The Experts below are selected from a list of 1566 Experts worldwide ranked by ideXlab platform

M.n. Wernick - One of the best experts on this subject based on the ideXlab platform.

  • Accurate Mesh Representation of vector-valued (color) images
    Proceedings 2003 International Conference on Image Processing (Cat. No.03CH37429), 2003
    Co-Authors: J.g. Brankov, Y. Yang, M.n. Wernick
    Abstract:

    In this work we present a fast procedure for content-adaptive Mesh Representation of vector-valued (e.g., color) images. The goal is to obtain a single Mesh structure that accurately represents all the individual components of the image. The proposed method is justified by an error bound that is rigorously derived for such a Representation. It employs an error-diffusion type algorithm to place the Mesh nodes nonuniformly in the image domain according to the image content. Experimental results demonstrate that: (1) a compact and accurate Representation for color images can be achieved at low computational cost by the proposed algorithm; and (2) joint treatment of the different image components by the proposed algorithm can result in a more accurate Mesh Representation than a Mesh based on a single image component (such as intensity) alone.

  • content adaptive 3d Mesh modeling for Representation of volumetric images
    International Conference on Image Processing, 2002
    Co-Authors: J.g. Brankov, Y. Yang, M.n. Wernick
    Abstract:

    In this work we present a fast, content-adaptive approach for three-dimensional (3D) Mesh Representation of volumetric images. A rigorous error bound is derived for a 3D Mesh Representation of a volumetric image based on the theory of function interpolation. From this result, a computationally efficient algorithm is proposed for adaptive placement of Mesh nodes (hence Mesh elements) in the 3D image domain according to the image content. Experimental results demonstrate that a highly compact and accurate Representation of volumetric images can be achieved at low computational cost by the proposed algorithm.

  • ICIP-2002 Paper Proposal: CONTENT-ADAPTIVE 3D Mesh MODELING FOR Representation OF VOLUMETRIC IMAGES
    2002
    Co-Authors: J.g. Brankov, Y. Yang, M.n. Wernick
    Abstract:

    In this work we present a fast, content-adaptive approach for three-dimensional (3D) Mesh Representation of volumetric images. A rigorous error bound is derived for a 3D Mesh Representation of a volumetric image based on the theory of function interpolation. From this result, a computationally efficient algorithm is proposed for adaptive placement of Mesh nodes (hence Mesh elements) in the 3D image domain according to the image content. Experimental results demonstrate that a highly compact and accurate Representation of volumetric images can be achieved at low computational cost by the proposed algorithm.

  • ICIP-2002 Paper Proposal: CONTENT-ADAPTIVE Mesh MODELING FOR FULLY-3D TOMOGRAPHIC IMAGE RECONSTRUCTION 1
    2002
    Co-Authors: Y. Yang, J.g. Brankov, M.n. Wernick
    Abstract:

    In this paper we propose the use of a content-adaptive volumetric Mesh model for fully three-dimensional (3D) tomographic image reconstruction. In the proposed framework, the image to be reconstructed is first modeled by an efficient Mesh Representation. The image is then obtained through estimation of the nodal values from the measured data. The use of a Mesh Representation can alleviate the ill-posed nature of the reconstruction problem, thereby leading to improved quality in the reconstructed images. In addition, it reduces the data storage requirement, resulting in efficient algorithms. The proposed methods are tested using gated cardiacperfusion images. Initial results demonstrate that the proposed approach achieves superior performance when compared to several commonly used methods for image reconstruction, and produces results very rapidly.

  • ICIP (1) - Accurate Mesh Representation of vector-valued (color) images
    Proceedings 2003 International Conference on Image Processing (Cat. No.03CH37429), 1
    Co-Authors: J.g. Brankov, Y. Yang, M.n. Wernick
    Abstract:

    In this work we present a fast procedure for content-adaptive Mesh Representation of vector-valued (e.g., color) images. The goal is to obtain a single Mesh structure that accurately represents all the individual components of the image. The proposed method is justified by an error bound that is rigorously derived for such a Representation. It employs an error-diffusion type algorithm to place the Mesh nodes nonuniformly in the image domain according to the image content. Experimental results demonstrate that: (1) a compact and accurate Representation for color images can be achieved at low computational cost by the proposed algorithm; and (2) joint treatment of the different image components by the proposed algorithm can result in a more accurate Mesh Representation than a Mesh based on a single image component (such as intensity) alone.

