The Experts below are selected from a list of 1911 Experts worldwide ranked by ideXlab platform
Zoran Popovic - One of the best experts on this subject based on the ideXlab platform.
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articulated body deformation from range scan data
International Conference on Computer Graphics and Interactive Techniques, 2002Co-Authors: Brett Allen, Brian Curless, Zoran PopovicAbstract:This paper presents an example-based method for calculating skeleton-driven body deformations. Our example data consists of range scans of a human body in a variety of poses. Using markers captured during range scanning, we construct a kinematic skeleton and identify the pose of each scan. We then construct a mutually consistent parameterization of all the scans using a posable subdivision surface template. The detail deformations are represented as displacements from this surface, and holes are filled smoothly within the displacement maps. Finally, we combine the range scans using k-Nearest Neighbor Interpolation in pose space. We demonstrate results for a human upper body with controllable pose, kinematics, and underlying surface shape.
Li Yong-liang - One of the best experts on this subject based on the ideXlab platform.
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Image Zoom Algorithm Based on the Spring Model
Computer Science, 2009Co-Authors: Li Yong-liangAbstract:To avoid the phenomenon of jaggy and blur edges during zoom image,after analyzing the Nearest Neighbor Interpolation model and the surface fitting model,an image zoom algorithm was proposed based on the spring model.The Interpolation formula was presented and the output results concerning on image zoom were simulated based on different algorithms.The result of experiment shows that the proposed method is able to maintain clear borders of source image and the algorithm is efficient in computation for making image zoom.
Brett Allen - One of the best experts on this subject based on the ideXlab platform.
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articulated body deformation from range scan data
International Conference on Computer Graphics and Interactive Techniques, 2002Co-Authors: Brett Allen, Brian Curless, Zoran PopovicAbstract:This paper presents an example-based method for calculating skeleton-driven body deformations. Our example data consists of range scans of a human body in a variety of poses. Using markers captured during range scanning, we construct a kinematic skeleton and identify the pose of each scan. We then construct a mutually consistent parameterization of all the scans using a posable subdivision surface template. The detail deformations are represented as displacements from this surface, and holes are filled smoothly within the displacement maps. Finally, we combine the range scans using k-Nearest Neighbor Interpolation in pose space. We demonstrate results for a human upper body with controllable pose, kinematics, and underlying surface shape.
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SIGGRAPH - Articulated body deformation from range scan data
Proceedings of the 29th annual conference on Computer graphics and interactive techniques - SIGGRAPH '02, 2002Co-Authors: Brett Allen, Brian Curless, Zoran PopovićAbstract:This paper presents an example-based method for calculating skeleton-driven body deformations. Our example data consists of range scans of a human body in a variety of poses. Using markers captured during range scanning, we construct a kinematic skeleton and identify the pose of each scan. We then construct a mutually consistent parameterization of all the scans using a posable subdivision surface template. The detail deformations are represented as displacements from this surface, and holes are filled smoothly within the displacement maps. Finally, we combine the range scans using k-Nearest Neighbor Interpolation in pose space. We demonstrate results for a human upper body with controllable pose, kinematics, and underlying surface shape.
Brian Curless - One of the best experts on this subject based on the ideXlab platform.
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articulated body deformation from range scan data
International Conference on Computer Graphics and Interactive Techniques, 2002Co-Authors: Brett Allen, Brian Curless, Zoran PopovicAbstract:This paper presents an example-based method for calculating skeleton-driven body deformations. Our example data consists of range scans of a human body in a variety of poses. Using markers captured during range scanning, we construct a kinematic skeleton and identify the pose of each scan. We then construct a mutually consistent parameterization of all the scans using a posable subdivision surface template. The detail deformations are represented as displacements from this surface, and holes are filled smoothly within the displacement maps. Finally, we combine the range scans using k-Nearest Neighbor Interpolation in pose space. We demonstrate results for a human upper body with controllable pose, kinematics, and underlying surface shape.
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SIGGRAPH - Articulated body deformation from range scan data
Proceedings of the 29th annual conference on Computer graphics and interactive techniques - SIGGRAPH '02, 2002Co-Authors: Brett Allen, Brian Curless, Zoran PopovićAbstract:This paper presents an example-based method for calculating skeleton-driven body deformations. Our example data consists of range scans of a human body in a variety of poses. Using markers captured during range scanning, we construct a kinematic skeleton and identify the pose of each scan. We then construct a mutually consistent parameterization of all the scans using a posable subdivision surface template. The detail deformations are represented as displacements from this surface, and holes are filled smoothly within the displacement maps. Finally, we combine the range scans using k-Nearest Neighbor Interpolation in pose space. We demonstrate results for a human upper body with controllable pose, kinematics, and underlying surface shape.
Eunjung Yang - One of the best experts on this subject based on the ideXlab platform.
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Performance of Sparse Recovery Algorithms for the Reconstruction of Radar Images From Incomplete RCS Data
IEEE Geoscience and Remote Sensing Letters, 2015Co-Authors: Byung-soo Kang, Eunjung YangAbstract:In this letter, we compare the performances of sparse recovery algorithms (SRAs) for the reconstruction of a 2-D inverse synthetic aperture radar (ISAR) image from incomplete radar-cross-section (RCS) data. The three methods considered for the SRA include the basis pursuit (BP), the BP denoising, and the orthogonal matching pursuit methods. The performances of the methods in terms of the reconstruction accuracy of the ISAR image are compared using the incomplete RCS data. In addition, traditional Interpolation methods such as Nearest-Neighbor Interpolation, linear Interpolation, and spline Interpolation are applied to the incomplete RCS data to reconstruct ISAR images, and their performances are compared to that of the SRAs.
