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
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
  • 2014:  IEEE Fellow
  • 2013:  Best Paper Award for paper entitled “Efficient Object Localization and Pose Estimation with 3D Wireframe Models," IEEE Workshop on 3D Representation and Recognition, 2013
  • 2013:  Outstanding Reviewer Award, IEEE Conference on Computer Vision and Pattern Recognition, 2013
  • 2013:  Best Paper Award for paper entitled “Joint Dictionary Learning for Categorization of Images using a Max-Margin Framework”, Pacific-Rim Symposium on Image and Video Technology, 2013
  • 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

Publications

Journal Articles
  • Lobel, H., Vidal, R., Soto, A. (2015).  Learning Shared, Discriminative, and Compact Representations for Visual Recognition.  IEEE Transactions on Pattern Analysis and Machine Intelligence.  (99).
  • Ravichandran, A., Favaro, P., Vidal, R. (2014).  A Unified Approach to Segmentation and Categorization of Dynamic Textures.  International Journal of Computer Vision.
  • Gorospe, G., Zhu, R., Millrod, M., Zambidis, E., Tung, L., Vidal, R. (2014).  Automated Grouping of Action Potentials of Human Embryonic Stem Cell-Derived Cardiomyocytes.  IEEE Transactions on Biomedical Engineering.  61(9).  2389–2395.
  • Tron, R., Vidal, R. (2014).  Distributed 3-D Localization of Camera Sensor Networks From 2-D Image Measurements.  IEEE Transactions on Automatic Control.  59(12).  3325–3340.
  • Rother, D., Mahendran, S., Vidal, R. (2014).  Hypothesize and Bound: A Computational Focus of Attention Mechanism for Simultaneous 3D Shape Reconstruction.  International Journal of Computer Vision.
  • Rother, D., Schütz, S., Vidal, R. (2014).  Hypothesize and Bound: A Computational Focus of Attention Mechanism for Simultaneous N-D Segmentation, Pose Estimation and Classification Using Shape Priors.  International Journal of Computer Vision.
  • Vidal, R., Favaro, P. (2014).  Low Rank Subspace Clustering (LRSC).  Pattern Recognition Letters.  43.  47–61.
  • Cetingul, H., Wright, M., Thompson, P., Vidal, R. (2014).  Segmentation of High Angular Resolution Diffusion MRI using Sparse Riemannian Manifold Clustering.  IEEE Transactions on Medical Imaging.  33(2).  301–317.
  • Ofli, F., Chaudhry, R., Kurillo, G., Vidal, R., Bajcsy, R. (2014).  Sequence of the Most Informative Joints (SMIJ): A New Representation for Human Skeletal Action Recognition.  Journal of Visual Communication and Image Representation.  25(1).  24–38.
  • Ravichandran, A., Chaudhry, R., Vidal, R. (2013).  Categorizing Dynamic Textures using a Bag of Dynamical Systems.  IEEE Transactions on Pattern Analysis and Machine Intelligence.  35(2).  342–353.
  • Chaudhry, R., Hager, G., Vidal, R. (2013).  Dynamic Template Tracking and Recognition.  International Journal of Computer Vision.  105(1).  19–48.
  • Afsari, B., Tron, R., Vidal, R. (2013).  On the Convergence of Gradient Descent for Locating the Riemmanian Center of Mass.  SIAM Journal on Control and Optimization.  51(3).  2230–2260.
  • Tron, R., Afsari, B., Vidal, R. (2013).  Riemannian Consensus for Manifolds with Bounded Curvature.  IEEE Transactions on Automatic Control.  58(4).  921–934.
  • Elhamifar, E., Vidal, R. (2013).  Sparse Subspace Clustering: Algorithm, Theory, and Applications.  IEEE Transactions on Pattern Analysis and Machine Intelligence.  35(11).  2765–2781.
  • Zappella, L., Béjar, B., Hager, G., Vidal, R. (2013).  Surgical Gesture Classification from Video and Kinematic data.  Medical Image Analysis.  17(7).  732–745.
  • 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.
  • Elhamifar, E., Vidal, R. (2012).  Block-Sparse Recovery via Convex Optimization.  IEEE Transactions on Signal Processing.  60(8).  4094–4107.