Sang Uk Lee - One of the best experts on this subject based on the ideXlab platform.

  • robust semi regular Mesh Representation of 3d dynamic objects
    International Symposium on Circuits and Systems, 2003
    Co-Authors: Jeonghyu Yang, Changsu Kim, Sang Uk Lee
    Abstract:

    In this paper, we propose a robust scheme to represent 3D dynamic objects, which are given as a sequence of irregular Meshes. The sequence of irregular Meshes is converted into a sequence of semi-regular Meshes with time-invariant topology to facilitate the manipulation of 3D data. To this end, we sequentially perform the motion estimation of base Meshes, the shape transformation of subdivision points, and the selective intra-reMeshing. It is shown that a given sequence can be efficiently reMeshed without parameterization data by exploiting temporal correlation in the sequence. Simulation results demonstrate that the proposed algorithm reproduces the original geometry faithfully with a sequence of semi-regular Meshes.

  • semi regular Mesh Representation of 3d dynamic objects based on correspondence matching
    Multimedia Signal Processing, 2002
    Co-Authors: Jeonghyu Yang, Changsu Kim, Sang Uk Lee
    Abstract:

    In this paper, we propose a novel method to represent 3D dynamic objects, which are captured with a laser scanner in successive time instances. The objective is to convert an input Mesh sequence into a semi-regular Mesh sequence with time-invariant topology information, since it enables the easier manipulation of 3D data using many signal processing techniques. We achieve this objective by performing global motion estimation, local deformation estimation, and correspondence optimization subsequently. Simulation results show that the proposed algorithm reconstructs the original geometry faithfully. Furthermore, the resulting semi-regular Mesh sequences can be effectively compressed by adopting wavelet coding schemes.

  • ISCAS (2) - Robust semi-regular Mesh Representation of 3D dynamic objects
    Proceedings of the 2003 International Symposium on Circuits and Systems 2003. ISCAS '03., 1
    Co-Authors: Jeonghyu Yang, Changsu Kim, Sang Uk Lee
    Abstract:

    In this paper, we propose a robust scheme to represent 3D dynamic objects, which are given as a sequence of irregular Meshes. The sequence of irregular Meshes is converted into a sequence of semi-regular Meshes with time-invariant topology to facilitate the manipulation of 3D data. To this end, we sequentially perform the motion estimation of base Meshes, the shape transformation of subdivision points, and the selective intra-reMeshing. It is shown that a given sequence can be efficiently reMeshed without parameterization data by exploiting temporal correlation in the sequence. Simulation results demonstrate that the proposed algorithm reproduces the original geometry faithfully with a sequence of semi-regular Meshes.

Henry Markram - One of the best experts on this subject based on the ideXlab platform.

  • A Neuron Membrane Mesh Representation for Visualization of Electrophysiological Simulations
    IEEE Transactions on Visualization and Computer Graphics, 2012
    Co-Authors: Sébastien Lasserre, Felix Schuermann, Pedro De Miguel Anasagasti, Georges Abou Jaoude, Juan Hernando, Sean Hill, Henry Markram
    Abstract:

    We present a process to automatically generate three-dimensional Mesh Representations of the complex, arborized cell membrane surface of cortical neurons (the principal information processing cells of the brain) from nonuniform morphological measurements. Starting from manually sampled morphological points (3D points and diameters) from neurons in a brain slice preparation, we construct a polygonal Mesh Representation that realistically represents the continuous membrane surface, closely matching the original experimental data. A mapping between the original morphological points and the newly generated Mesh enables simulations of electrophysiolgical activity to be visualized on this new membrane Representation. We compare the new Mesh Representation with the state of the art and present a series of use cases and applications of this technique to visualize simulations of single neurons and networks of multiple neurons.

J.g. Brankov - One of the best experts on this subject based on the ideXlab platform.

