The Experts below are selected from a list of 360 Experts worldwide ranked by ideXlab platform
Ronald S Fearing - One of the best experts on this subject based on the ideXlab platform.
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determining the axis of a Surface of Revolution using tactile sensing
IEEE Transactions on Pattern Analysis and Machine Intelligence, 1993Co-Authors: M D Berkemeier, Ronald S FearingAbstract:Dextrous robot hands need to be able to determine the pose of objects to reliably grasp and manipulate them. The first contacts with an object can be used to provide an initial estimate of this information if the object is constrained to be of a particular class. The authors consider a simple example of exploiting class constraints: finding the axis of an unknown Surface of Revolution. Three tactile curvature measurements on a Surface of Revolution with twice-differentiable sweeping rule function are shown to be sufficient for determining the axis except for certain singular configurations. Position and orientation error uncertainties and experimental results are presented for a cylindrical tactile sensor. >
M D Berkemeier - One of the best experts on this subject based on the ideXlab platform.
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determining the axis of a Surface of Revolution using tactile sensing
IEEE Transactions on Pattern Analysis and Machine Intelligence, 1993Co-Authors: M D Berkemeier, Ronald S FearingAbstract:Dextrous robot hands need to be able to determine the pose of objects to reliably grasp and manipulate them. The first contacts with an object can be used to provide an initial estimate of this information if the object is constrained to be of a particular class. The authors consider a simple example of exploiting class constraints: finding the axis of an unknown Surface of Revolution. Three tactile curvature measurements on a Surface of Revolution with twice-differentiable sweeping rule function are shown to be sufficient for determining the axis except for certain singular configurations. Position and orientation error uncertainties and experimental results are presented for a cylindrical tactile sensor. >
Ligang Wang - One of the best experts on this subject based on the ideXlab platform.
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generalization of wolf effect of light on arbitrary two dimensional Surface of Revolution
Optics Express, 2018Co-Authors: Adeel Abbas, Ligang WangAbstract:Investigation of physics on two-dimensional curved Surface has significant meaning in study of general relativity, inasmuch as its realizability in experimental analogy and verification of faint gravitational effects in laboratory. Several phenomena about dynamics of particles and electromagnetic waves have been explored on curved Surfaces. Here we consider Wolf effect, a phenomenon of spectral shift due to the fluctuating nature of light fields, on an arbitrary Surface of Revolution (SOR). The general expression of the propagation of partially coherent beams propagating on arbitrary SOR is derived and the corresponding evolution of light spectrum is also obtained. We investigate the extra influence of Surface topology on spectral shift by defining two quantities, effective propagation distance and effective transverse distance, and compare them with longitudinal and transverse proper lengths. Spectral shift is accelerated when the defined effective quantities are greater than real proper lengths, and vice versa. We also employ some typical SORs, cylindrical Surfaces, conical Surfaces, SORs generated by power function and periodic peanut-shell shapes, as examples to provide concrete analyses. This work generalizes the research of Wolf effect to arbitrary SORs, and provides a universal method for analyzing properties of propagation compared with that in flat space for any SOR whose topology is known.
Chang Liu - One of the best experts on this subject based on the ideXlab platform.
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real time geometric fitting and pose estimation for Surface of Revolution
Pattern Recognition, 2019Co-Authors: Chang LiuAbstract:Abstract This paper presents a novel ellipse fitting method to simultaneously estimate the Euclidean pose and structure of a Surface of Revolution (SOR) by minimizing the geometric reprojection error of the visible cross sections in image space. This geometric error function and its Jacobian matrix are explicitly derived to enable Levenberg-Marquardt (LM) optimization. With the obtained pose and structure, the Euclidean shape of a SOR can be reconstructed by generating the ellipse tangency to the apparent contour of the SOR. Given the real size of several visible cross sections, this approach can be extended to perform a real-time 3D tracking of the SOR. Additionally, this technique can be also generalized to fitting for imaged parallel circles. Sufficient experiments validate the accuracy and the real-time performance of the proposed method.