  • Singaraju, D., Vidal, R. (2011).  Estimation of Alpha Mattes for Multiple Layers.  IEEE Transactions on Pattern Analysis and Machine Intelligence.  33(7).  1295–1309.
  • Tron, R., Vidal, R. (2011).  Distributed Computer Vision Algorithms.  IEEE Signal Processing Magazine.  28(2).  32–45.
  • Lauer, F., Bloch, G., Vidal, R. (2011).  A Continuous Optimization Framework for Hybrid System Identification.  Automatica.  47(3).  608–613.
  • Vidal, R. (2011).  Subspace Clustering.  IEEE Signal Processing Magazine.  28(3).  52–68.
  • Goh, A., Lenglet, C., Thompson, P., Vidal, R. (2011).  A Nonparametric Riemannian Framework for Processing High Angular Resolution Diffusion Images and its Applications to ODF-based Morphometry.  Neuroimage.  47(3).  608–613.
  • Cetingül, H., Plank, G., Trayanova, N., Vidal, R. (2011).  Estimation of Local Orientations in Fibrous Structures with Applications to the Purkinje System.  IEEE Transactions on Biomedical Engineering.  58(6).  1762–1772.
  • Ravichandran, A., Vidal, R. (2011).  Video Registration Using Dynamic Textures.  IEEE Transactions on Pattern Analysis and Machine Intelligence.  33(1).  158–171.
  • Goh, A., Lenglet, C., Thompson, P., Vidal, R. (2010).  A Convex Framework for Estimation of Orientation Distribution Functions with Non-negativity Constraints and Spatial Regularity.  Medical Image Analysis.
  • Singaraju, D., Grady, L., Vidal, R. (2010).  Image Segmentation with Asymmetric Pairwise Penalties.  IEEE Transactions on Pattern Analysis and Machine Intelligence.
  • Goh, A., Vidal, R. (2010).  Locally Linear Manifold Clustering (LLMC).  Journal of Machine Learning Research.
  • Rao, S., Tron, R., Vidal, R., Ma, Y. (2010).  Motion Segmentation in the Presence of Outlying, Incomplete, or Corrupted Trajectories.  IEEE Transactions on Pattern Analysis and Machine Intelligence.  32(10).  1832–1845.
  • Vidal, R. (2008).  Recursive Identification of Switched ARX Systems.  Automatica.  44(9).  2274–2287.
  • Vidal, R., Tron, R., Hartley, R. (2008).  Multiframe Motion Segmentation with Missing Data Using PowerFactorization and GPCA.  International Journal of Computer Vision.  79(1).  85–105.
  • Vidal, R., Hartley, R. (2008).  Three-View Multibody Structure from Motion.  IEEE Transactions on Pattern Analysis and Machine Intelligence.  30(2).  214–227.
  • Vishwanathan, S., Smola, A., Vidal, R. (2007).  Binet-Cauchy Kernels on Dynamical Systems and its Application to the Analysis of Dynamic Scenes.  International Journal of Computer Vision.  73(1).  95–119.
  • Paoletti, S., Juloski, A., Ferrari-Trecate, G., Vidal, R. (2007).  Identification of Hybrid Systems: A Tutorial.  European Journal of Control.  73(1).  242–260.
  • Vidal, R., Ma, Y. (2006).  A Unified Algebraic Approach to 2-D and 3-D Motion Segmentation.  Journal of Mathematical Imaging and Vision.  25(3).  403–421.
  • Vidal, R., Ma, Y., Soatto, S., Sastry, S. (2006).  Two-View Multibody Structure from Motion.  International Journal of Computer Vision.  68(1).  7–25.
  • Vidal, R., Ma, Y., Sastry, S. (2005).  Generalized Principal Component Analysis (GPCA).  IEEE Transactions on Pattern Analysis and Machine Intelligence.  27(12).  1–15.
  • Ghoreyshi, A., Vidal, R., Mery, D. (2005).  Segmentation of Circular Casting Defects Using a Robust Algorithm.  Insight, Journal of the British Institute of Non-Destructive Testing.  47(10).  615–617.
