Exactly capturing three dimensional (3D) motion i nf ormation of an object is an essential and important task in computer vision, and is also one of the most difficult problems. In this paper, a binocular vision s yst...Exactly capturing three dimensional (3D) motion i nf ormation of an object is an essential and important task in computer vision, and is also one of the most difficult problems. In this paper, a binocular vision s ystem and a method for determining 3D motion parameters of an object from binocu lar sequence images are introduced. The main steps include camera calibration, t he matching of motion and stereo images, 3D feature point correspondences and re solving the motion parameters. Finally, the experimental results of acquiring th e motion parameters of the objects with uniform velocity and acceleration in the straight line based on the real binocular sequence images by the mentioned meth od are presented.展开更多
Current research of binocular vision systems mainly need to resolve the camera’s intrinsic parameters before the reconstruction of three-dimensional(3D)objects.The classical Zhang’calibration is hardly to calculate ...Current research of binocular vision systems mainly need to resolve the camera’s intrinsic parameters before the reconstruction of three-dimensional(3D)objects.The classical Zhang’calibration is hardly to calculate all errors caused by perspective distortion and lens distortion.Also,the image-matching algorithm of the binocular vision system still needs to be improved to accelerate the reconstruction speed of welding pool surfaces.In this paper,a preset coordinate system was utilized for camera calibration instead of Zhang’calibration.The binocular vision system was modified to capture images of welding pool surfaces by suppressing the strong arc interference during gas metal arc welding.Combining and improving the algorithms of speeded up robust features,binary robust invariant scalable keypoints,and KAZE,the feature information of points(i.e.,RGB values,pixel coordinates)was extracted as the feature vector of the welding pool surface.Based on the characteristics of the welding images,a mismatch-elimination algorithm was developed to increase the accuracy of image-matching algorithms.The world coordinates of matching feature points were calculated to reconstruct the 3D shape of the welding pool surface.The effectiveness and accuracy of the reconstruction of welding pool surfaces were verified by experimental results.This research proposes the development of binocular vision algorithms that can reconstruct the surface of welding pools accurately to realize intelligent welding control systems in the future.展开更多
文摘Exactly capturing three dimensional (3D) motion i nf ormation of an object is an essential and important task in computer vision, and is also one of the most difficult problems. In this paper, a binocular vision s ystem and a method for determining 3D motion parameters of an object from binocu lar sequence images are introduced. The main steps include camera calibration, t he matching of motion and stereo images, 3D feature point correspondences and re solving the motion parameters. Finally, the experimental results of acquiring th e motion parameters of the objects with uniform velocity and acceleration in the straight line based on the real binocular sequence images by the mentioned meth od are presented.
基金Supported by National Natural Science Foundation of China(Grant No.51775313)Major Program of Shandong Province Natural Science Foundation(Grant No.ZR2018ZC1760)Young Scholars Program of Shandong University(Grant No.2017WLJH24).
文摘Current research of binocular vision systems mainly need to resolve the camera’s intrinsic parameters before the reconstruction of three-dimensional(3D)objects.The classical Zhang’calibration is hardly to calculate all errors caused by perspective distortion and lens distortion.Also,the image-matching algorithm of the binocular vision system still needs to be improved to accelerate the reconstruction speed of welding pool surfaces.In this paper,a preset coordinate system was utilized for camera calibration instead of Zhang’calibration.The binocular vision system was modified to capture images of welding pool surfaces by suppressing the strong arc interference during gas metal arc welding.Combining and improving the algorithms of speeded up robust features,binary robust invariant scalable keypoints,and KAZE,the feature information of points(i.e.,RGB values,pixel coordinates)was extracted as the feature vector of the welding pool surface.Based on the characteristics of the welding images,a mismatch-elimination algorithm was developed to increase the accuracy of image-matching algorithms.The world coordinates of matching feature points were calculated to reconstruct the 3D shape of the welding pool surface.The effectiveness and accuracy of the reconstruction of welding pool surfaces were verified by experimental results.This research proposes the development of binocular vision algorithms that can reconstruct the surface of welding pools accurately to realize intelligent welding control systems in the future.
