Vidal, Rene

Associate Professor
Center For Imaging Science

Clark Hall 302B
3400 N Charles St
(410) 516-7306
rvidal@jhu.edu

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About

Education
  • Ph.D. 2003, University of California at Berkeley
  • M.S. 2000, University of California at Berkeley
  • M.S. 1997, Catholic University of Chile
  • B.S. 1995, Catholic University of Chile
Experience
  • 2010: Associate Professor of Biomedical Engineering, Johns Hopkins University Secondary appointments: Computer Science, Electrical and Computer Engineering, Mechanical Engineering
  • 2012-2012: Visiting Professor, Computer Science Department, Catholic University, Santiago, Chile
  • 2012-2012: Visiting Professor, Math Department, Stanford University
  • 2012-2012: Visiting Professor, Computer Science Department, Ecole National Superieure, Paris, France
  • 2009-2010: Visiting Professor, Grupo de Visió per Computador i Robótica, Universitat de Girona, Girona, Spain
  • 2004-2010: Assistant Professor of Biomedical Engineering, Johns Hopkins University Secondary appointments: Computer Science, Electrical and Computer Engineering, Mechanical Engineering
  • 2008-2008: Visiting Professor, Centre de Recherche en Automatique, Université Henri Poincaré, Nancy, France
  • 2007-2007: Visiting Professor, Australian National University
  • 2006-2007: Visiting Professor, Heriot Watt University, UK
  • 2003-2004: Research Fellow, National ICT Australia
  • 2002-2002: Research Intern, RIACS NASA Ames, Moffet Field CA
  • 2001-2001: Research Intern, NEC Research Institute, Princeton NJ
  • 1997-1998: Research Engineer, DICTUC SA, Santiago, Chile
Research Areas
  • Biomedical Imaging
  • Processing of high angular resolution diffusion imaging (HARDI)
  • Registration and segmentation of diffusion MRI
  • Segmentation and fiber tracking of cardiac MRI
  • Interactive medical image segmentation
  • Computer Vision
  • Camera sensor networks
  • Recognition of human activities
  • Dynamic scene analysis: dynamic texture segmentation and recognition, motion/video segmentation
  • Structure from motion: omnidirectional vision, multiple view geometry, optimal motion estimation and 3-D reconstruction, camera self-calibration, non-rigid motion analysis
  • Dynamical Systems and Control
  • Observability, realization and identification of hybrid systems
  • Computation of controlled invariant sets using semi-definite programming
  • Decidability analysis of the controlled invariance problem for discrete-time hybrid systems
  • Machine Learning: Subspace clustering: generalized principal component analysis (GPCA)
  • Manifold learning and clustering: kernel GPCA, locally linear manifold clustering (LLMC)
  • Classification of dynamical systems: Binet-Cauchy kernels, Dynamic Boost
  • Robotics
  • Formation control of teams of non-holonomic robots
  • Coordination and control of multiple autonomous vehicles for pursuit-evasion games
  • Multiple view motion estimation and control for landing an unmanned aerial vehicle
  • Signal Processing
  • Consensus on manifolds and distributed optimization
  • Compressive sensing
Awards
  • 2012:  Best Paper Award for paper entitled "Intrinsic Consensus on SO(3) with Almost-Global Convergence - " IEEE Conference on Decision and Control - 2012
  • 2012:  Best Paper Award in Medical Robotics and Computer Assisted Interventions for paper entitled 'Surgical Gesture Classification from Video Data' - MICCAI 2012
  • 2012:  J. K. Aggarwal Prize "for outstanding contributions to generalized principal component analysis (GPCA) and subspace clustering in computer vision and pattern recognition - " 2012
  • 2011:  Best Paper Award Finalist for paper entitled 'Average Consensus on Riemannian Manifolds with Bounded Curvature' - 50th IEEE Conference on Decision and Control - 2011