  • Vidal, R., Shakernia, O., Sastry, S. (2004).  Following the Flock: Distributed Formation Control with Omnidirectional Vision-Based Motion Segmentation and Visual Servoing.  IEEE Robotics and Automation Magazine.  11(4).  14–20.
  • Ma, Y., Huang, K., Vidal, R., Kosecká, J., Sastry, S. (2004).  Rank Conditions on the Multiple View Matrix.  International Journal of Computer Vision.  59(2).  115–137.
  • Vidal, R., Shakernia, O., Kim, J., Shim, D., Sastry, S. (2002).  Probabilistic Pursuit-Evasion Games: Theory, Implementation and Experimental Evaluation.  IEEE Transactions on Robotics and Automation.  18(5).  662–669.
  • Concha, J., Cipriano, A., Vidal, R. (2001).  Design of fuzzy controllers based on stability analysis.  Fuzzy Sets and Systems, Special Issue on Formal Methods for Fuzzy Modeling and Control.  121(1).  25–38.
  • Ma, Y., Vidal, R., Hsu, S., Sastry, S. (2001).  Optimal Motion Estimation from Multiple Images by Normalized Epipolar Constraint.  Journal of Communications in Information and Systems.  1.  51–73.
  • Cipriano, A., Guarini, M., Vidal, R., Soto, A., Sepúlveda, C., Mery, D., Briseno, H. (1998).  A Real Time Visual Sensor for Supervision of Flotation Cells.  Minerals Engineering.  11(837).  489–499.
Books
  • Vidal, R., Ma, Y., Sastry, S. (2014).  Generalized Principal Component Analysis.  Springer Verlag.
  • (2007).  Dynamical Vision.  Springer Verlag.
Book Chapters
  • Afsari, B., Vidal, R. (2014).  Distances on Spaces of High-Dimensional Linear Stochastic Processes: A Survey.  Geometric Theory of Information.  Spinger-Verlag.  219–242.
  • Tron, R., Terzis, A., Vidal, R. (2011).  Distributed Image-Based 3-D Localization in Camera Sensor Networks.  Distributed Video Sensor Networks.  Springer.
  • 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.  MIT Press.
  • Daafouz, J., Benedetto, M., Blondel, V., Ferrari-Trecate, G., Hetel, L., Johansson, M., Juloski, A., Paoletti, S., Pola, G., Santis, E., Vidal, R. (2009).  Switched and Piecewise Affine Systems.  Handbook of Hybrid Systems Control, Theory, Tools, Application.  Cambridge University Press.  87–137.
  • Bako, L., Vidal, R. (2008).  Identification of MIMO Switched ARX Models.  Hybrid Systems: Computation and Control.  Spinger-Verlag.
  • Petreczky, M., Vidal, R. (2008).  Realization of Discrete-Time Semi-Algebraic Hybrid Systems.  Hybrid Systems: Computation and Control.  Springer Verlag.
  • Petreczky, M., Vidal, R. (2007).  Metrics and topology for nonlinear and hybrid systems.  Hybrid Systems: Computation and Control.  Springer Verlag.
  • Vidal, R. (2006).  Segmentation of Dynamic Scenes Taken by a Central Panoramic Camera.  Imaging Beyond the Pinhole Camera.  Springer Verlag.
  • Juloski, A., Heemels, W., Ferrari-Trecate, G., Vidal, R., Paoletti, S., Niessen, J. (2005).  Comparison of four procedures for the identification of hybrid systems.  Hybrid Systems: Computation and Control.  Springer-Verlag, Berlin.  3414.  354–369.
  • Ma, Y., Vidal, R. (2005).  Identification of Deterministic Switched ARX Systems via Identification of Algebraic Varieties.  Hybrid Systems: Computation and Control.  Springer Verlag.  449–465.
  • Vidal, R., Chiuso, A., Soatto, S., Sastry, S. (2003).  Observability of Linear Hybrid Systems.  Hybrid Systems: Computation and Control.  Springer Verlag.  526–539.
  • Vidal, R., Schaffert, S., Lygeros, J., Sastry, S. (2000).  Controlled Invariance of Discrete Time Systems.  Hybrid Systems: Computation and Control.  Springer Verlag.  437–451.
