing Lin Zhou ◽  
Ji Guang Liu

Obstacle detection is a crucial issue for pilotless device guidance function and it has to be performed with high reliability to avoid any potential collision with the front object. The vision-based obstacle detection systems are regarded perfect for this purpose because they require little on all kind of condition. In this paper, an obstacle detection system using stereo vision sensors and structured light is developed. This system realizes rapid feature matching and high precision measurement distance with the help of structured light, avoiding the time-consuming of the initial corresponding pairs. After the initial detection, the system executes the tracking light strip algorithm for the obstacles. The proposed system can detect a front obstacle in vision field and obtain the size of obstacle. The proposed obstacle detection system is set up and its performance is verified experimentally


2020 ◽  
Vol 35 (8) ◽  
pp. 1566-1573
Author(s):  
Lan-Lan Tian ◽  
Ying-Zeng Gong ◽  
Wei Wei ◽  
Jin-Ting Kang ◽  
Hui-Min Yu ◽  
...  

This study presents a rapid and simple method of high precision Ba isotope measurement for barite using H2O extraction.


Sign in / Sign up

Export Citation Format

Share Document