  • 2009:  General Chairs' Recognition Award for Interactive Papers at the 48th IEEE Conference on Decision and Control
  • 2009:  General Chairs' Recognition Award for Interactive Papers at the 48th IEEE Conference on Decision and Control - 2009
  • 2009:  Outstanding Reviewer Award - IEEE Conference on Computer Vision and Pattern Recognition - 2009
  • 2009:  Outstanding Reviewer Award - IEEE International Conference on Computer Vision - 2009
  • 2009:  Outstanding Reviewer Award - IEEE International Conference on Computer Vision - 2009
  • 2009:  Sloan Research Fellowship - Alfred P. Sloan Foundation
  • 2009:  Young Investigator Award - Office of Naval Research
  • 2008:  Outstanding Reviewer Award - IEEE Conference on Computer Vision and Pattern Recognition - 2008
  • 2007:  Johns Hopkins nominee for Microsoft New Faculty Award
  • 2006:  VIBOT Fellowship in Vision and Robotics
  • 2005:  CAREER Award - National Science Foundation
  • 2004:  Best Paper Award Honorable Mention - European Conference on Computer Vision
  • 2004:  David J. Sakrison Memorial Prize - University of California at Berkeley
  • 2003:  Eli Jury Award - University of California at Berkeley
  • 2002:  SSRP Continuation Award - NASA Ames
  • 1998:  Marcos Orrego Puelma Award - Institute of Engineers of Chile
  • 1996:  Dow Chemical Company Prize to the best M.Eng. student - Catholic University of Chile
  • 1991:  Award to the best student of the School of Engineering - Catholic University of Chile
Presentations
  • Processing High Angular Resolution Diffusion Images of the Brain. Workshop on What Can Computer Vision Do for Neuroscience and Vice Versa? Janelia Farm Campus, Howard Hughes Medical Institute, October 2010
      , October 18, 2010
    1. Computer Vision: from Flying Robots to the Discovery of Brain Pathways, Department of Biomedical Engineering, Johns Hopkins University, October 2010
        , October 13, 2010
      1. Subspace Clustering. Shanks Workshop on "Machine learning and the Analysis of High Dimensional data sets”, Department of Mathematics, Vanderbilt University, September, 2010
          , September 10, 2010
        1. Multi-Subspace Learning and Clustering via Sparse Representation, Tutorial on Learning Multi-Subspaces in Computer Vision, IEEE Conference on Computer Vision and Pattern Recognition, San Francisco, CA, USA, June 2010
            , June 13, 2010
          1. 3D Motion Segmentation by Sparse Subspace Clustering, Mathematical Imaging Group, Lunds Universitet, Sweden, May 2010
              , May 11, 2010
            1. Interactive Medical Image Segmentation, Department of Biomedical Engineering, Johns Hopkins University, April 2010
                , April 11, 2010
              1. Multi-Manifold Learning. AAAI 2009 Fall Symposium on Manifold Learning and its Applications, Arlington, VA, November 2009, November 5, 2009
              2. Sparse Subspace Clustering. Research in Imaging Sciences Workshop, Minneapolis, MN, October 2009
                  , October 6, 2009
                1. Sparse Subspace Clustering. Forum on Geometric Aspects of Machine Learning and Visual Analytics: Recent Developments and Future Challenges, Atlantic City, NJ, October 2009
                    , October 4, 2009
                  1. 3D Motion Segmentation by Sparse Subspace Clustering. Visual Geometry Group, University of Oxford, UK, September 2009, September 20, 2009
                  2. Dynamic Texture Mosaicing, Segmentation, and Recognition. Computer Vision Center, Universidad Autonoma de Barcelona, Spain, May 2009.
                      , May 14, 2009
                    1. Interactive Medical Image Segmentation and Image Analysis Techniques for Diffusion MRI, I4M Seminar Series, Johns Hopkins University, March 2009.