  • Concha, J., Cipriano, A., Vidal, R. (2000).  Design of Stable Fuzzy Controllers for Nonlinear Processes.  Stability Issues in Fuzzy Control.  Springer Verlag.
Other Publications
  • Singaraju, D., Grady, L., Vidal, R. (2010).  P-brush: A Generalized Algorithm for Interactive Segmentation.  US Patent 20100104186.
  • Ravichandran, A., Vidal, R. (2010).  System and Method for Registering Video Sequences.  US Patent 20100260439 A1.
  • Cetingul, H., Tek, H., Vidal, R. (2009).  A Multiscale Orientation Detector for Analyzing Local Topology of Tubular Structures.  US Patent 2009E16562US (Pending).
  • Vidal, R. (2003).  Generalized Principal Component Analysis (GPCA): an Algebraic Geometric Approach to Subspace Clustering and Motion Segmentation.  University of California, Berkeley.
  • Vidal, R., Soatto, S., Sastry, S. (2002).  A Factorization Method for 3D Multi-body motion estimation and segmentation.  UC Berkeley.  (UCB/ERL M02/3).
  • Vidal, R. (2000).  Controlled Invariance of Discrete Time Hybrid Systems.  University of California at Berkeley.
  • Vidal, R. (1997).  Control of a Robot Arm using Fuzzy Logic and Image Processing.  Catholic University of Chile.
Conference Proceedings
  • Tsakiris, M., Vidal, R. (2014).  Abstract Algebraic-Geometric Subspace Clustering.  Proceedings of Asilomar Conference on Signals, Systems and Computers.
  • Patel, V., Vidal, R. (2014).  Kernel Sparse Subspace Clustering.  International Conference on Image Processing.
  • Wolfers, S., Schwab, E., Vidal, R. (2014).  Nonnegative ODF Estimation Via Optimal Constraint Selection.  IEEE International Symposium on Biomedical Imaging.
  • Tao, L., Porikli, F., Vidal, R. (2014).  Sparse Dictionaries for Semantic Segmentation.  European Conference on Computer Vision.
  • Haeffele, B., Young, E., Vidal, R. (2014).  Structured Low-Rank Matrix Factorization: Optimality, Algorithm, and Applications to Image Processing.  International Conference on Machine Learning.
  • Yoruk, E., Vidal, R. (2013).  A 3D Wireframe Model for Efficient Object Localization and Pose Estimation.  ICCV Workshop on 3D Representation and Recognition.
  • Ofli, F., Chaudhry, R., Kurillo, G., Vidal, R., Bajcsy, R. (2013).  Berkeley MHAD: A Comprehensive Multimodal Human Action Database.  IEEE Workshop on Applications of Computer Vision.
  • Chaudhry, R., Ofli, F., Kurillo, G., Bajcsy, R., Vidal, R. (2013).  Bio-inspired Dynamic 3D Discriminative Skeletal Features for Human Action Recognition.  International Workshop on Human Activity Understanding from 3D Data.
  • Jain, A., Chatterjee, S., Vidal, R. (2013).  Coarse-to-fine Semantic Video Segmentation using Supervoxel Trees.  IEEE International Conference on Computer Vision.
  • Jimenez, N., Afsari, B., Vidal, R. (2013).  Fast Jacobi-type Algorithm for Computing Distances Between Linear Dynamical Systems.  European Control Conference.  3682–3687.
  • Afsari, B., Vidal, R. (2013).  Group Action Induced Distances on Spaces of High-Dimensional Linear Stochastic Processes.  Geometric Science of Information.  8085.  425–432.
  • Lobel, H., Soto, A., Vidal, R. (2013).  Hierarchical Joint Max-Margin Learning of Mid and Top Level Representations for Visual Recognition.  IEEE International Conference on Computer Vision.
  • Chaudhry, R., Vidal, R. (2013).  Initial-State Invariant Binet-Cauchy Kernels for the Comparison of Linear Dynamical Systems.  IEEE Conference on Decision and Control.
