The Experts below are selected from a list of 1797 Experts worldwide ranked by ideXlab platform
Laurent Kneip - One of the best experts on this subject based on the ideXlab platform.
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IROS - Articulated Multi-Perspective Cameras and Their Application to Truck Motion Estimation
2019 IEEE RSJ International Conference on Intelligent Robots and Systems (IROS), 2019Co-Authors: Xin Peng, Laurent KneipAbstract:While monocular and stereo Camera based motion estimation has reached a level of maturity that enables industrial use, the community keeps exploring novel multi-sensor solutions to meet the high robustness and accuracy requirements of certain applications such as autonomous vehicles. The present paper focuses on motion estimation with multi-Perspective Camera systems. In particular, we look into the intricate case in which the Cameras are distributed over an articulated body, a scenario that occurs in truck motion estimation where additional Cameras are installed on the trailer. The resulting articulated multi-Perspective Camera is analyzed in theory and practice, and we show that— by taking the non-holonomic constraints of the vehicle into account— a single point correspondence measured from the trailer is sufficient to render the additional unknown parameters given by the internal joint configuration before and after a relative displacement fully observable. optimizing over all parameters enhances the accuracy of the motion estimation of the entire system with respect to using the Cameras on each rigid part alone. Results are confirmed on both simulated and real data.
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Articulated Multi-Perspective Cameras and Their Application to Truck Motion Estimation
2019 IEEE RSJ International Conference on Intelligent Robots and Systems (IROS), 2019Co-Authors: Xin Peng, Laurent KneipAbstract:While monocular and stereo Camera based motion estimation has reached a level of maturity that enables industrial use, the community keeps exploring novel multi-sensor solutions to meet the high robustness and accuracy requirements of certain applications such as autonomous vehicles. The present paper focuses on motion estimation with multi-Perspective Camera systems. In particular, we look into the intricate case in which the Cameras are distributed over an articulated body, a scenario that occurs in truck motion estimation where additional Cameras are installed on the trailer. The resulting articulated multi-Perspective Camera is analyzed in theory and practice, and we show that- by taking the non-holonomic constraints of the vehicle into account- a single point correspondence measured from the trailer is sufficient to render the additional unknown parameters given by the internal joint configuration before and after a relative displacement fully observable. optimizing over all parameters enhances the accuracy of the motion estimation of the entire system with respect to using the Cameras on each rigid part alone. Results are confirmed on both simulated and real data.
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ICVS - On Scale Initialization in Non-overlapping Multi-Perspective Visual Odometry
Lecture Notes in Computer Science, 2017Co-Authors: Yifu Wang, Laurent KneipAbstract:Multi-Perspective Camera systems pointing into all directions represent an increasingly interesting solution for visual localization and mapping. They combine the benefits of omni-directional measurements with a sufficient baseline for producing measurements in metric scale. However, the observability of metric scale suffers from degenerate cases if the Cameras do not share any overlap in their field of view. This problem is of particular importance in many relevant practical applications, and it impacts most heavily on the difficulty of bootstrapping the structure-from-motion process. The present paper introduces a complete real-time pipeline for visual odometry with non-overlapping, multi-Perspective Camera systems, and in particular presents a solution to the scale initialization problem. We evaluate our method on both simulated and real data, thus proving robust initialization capacity as well as best-in-class performance regarding the overall motion estimation accuracy.
Bart Lamiroy - One of the best experts on this subject based on the ideXlab platform.
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Object Pose: The Link between Weak Perspective, ParaPerspective, and Full Perspective
International Journal of Computer Vision, 1997Co-Authors: Radu Horaud, Fadi Dornaika, Bart LamiroyAbstract:Recently, DeMenthon and Davis (1992, 1995) proposed a method for determining the pose of a 3-D object with respect to a Camera from 3-D to 2-D point correspondences. The method consists of iteratively improving the pose computed with a weak Perspective Camera model to converge, at the limit, to a pose estimation computed with a Perspective Camera model. In this paper we give an algebraic derivation of DeMenthon and Davis' method and we show that it belongs to a larger class of methods where the Perspective Camera model is approximated either at zero order (weak Perspective) or first order (paraPerspective). We describe in detail an iterative paraPerspective pose computation method for both non coplanar and coplanar object points. We analyse the convergence of these methods and we conclude that the iterative paraPerspective method (proposed in this paper) has better convergence properties than the iterative weak Perspective method. We introduce a simple way of taking into account the orthogonality constraint associated with the rotation matrix. We analyse the sensitivity to Camera calibration errors and we define the optimal experimental setup with respect to imprecise Camera calibration. We compare the results obtained with this method and with a non-linear optimization method.