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ellipse fitting for imaged cross sections of a Surface of Revolution
Pattern Recognition, 2015Co-Authors: Chang LiuAbstract:This paper addresses the problem of accurately fitting the elliptical projections of the cross sections of a Surface of Revolution (SOR) with the given intrinsic matrix of a camera. By the new approach proposed in this paper, the image points of the SOR cross sections are fitted under the two geometric constraints which are derived from the configuration characteristics of SOR. It is demonstrated by comparison with other previous methods that our method can fit the elliptical projections of SOR cross sections more accurately and robustly. In this paper, we also describe the applications of the algorithm in Euclidean reconstruction of SOR and pose estimation for SOR-shaped object, such as spacecraft. We accurately fit the imaged cross sections of a Surface of Revolution.The ellipses can be fitted under the circular point and orthogonality constraints.An effective optimization is elaborately designed.The method can serve for reconstruction and localization of a Surface of Revolution.
Paulo R S Mendonca - One of the best experts on this subject based on the ideXlab platform.
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epipolar geometry from profiles under circular motion
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2001Co-Authors: Paulo R S Mendonca, Kwanyee K Wong, R CippollaAbstract:Addresses the problem of motion estimation from profiles (apparent contours) of an object rotating on a turntable in front of a single camera. A practical and accurate technique for solving this problem from profiles alone is developed. It is precise enough to reconstruct the shape of the object. No correspondences between points or lines are necessary. Symmetry of the Surface of Revolution swept out by the rotating object is exploited to obtain the image of the rotation axis and the homography relating epipolar lines in two views robustly and elegantly. These, together with geometric constraints for images of rotating objects, are used to obtain first the image of the horizon, which is the projection of the plane that contains the camera centers, and then the epipoles, thus fully determining the epipolar geometry of the image sequence. The estimation of this geometry by this sequential approach avoids many of the problems found in other algorithms. The search for the epipoles, by far the most critical step, is carried out as a simple 1D optimization. Parameter initialization is trivial and completely automatic at all stages. After the estimation of the epipolar geometry, the Euclidean motion is recovered using the fixed intrinsic parameters of the camera obtained either from a calibration grid or from self-calibration techniques. Finally, the spinning object is reconstructed from its profiles using the motion estimated in the previous stage. Results from real data are presented, demonstrating the efficiency and usefulness of the proposed methods.
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camera pose estimation and reconstruction from image profiles under circular motion
European Conference on Computer Vision, 2000Co-Authors: Paulo R S Mendonca, Kwanyee K Wong, Roberto CipollaAbstract:This paper addresses the problem of motion estimation and reconstruction of 3D models from profiles of an object rotating on a turntable, obtained from a single camera. Its main contribution is the development of a practical and accurate technique for solving this problem from profiles alone, which is, for the first time, precise enough to allow the reconstruction of the object. No correspondence between points or lines are necessary, although the method proposed can be equally used when these features are available, without any further adaptation. Symmetry properties of the Surface of Revolution swept out by the rotating object are exploited to obtain the image of the rotation axis and the homography relating epipolar lines, in a robust and elegant way. These, together with geometric constraints for images of rotating objects, are then used to obtain first the image of the horizon, which is the projection of the plane that contains the camera centres, and then the epipoles, thus fully determining the epipolar geometry of the sequence of images. The estimation of the epipolar geometry by this sequential approach (image of rotation axis -- homography -- image of the horizon -- epipoles) avoids many of the problems usually found in other algorithms for motion recovery from profiles. In particular, the search for the epipoles, by far the most critical step, is carried out as a simple one-dimensional optimisation problem. The initialisation of the parameters is trivial and completely automatic for all stages of the algorithm. After the estimation of the epipolar geometry, the Euclidean motion is recovered using the fixed intrinsic parameters of the camera, obtained either from a calibration grid or from self-calibration techniques. Finally, the spinning object is reconstructed from its profiles, using the motion estimated in the previous stage. Results from real data are presented, demonstrating the efficiency and usefulness of the proposed methods.