  • Lobel, H., Vidal, R., Mery, D., Soto, A. (2013).  Joint Dictionary and Classifier Learning for Categorization of Images Using a Max-margin Framework.  Pacific-Rim Symposium on Image and Video Technology.
  • Patel, V., Nguyen, H., Vidal, R. (2013).  Latent Space Sparse Subspace Clustering.  IEEE International Conference on Computer Vision.
  • Schwab, E., Cetingul, H., Afsari, B., Yassa, M., Vidal, R. (2013).  Rotation Invariant Features for HARDI.  Information Processing in Medical Imaging.
  • Tao, L., Zappella, L., Hager, G., Vidal, R. (2013).  Segmentation and Recognition of Surgical Gestures from Kinematic and Video Data.  Medical Image Computing and Computer Assisted Intervention.
  • Afsari, B., Vidal, R. (2013).  The Alignment Distance on Spaces of Linear Dynamical Systems.  IEEE Conference on Decision and Control.
  • Cetingul, H., Afsari, B., Vidal, R. (2012).  An Algebraic Solution to Rotation Recovery in HARDI from Correspondences of Orientation Distribution Functions.  IEEE International Symposium on Biomedical Imaging.
  • Schwab, E., Afsari, B., Vidal, R. (2012).  Estimation of Non-Negative ODFs using Eigenvalue Distribution of Spherical Functions.  Medical Image Computing and Computer Assisted Intervention.  7511(2).  322–330.
  • Elhamifar, E., Sapiro, G., Vidal, R. (2012).  Finding Exemplars from Pairwise Dissimilarities via Simultaneous Sparse Recovery.  Neural Information Processing and Systems.
  • Cetingul, H., Afsari, B., Wright, M., Thompson, P., Vidal, R. (2012).  Group action induced averaging for HARDI processing.  IEEE International Symposium on Biomedical Imaging.
  • Afsari, B., Chaudhry, R., Ravichandran, A., Vidal, R. (2012).  Group Action Induced Distances for Averaging and Clustering Linear Dynamical Systems with Applications to the Analysis of Dynamic Visual Scenes.  IEEE Conference on Computer Vision and Pattern Recognition.
  • Perrone, D., Ravichandran, A., Vidal, R., Favaro, P. (2012).  Image Priors for Image Deblurring with Uncertain Blur.  British Machine Vision Conference.
  • Tron, R., Afsari, B., Vidal, R. (2012).  Intrinsic Consensus on $SO(3)$ with Almost-Global Convergence.  IEEE Conference on Decision and Control.
  • Elhamifar, E., Sapiro, G., Vidal, R. (2012).  See All by Looking at A Few: Sparse Modeling for Finding Representative Objects.  IEEE Conference on Computer Vision and Pattern Recognition.
  • Ofli, F., Chaudhry, R., Kurillo, G., Vidal, R., Bajcsy, R. (2012).  Sequence of the Most Informative Joints (SMIJ): A New Representation for Human Skeletal Action Recognition.  International Workshop on Human Activity Understanding from 3D Data.
  • Tao, L., Elhamifar, E., Khudanpur, S., Hager, G., Vidal, R. (2012).  Sparse Hidden Markov Models for Surgical Gesture Classification and Skill Evaluation.  Information Processing in Computed Assisted Interventions.
  • Béjar, B., Zappella, L., Vidal, R. (2012).  Surgical Gesture Classification from Video Data.  Medical Image Computing and Computer Assisted Intervention.  34–41.
  • Jain, A., Zappella, L., McClure, P., Vidal, R. (2012).  Visual Dictionary Learning for Joint Object Categorization and Segmentation.  European Conference on Computer Vision.
  • Favaro, P., Vidal, R., Ravichandran, A. (2011).  A Closed Form Solution to Robust Subspace Estimation and Clustering.  IEEE Conference on Computer Vision and Pattern Recognition.
  • Rother, D., Vidal, R. (2011).  A Hypothesize-and-Bound Algorithm for Simultaneous Object Classification, Pose Estimation and 3D Reconstruction from a Single 2D Image.  ICCV Workshop on 3D Representation and Recognition.
  • Chen, Y., Tron, R., Terzis, A., Vidal, R. (2011).  Accelerated Corrective Consensus: Convergence to the Exact Average at a Faster Rate.  American Control Conference.