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Object pose: links between paraPerspective and Perspective
Proceedings of IEEE International Conference on Computer Vision, 1995Co-Authors: R. Horaud, S. Christy, Fadi Dornaika, Bart LamiroyAbstract:D.F. Dementhon and L.S. Davis (1995) proposed a method for determining the pose of a 3D object with respect to a Camera from 3D to 2D point correspondences. The method consists of iteratively improving the pose computed with a weak Perspective Camera model to converge at the limit, to a pose estimation computed with a Perspective Camera model. We show that the method of Dementhon and Davis can be extended to paraPerspective. The iterative paraPerspective pose algorithm that we describe in detail has interesting properties both in terms of speed and rate of convergence. Moreover, we introduce a simple way of taking into account the orthogonality constraint associated with the rotation matrix and we define the optimal experimental setup to be used in the presence of Camera calibration errors.
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ICCV - Object pose: links between paraPerspective and Perspective
Proceedings of IEEE International Conference on Computer Vision, 1995Co-Authors: Radu Horaud, S. Christy, Fadi Dornaika, Bart LamiroyAbstract:D.F. Dementhon and L.S. Davis (1995) proposed a method for determining the pose of a 3D object with respect to a Camera from 3D to 2D point correspondences. The method consists of iteratively improving the pose computed with a weak Perspective Camera model to converge at the limit, to a pose estimation computed with a Perspective Camera model. We show that the method of Dementhon and Davis can be extended to paraPerspective. The iterative paraPerspective pose algorithm that we describe in detail has interesting properties both in terms of speed and rate of convergence. Moreover, we introduce a simple way of taking into account the orthogonality constraint associated with the rotation matrix and we define the optimal experimental setup to be used in the presence of Camera calibration errors. >
P. Martinet - One of the best experts on this subject based on the ideXlab platform.
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Omnidirectional Visual-Servo of a Gough–Stewart Platform
IEEE Transactions on Robotics, 2009Co-Authors: O. Tahri, Y. Mezouar, N. Andreff, P. MartinetAbstract:This paper deals with the visual control of the Gough-Stewart platform using a central catadioptric Camera observing the platform's legs. This allows a large field of view to be obtained and avoids the occlusion problems observed when a classical Perspective Camera is used. An automatic and simple method to detect the projections of the leg in the image is also proposed. The control scheme presented here is shown to encompass the classical Perspective Camera case, as well as catadioptric ones. Finally, experimental results comparing two kinds of visual features (leg directions and leg edges) are described.
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IROS - Omnidirectional visual-servo of a Gough-Stewart platform
2007 IEEE RSJ International Conference on Intelligent Robots and Systems, 2007Co-Authors: Omar Tahri, N. Andreff, Youcef Mezouar, P. MartinetAbstract:This work deals with the control by vision of the Gough-Stewart platform. For that, a central catadioptric Camera is used to observe the platform legs. This allows to obtain a large field of view, and then avoids the occlusion problems observed when a classical Perspective Camera is used. The leg projections onto the catadioptric plane are used to determine their orientation in the Camera frame. Finally, the computed orientations will be used in a visual servoing scheme of the platform effector.
S. Gasparini - One of the best experts on this subject based on the ideXlab platform.
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"How many planar viewing surfaces are there in noncentral catadioptric Cameras?" Towards singe-image localization of space lines
2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06), 2006Co-Authors: V. Caglioti, S. GaspariniAbstract:In-door environments often contain several straight line segments. The 3D reconstruction of such environments can thus reduce to the localization of lines in the 3D space. Multi-view reconstruction requires the solution of the correspondence problem. The use of a single image to localize space lines is attractive, since the correspondence problem can be avoided. However, using a Perspective Camera (or a central one), a line can not be localized, since its viewing surface is planar, and hence it can contain infinite lines other than the correct one. In this paper we study the number of planar viewing surfaces for a general class of catadioptric Cameras, constituted by an axial symmetric mirror and a Perspective Camera placed at generic relative position. We show that, under broad conditions, there is only a discrete set of planar viewing surfaces for the considered class of Cameras. This result establishes a qualitative difference with respect to axial-symmetric Cameras (e.g., catadioptric Cameras constituted by an axial-symmetric mirror plus a Perspective Camera, whose viewpoint is constrained to be on the mirror axis), where an infinite set of planar viewing surfaces exists. Then, some conditions are derived for the localization of lines in the 3D space from single images. Preliminary experiments are also reported.