                      , March 23, 2009
                    2. Manifold Clustering with Applications in Computer Vision and Diffusion Weighted Imaging. Department of Mathematics, University of Liege, March 2009
                      , March 13, 2009
                    3. Binet-Cauchy Kernels for the Recognition of Visual Dynamical Processes. Plenary Lecture at the Benelux Meeting in Systems and Control, Belgium. (Invited), March 5, 2009
                    4. Generalized Principal Component Analysis (GPCA) Department of Mathematics Seminar. University of Maryland at Baltimore County. 2008-11-00. (Invited), October 31, 2008
                    5. Binet-Cauchy Kernels on Dynamical Systems Department of Electrical and Computer Engineering and Computer Science, Seminar. niversity of Minnesota at Minneapolis. 2008-10-00. (Invited), September 30, 2008
                    6. Clustering Linear and Nonlinear Manifolds Workshop on Multi-Manifold Data Modeling and Applications. Minneapolis, MN. 2008-10-00. (Invited), September 30, 2008
                    7. Binet-Cauchy Kernels on Dynamical Systems Department of Electrical Engineering and Computer Science, Seminar. University of California at Berkeley. 2008-09-00. (Invited), August 31, 2008
                    8. Generalized Principal Component Analysis (GPCA) Seminar of the Centre de Mathématiques Appliquées. École Polytechnique, France. 2008-09-00. (Invited), August 31, 2008
                    9. Segmentation and Fiber Clustering in Diffusion Tensor Images Workshop on What Can Computer Vision Do for Neuroscience and Vice Versa?. Janelia Farm Research Campus, Howard Hughes Medical Institute. 2008-09-00. (Invited), August 31, 2008
                    10. Clustering Linear and Nonlinear Manifolds using Generalized Principal Components Analysis Minisymposium on Hybrid Linear and Nonlinear Modeling and their Applications. San Diego CA. 2008-07-00. (Invited), June 30, 2008
                    11. Segmentation and Fiber Clustering in Diffusion Tensor Images Department of Biomedical Engineering, Seminar Series. McGill University, Canada. 2008-05-00. (Invited), April 30, 2008
                    12. Dynamic Texture Mosaicing, Segmentation and Recognition Department of Electrical Engineering, Seminar Series. University of Delaware. 2008-04-00. (Invited), March 31, 2008
                    13. An Algebraic Geometric Approach to Hybrid System Identification. Workshop on Hybrid System Identification via Generalized Principal Component Analysis, Conference on Decision and Control. New Orleans, LA, USA. 2007-12-00., November 30, 2007
                    14. Generalized Principal Component Analysis (GPCA). Workshop on Optimization on Manifolds, Conference on Decision and Control. New Orleans, LA, USA. 2007-12-00. (Invited), November 30, 2007
                    15. Modeling, Segmentation and Registration of Dynamic Textures. Departmental Seminar, Research School of Information, Science and Engineering, Australian National University. Canberra, Australia. 2007-11-00. (Invited), October 31, 2007
                    16. Generalized Principal Component Analysis (GPCA). Departmental Seminar, Department of Mathematics, Vanderbilt University. Nashville, TN, USA. 2007-09-00. (Invited), August 31, 2007
                    17. Generalized Principal Component Analysis (GPCA). Workshop on Image Processing. Guanajuato, Mexico. 2007-08-00. (Invited), July 31, 2007
                    18. An Algebraic Geometric Approach to Hybrid System Identification. Workshop on Identification of Hybrid Systems, European Control Conference. Kos, Greece. 2007-07-00. (Invited), June 30, 2007
                    19. Generalized Principal Component Analysis (GPCA). Summer Workshop on Language and Speech Processing. Johns Hopkins Unversity. 2007-07-00. (Invited), June 30, 2007
                    20. Generalized Principal Component Analysis (GPCA). Tutorial at the IEEE Conference on Computer Vision and Pattern Recognition. Minneapolis, MN, USA. 2007-06-00. (Invited), May 31, 2007
                    21. Modeling and Segmentation of Dynamic Textures. Vision Seminar, Harriot Watt University. Edinburgh, UK. 2006-12-00. (Invited), November 30, 2006
                    22. Binet-Cauchy Kernels on Dynamical Systems EE Seminar. Princeton University. 2006-11-00. (Invited), October 31, 2006
                    23. Dynamic GPCA: Theory and Applications in Computer Vision, Biomedical Imaging, and Dynamical Systems ME Seminar. University of Delaware. 2006-11-00. (Invited), October 31, 2006
                    24. Modeling and Segmentation of Dynamic Textures ERC-CISST Seminar. Johns Hopkins University. 2006-11-00. (Invited), October 31, 2006
                    25. Binet-Cauchy Kernels on Dynamical Systems CIS Seminar. Johns Hopkins University. 2006-10-00., September 30, 2006
                    26. Segmentation of Dynamic Scenes and Textures BIRS Workshop on Mathematical Methods in Computer Vision. Banff, Canada. 2006-10-00. (Invited), September 30, 2006