  • Tron, R., Afsari, B., Vidal, R. (2011).  Average Consensus on Riemannian Manifolds with Bounded Curvature.  IEEE Conference on Decision and Control.
  • Chen, Y., Tron, R., Terzis, A., Vidal, R. (2011).  Corrective Consensus with Asymmetric Wireless Links.  IEEE Conference on Decision and Control.
  • Tron, R., Vidal, R. (2011).  Distributed Computer Vision Algorithms Through Distributed Averaging.  IEEE Conference on Computer Vision and Pattern Recognition.
  • Elhamifar, E., Vidal, R. (2011).  Robust Classification using Structured Sparse Representation.  IEEE Conference on Computer Vision and Pattern Recognition.
  • Elhamifar, E., Vidal, R. (2011).  Sparse Manifold Clustering and Embedding.  Neural Information Processing and Systems.
  • Cetingül, H., Vidal, R. (2011).  Sparse Riemannian Manifold Clustering for HARDI Segmentation.  IEEE International Symposium on Biomedical Imaging.  839–842.
  • Elhamifar, E., Vidal, R. (2011).  Sparsity in Unions of Subspaces for Classification and Clustering of High-Dimensional Data.  Allerton Conference on Communication, Control, and Computing.
  • Singaraju, D., Vidal, R. (2011).  Using Global Bag of Features Models in Random Fields for Joint Categorization and Segmentation of Objects.  IEEE Conference on Computer Vision and Pattern Recognition.
  • Ravichandran, A., Favaro, P., Vidal, R. (2010).  A Unified Approach to Segmentation and Categorization of Dynamic Textures.  Asian Conference on Computer Vision.
  • Elhamifar, E., Vidal, R. (2010).  Clustering Disjoint Subspaces via Sparse Representation.  IEEE International Conference on Acoustics, Speech, and Signal Processing.
  • Li, J., Elhamifar, E., Wang, I., Vidal, R. (2010).  Consensus with Robustness to Outliers via Distributed Optimization.  IEEE Conference on Decision and Control.
  • Chen, Y., Tron, R., Terzis, A., Vidal, R. (2010).  Corrective Consensus: Converging to the Exact Average.  IEEE Conference on Decision and Control.
  • Lauer, F., Bloch, G., Vidal, R. (2010).  Nonlinear Hybrid System Identification with Kernel Models.  IEEE Conference on Decision and Control.
  • Goh, A., Lenglet, C., Thompson, P., Vidal, R. (2009).  A Nonparametric Riemannian Framework for Processing High Angular Resolution Diffusion Images (HARDI).  IEEE Conference on Computer Vision and Pattern Recognition.
  • Lauer, F., Vidal, R., Bloch, G. (2009).  A Product-of-Errors Framework for Linear Hybrid System Identification.  IFAC Symposium on System Identification.
  • Elhamifar, E., Vidal, R. (2009).  Distributed Calibration of Camera Sensor Networks.  International Conference on Distributed Smart Cameras.
  • Tron, R., Vidal, R. (2009).  Distributed Image-Based 3-D Localization in Camera Sensor Networks.  IEEE Conference on Decision and Control.
  • Goh, A., Lenglet, C., Thompson, P., Vidal, R. (2009).  Estimating Orientation Distribution Functions with Probability Density Constraints and Spatial Regularity.  Medical Image Computing and Computer Assisted Intervention.  5761.  877–885.
  • Cetingül, H., Plank, G., Trayanova, N., Vidal, R. (2009).  Estimation of Multimodal Orientation Distribution Functions from Cardiac MRI For Tracking Purkinje fibers through branchings.  IEEE International Symposium on Biomedical Imaging.  839–842.
  • Chaudhry, R., Ravichandran, A., Hager, G., Vidal, R. (2009).  Histograms of Oriented Optical Flow and Binet-Cauchy Kernels on Nonlinear Dynamical Systems for the Recognition of Human Actions.  IEEE Conference on Computer Vision and Pattern Recognition.
  • Bako, L., Mercere, G., Vidal, R., Lecoeuche, S. (2009).  Identification of Switched Linear State Space Models without Dwell Time.  IFAC Symposium on System Identification.