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CVPR (1) - "How many planar viewing surfaces are there in noncentral catadioptric Cameras?" Towards singe-image localization of space lines
2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1 (CVPR'06), 2006Co-Authors: V. Caglioti, S. GaspariniAbstract:In-door environments often contain several straight line segments. The 3D reconstruction of such environments can thus reduce to the localization of lines in the 3D space. Multi-view reconstruction requires the solution of the correspondence problem. The use of a single image to localize space lines is attractive, since the correspondence problem can be avoided. However, using a Perspective Camera (or a central one), a line can not be localized, since its viewing surface is planar, and hence it can contain infinite lines other than the correct one. In this paper we study the number of planar viewing surfaces for a general class of catadioptric Cameras, constituted by an axial symmetric mirror and a Perspective Camera placed at generic relative position. We show that, under broad conditions, there is only a discrete set of planar viewing surfaces for the considered class of Cameras. This result establishes a qualitative difference with respect to axial-symmetric Cameras (e.g., catadioptric Cameras constituted by an axial-symmetric mirror plus a Perspective Camera, whose viewpoint is constrained to be on the mirror axis), where an infinite set of planar viewing surfaces exists. Then, some conditions are derived for the localization of lines in the 3D space from single images. Preliminary experiments are also reported.
Xin Peng - One of the best experts on this subject based on the ideXlab platform.
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IROS - Articulated Multi-Perspective Cameras and Their Application to Truck Motion Estimation
2019 IEEE RSJ International Conference on Intelligent Robots and Systems (IROS), 2019Co-Authors: Xin Peng, Laurent KneipAbstract:While monocular and stereo Camera based motion estimation has reached a level of maturity that enables industrial use, the community keeps exploring novel multi-sensor solutions to meet the high robustness and accuracy requirements of certain applications such as autonomous vehicles. The present paper focuses on motion estimation with multi-Perspective Camera systems. In particular, we look into the intricate case in which the Cameras are distributed over an articulated body, a scenario that occurs in truck motion estimation where additional Cameras are installed on the trailer. The resulting articulated multi-Perspective Camera is analyzed in theory and practice, and we show that— by taking the non-holonomic constraints of the vehicle into account— a single point correspondence measured from the trailer is sufficient to render the additional unknown parameters given by the internal joint configuration before and after a relative displacement fully observable. optimizing over all parameters enhances the accuracy of the motion estimation of the entire system with respect to using the Cameras on each rigid part alone. Results are confirmed on both simulated and real data.
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Articulated Multi-Perspective Cameras and Their Application to Truck Motion Estimation
2019 IEEE RSJ International Conference on Intelligent Robots and Systems (IROS), 2019Co-Authors: Xin Peng, Laurent KneipAbstract:While monocular and stereo Camera based motion estimation has reached a level of maturity that enables industrial use, the community keeps exploring novel multi-sensor solutions to meet the high robustness and accuracy requirements of certain applications such as autonomous vehicles. The present paper focuses on motion estimation with multi-Perspective Camera systems. In particular, we look into the intricate case in which the Cameras are distributed over an articulated body, a scenario that occurs in truck motion estimation where additional Cameras are installed on the trailer. The resulting articulated multi-Perspective Camera is analyzed in theory and practice, and we show that- by taking the non-holonomic constraints of the vehicle into account- a single point correspondence measured from the trailer is sufficient to render the additional unknown parameters given by the internal joint configuration before and after a relative displacement fully observable. optimizing over all parameters enhances the accuracy of the motion estimation of the entire system with respect to using the Cameras on each rigid part alone. Results are confirmed on both simulated and real data.