                    27. Segmentation of Dynamic Scenes and Textures Plenary Lecture. Workshop on Computational Vision, Robotics, Neurocontrol and Medical Image Processing, Guadalajara, Mexico. 2006-06-00. (Invited), May 31, 2006
                    28. Segmentation of Dynamic Scenes and Textures Plenary Lecture. Workshop on Statistical Methods in Multi-Image and Video Processing (SMVP), Prague, Check Republic. 2006-05-00. (Invited), April 30, 2006
                    29. Algebraic Techniques for Segmentation and Registration with Applications to DTI and Interventional MRI. Clinical Neuroscience Seminar. Johns Hopkins University. 2006-04-00. (Invited), March 31, 2006
                    30. Generalized Principal Component Analysis (GPCA): an Algebraic Geometric Approach to Subspace Clustering CS Seminar. Stevens Institute of Technology. 2006-02-00. (Invited), January 31, 2006
                    31. An Algebraic Geometric Approach to Hybrid System Identification Workshop on Identification of Hybrid Systems, Conference on Decision and Control. Seville, Spain. 2005-12-00. (Invited), November 30, 2005
                    32. Segmenting a Beating Heart Using Generalized Principal Component Analysis IEEE Biomedical Engineering Chapter. Johns Hopkins University. 2005-12-00. (Invited), November 30, 2005
                    33. Generalized Principal Component Analysis (GPCA) Department of Applied Math and Statistics Seminar. Johns Hopkins University. 2005-11-00. (Invited), October 31, 2005
                    34. Toward Dynamic GPCA: Hybrid System Identification for the Analysis of Dynamic Scenes Sundaram Seshu Scholar Lecture. University of Illinois at Urbana Champaign. 2005-11-00. (Invited), October 31, 2005
                    35. Generalized Principal Component Analysis (GPCA) Department of Biomedical Engineering Seminar. Tsinghua University, Beijing, China. 2005-10-00. (Invited), September 30, 2005
                    36. Segmentation and Optical Flow for Multiple Moving Dynamic Textures Department of EECS Seminar. University of California at Berkeley. 2005-06-00. (Invited), May 31, 2005
                    37. Clustering Bilinear Surfaces Center for Imaging Science Seminar. Johns Hopkins University. 2005-04-00. (Invited), March 31, 2005
                    38. Reconstruction of Dynamic Scenes using GPCA Seminar. Siemens Corporate Research. 2005-04-00. (Invited), March 31, 2005
                    39. Generalized Principal Component Analysis (GPCA) Machine Learning Summer School. Canberra, Australia. 2005-01-00. (Invited), December 31, 2004
                    40. Generalized Principal Component Analysis (GPCA) Tutorial. Universidad Catolica de Chile. 2004-12-14. (Invited), December 14, 2004
                    41. Generalized Principal Component Analysis (GPCA) Vision Seminar. University of Maryland at College Park. 2004-11-00. (Invited), October 31, 2004
                    42. Segmentation of Dynamic Scenes via Generalized Principal Component Analysis Workshop on Mathematics and Image Analysis. Paris, France. 2004-09-06. (Invited), September 6, 2004
                    43. Motion Segmentation with Missing Data using PowerFactorization and GPCA IEEE Conference on Computer Vision and Pattern Recognition. Washington DC. 2004-07-00., June 30, 2004
                    44. A New GPCA Algorithm for Clustering Subspaces by Fitting, Differentiating and Dividing Polynomials. IEEE Conference on Computer Vision and Pattern Recognition. Washington DC. 2004-06-00., May 31, 2004
                    45. Reconstruction of Dynamic Scenes Workshop on Imaging Beyond the Pinhole Camera. Daghstul, Germany. 2004-06-00., May 31, 2004
                    46. A Unified Algebraic Approach to 2-D and 3-D Motion Segmentation. European Conference on Computer Vision. Prague, Czek Republic. 2004-05-00., April 30, 2004
                    47. Generalized Principal Component Analysis (GPCA) EECS Seminar. University of California at Berkeley. 2004-05-00. (Invited), April 30, 2004
                    48. Generalized Principal Component Analysis (GPCA) GRASP Seminar. University of Pennsylvania. 2004-03-00. (Invited), February 29, 2004
                    49. Generalized Principal Component Analysis (GPCA) Robotics Seminar. Carnegie Mellon University. 2004-02-00. (Invited), January 31, 2004
                    50. Generalized Principal Component Analysis (GPCA): an analytic approach to segmentation of static and dynamics scenes RSISE Seminar. Australian National University. 2003-06-00. (Invited), May 31, 2003
                    51. Generalized Principal Component Analysis (GPCA): an analytic approach to segmentation of static and dynamics scenes CS Seminar. University of California-Los Angeles. 2003-05-00. (Invited), April 30, 2003
                    52. Generalized Principal Component Analysis (GPCA): an analytic approach to segmentation of static and dynamics scenes EE Seminar. Princeton University. 2003-05-00. (Invited), April 30, 2003