  • Accurate Mesh Representation of vector-valued (color) images
    Proceedings 2003 International Conference on Image Processing (Cat. No.03CH37429), 2003
    Co-Authors: J.g. Brankov, Y. Yang, M.n. Wernick
    Abstract:

    In this work we present a fast procedure for content-adaptive Mesh Representation of vector-valued (e.g., color) images. The goal is to obtain a single Mesh structure that accurately represents all the individual components of the image. The proposed method is justified by an error bound that is rigorously derived for such a Representation. It employs an error-diffusion type algorithm to place the Mesh nodes nonuniformly in the image domain according to the image content. Experimental results demonstrate that: (1) a compact and accurate Representation for color images can be achieved at low computational cost by the proposed algorithm; and (2) joint treatment of the different image components by the proposed algorithm can result in a more accurate Mesh Representation than a Mesh based on a single image component (such as intensity) alone.

  • content adaptive 3d Mesh modeling for Representation of volumetric images
    International Conference on Image Processing, 2002
    Co-Authors: J.g. Brankov, Y. Yang, M.n. Wernick
    Abstract:

    In this work we present a fast, content-adaptive approach for three-dimensional (3D) Mesh Representation of volumetric images. A rigorous error bound is derived for a 3D Mesh Representation of a volumetric image based on the theory of function interpolation. From this result, a computationally efficient algorithm is proposed for adaptive placement of Mesh nodes (hence Mesh elements) in the 3D image domain according to the image content. Experimental results demonstrate that a highly compact and accurate Representation of volumetric images can be achieved at low computational cost by the proposed algorithm.

  • ICIP-2002 Paper Proposal: CONTENT-ADAPTIVE 3D Mesh MODELING FOR Representation OF VOLUMETRIC IMAGES
    2002
    Co-Authors: J.g. Brankov, Y. Yang, M.n. Wernick
    Abstract:

    In this work we present a fast, content-adaptive approach for three-dimensional (3D) Mesh Representation of volumetric images. A rigorous error bound is derived for a 3D Mesh Representation of a volumetric image based on the theory of function interpolation. From this result, a computationally efficient algorithm is proposed for adaptive placement of Mesh nodes (hence Mesh elements) in the 3D image domain according to the image content. Experimental results demonstrate that a highly compact and accurate Representation of volumetric images can be achieved at low computational cost by the proposed algorithm.

  • ICIP-2002 Paper Proposal: CONTENT-ADAPTIVE Mesh MODELING FOR FULLY-3D TOMOGRAPHIC IMAGE RECONSTRUCTION 1
    2002
    Co-Authors: Y. Yang, J.g. Brankov, M.n. Wernick
    Abstract:

    In this paper we propose the use of a content-adaptive volumetric Mesh model for fully three-dimensional (3D) tomographic image reconstruction. In the proposed framework, the image to be reconstructed is first modeled by an efficient Mesh Representation. The image is then obtained through estimation of the nodal values from the measured data. The use of a Mesh Representation can alleviate the ill-posed nature of the reconstruction problem, thereby leading to improved quality in the reconstructed images. In addition, it reduces the data storage requirement, resulting in efficient algorithms. The proposed methods are tested using gated cardiacperfusion images. Initial results demonstrate that the proposed approach achieves superior performance when compared to several commonly used methods for image reconstruction, and produces results very rapidly.

  • ICIP (1) - Accurate Mesh Representation of vector-valued (color) images
    Proceedings 2003 International Conference on Image Processing (Cat. No.03CH37429), 1
    Co-Authors: J.g. Brankov, Y. Yang, M.n. Wernick
    Abstract:

    In this work we present a fast procedure for content-adaptive Mesh Representation of vector-valued (e.g., color) images. The goal is to obtain a single Mesh structure that accurately represents all the individual components of the image. The proposed method is justified by an error bound that is rigorously derived for such a Representation. It employs an error-diffusion type algorithm to place the Mesh nodes nonuniformly in the image domain according to the image content. Experimental results demonstrate that: (1) a compact and accurate Representation for color images can be achieved at low computational cost by the proposed algorithm; and (2) joint treatment of the different image components by the proposed algorithm can result in a more accurate Mesh Representation than a Mesh based on a single image component (such as intensity) alone.

Kenichi Matsuyanagi - One of the best experts on this subject based on the ideXlab platform.