                    53. Generalized Principal Component Analysis (GPCA): an analytic approach to segmentation of static and dynamics scenes CS Seminar. Pennsylvania State University. 2003-04-00. (Invited), March 31, 2003
                    54. Generalized Principal Component Analysis (GPCA): an analytic approach to segmentation of static and dynamics scenes CS Seminar. University of California-San Diego. 2003-04-00. (Invited), March 31, 2003
                    55. Generalized Principal Component Analysis (GPCA): an analytic approach to segmentation of static and dynamics scenes CIS Seminar. Johns Hopkins University. 2003-03-00. (Invited), February 28, 2003
                    56. Generalized Principal Component Analysis (GPCA): an analytic approach to segmentation of static and dynamics scenes CS Seminar. Northwestern University. 2003-02-00. (Invited), January 31, 2003
                    57. Generalized Principal Component Analysis (GPCA) and its application to segmentation of dynamics scenes CDS Seminar. Caliifornia Institute of Technology. 2002-11-00., October 31, 2002
                    58. Generalized Principal Component Analysis (GPCA) and its application to segmentation of dynamics scenes CS Seminar. University of California at Santa Barbara. 2002-11-00., October 31, 2002
                    59. Generalized Principal Component Analysis (GPCA) and its application to segmentation of dynamics scenes Vision Seminar. University of California at San Diego. 2002-11-00., October 31, 2002
                    60. Generalized Principal Component Analysis (GPCA) and its application to segmentation of dynamics scenes Vision Seminar. University of Southern California. 2002-11-00., October 31, 2002
                    61. Segmentation of Dynamic Scenes CS Seminar. University of Illinois at Urbana-Champaign. 2002-10-00. (Invited), September 30, 2002
                    62. Segmentation of Dynamic Scenes from Multibody Fundamental Matrix Vision Seminar. Stanford University. 2002-05-00., April 30, 2002
                    63. Structure from Motion and Pursuit-Evasion Games ME Seminar. Caliifornia Institute of Technology. 2001-11-00., October 31, 2001
                    64. Structure from Motion and Pursuit-Evasion Games Vision Seminar. University of Southern California. 2001-11-00., October 31, 2001
                    65. The Multiple View Matrix GRASP Seminar. University of Pennsylvania. 2001-08-00. (Invited), July 31, 2001
                    66. Multi-Agent Probabilistic Pursuit-Evasion Games with Unmanned Ground and Aerial Vehicles CSL Seminar. University of Illinois at Urbana-Champaign. 2001-04-00. (Invited), March 31, 2001

                    Publications

                    Journal Articles
                    • Gorospe, G., Younes, L., Tung, L., Vidal, R. (2013).  A metamorphosis distance for embryonic cardiac action potential interpolation and classification..  Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention.  16(Pt 1).  469-76.
                    • Ahmidi, N., Gao, Y., Béjar, B., Vedula, S., Khudanpur, S., Vidal, R., Hager, G. (2013).  String motif-based description of tool motion for detecting skill and gestures in robotic surgery..  Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention.  16(Pt 1).  26-33.
                    Books
                    • Vidal, R., Ma, Y., Sastry, S. (2012). Generalized Principal Component Analysis.
                    • Vidal, R., Heyden, A., Ma, Y. (2007). Dynamical Vision.
                    Book Chapters
                    • Tron, R., Terzis, A., Vidal, R. (2011). Distributed Image-Based 3-D Localization in Camera Sensor Networks. Distributed Video Sensor Networks. (pp.289-302).
                    • Singaraju, D., Grady, L., Sinop, A., Vidal, R. (2011). Continuous Valued MRFs for Image Segmentation. Advances in Markov Random Fields for Vision and Image Processing.
                    • Vidal, R. (2006). Segmentation of Dynamic Scenes Taken by a Central Panoramic Camera. Imaging Beyond the Pinhole Camera.
                    • Concha, J., Cipriano, A., Vidal, R. (2000). Stability Issues in Fuzzy Control.
                    Other Publications
                    • Vidal, R., Chiuso, A., Soatto, S., Sastry, S. (2003). Observability of Linear Hybrid Systems. Hybrid Systems: Computation and Control.
                    Conference Proceedings
                    • Cowan, N., Shakernia, O., Vidal, R., Sastry, S. (2003).  Vision-based Follow-the-Leader.  Proc IEEE RSJ Int Conf Intell Robots Syst.  2.  1796- 1801.
                    Patents
                    • Singaraju, D., Grady, L., Vidal, R. "System and Method for Image Segmentation using Continuous Valued MRFs with Normed Pairwise Distributions", 2010.
                    • Ravichandran, A., Vidal, R. "Registering Video Sequences Using Linear Dynamical Systems", 2010.
                    • Cetingul, H.E., Tek, H., Vidal, R. "A Multiscale Orientation Detector for Analyzing Local Topology of Tubular Structures", 2009.
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