  • Cetingül, H., Vidal, R. (2009).  Intrinsic Mean Shift for Clustering on Stiefel and Grassmann Manifolds.  IEEE Conference on Computer Vision and Pattern Recognition.
  • Singaraju, D., Grady, L., Vidal, R. (2009).  P-Brush: Continuous Valued MRFs with Normed Pairwise Distributions for Image Segmentation.  IEEE Conference on Computer Vision and Pattern Recognition.
  • Elhamifar, E., Petreczky, M., Vidal, R. (2009).  Rank Tests for the Observability of Discrete-Time Jump Linear Systems with Inputs.  American Control Conference.
  • Elhamifar, E., Vidal, R. (2009).  Sparse Subspace Clustering.  IEEE Conference on Computer Vision and Pattern Recognition.
  • Cetingül, H., Plank, G., Trayanova, N., Vidal, R. (2009).  Stochastic Tractography in 3-D Images via Nonlinear Filtering and Spherical Clustering.  Workshop on Probabilistic Models for Medical Image Analysis.
  • Ravichandran, A., Chaudhry, R., Vidal, R. (2009).  View-Invariant Dynamic Texture Recognition using a Bag of Dynamical Systems.  IEEE Conference on Computer Vision and Pattern Recognition.
  • Goh, A., Vidal, R. (2008).  Clustering and Dimensionality Reduction on Riemannian Manifolds.  IEEE Conference on Computer Vision and Pattern Recognition.
  • Tron, R., Vidal, R. (2008).  Distributed Face Recognition via Consensus on SE(3).  Workshop on Omnidirectional Vision.
  • Tron, R., Vidal, R., Terzis, A. (2008).  Distributed pose averaging in camera networks via consensus on SE(3).  International Conference on Distributed Smart Cameras.
  • Singaraju, D., Vidal, R. (2008).  Interactive Image Matting for Multiple Layers.  IEEE Conference on Computer Vision and Pattern Recognition.
  • Singaraju, D., Grady, L., Vidal, R. (2008).  Interactive Image Segmentation Via Minimization of Quadratic Energies on Directed Graphs.  IEEE Conference on Computer Vision and Pattern Recognition.
  • Rao, S., Tron, R., Ma, Y., Vidal, R. (2008).  Motion Segmentation via Robust Subspace Separation in the Presence of Outlying, Incomplete, or Corrupted Trajectories.  IEEE Conference on Computer Vision and Pattern Recognition.
  • Cetingül, H., Vidal, R., Plank, G., Trayanova, N. (2008).  Nonlinear Filtering for Extracting Orientation and Tracing Tubular Structures in 2-D Medical Images.  IEEE International Symposium on Biomedical Imaging.  260–263.
  • Hartley, R., Vidal, R. (2008).  Perspective Nonrigid Shape and Motion Recovery.  European Conference on Computer Vision.
  • Goh, A., Vidal, R. (2008).  Segmenting Fiber Bundles in Diffusion Tensor Images.  European Conference on Computer Vision.  238–250.
  • Goh, A., Vidal, R. (2008).  Unsupervised Riemannian Clustering of Probability Density Functions.  European Conference on Machine Learning.
  • Ravichandran, A., Vidal, R. (2008).  Video Registration using Dynamic Textures.  European Conference on Computer Vision.
  • Tron, R., Vidal, R. (2007).  A Benchmark for the Comparison of 3-D Motion Segmentation Algorithms.  IEEE Conference on Computer Vision and Pattern Recognition.
  • Cetingül, H., Chaudhry, R., Vidal, R. (2007).  A System Theoretic Approach to Synthesis and Classification of Lip Articulation.  International Workshop on Dynamical Vision.
  • Vidal, R., Soatto, S., Chiuso, A. (2007).  Applications of Hybrid System Identification in Computer Vision.  European Control Conference.
  • Vidal, R., Favaro, P. (2007).  DynamicBoost: Boosting Time Series Generated by Dynamical Systems.  IEEE International Conference on Computer Vision.
  • Ghoreyshi, A., Vidal, R. (2007).  Epicardial Segmentation in Dynamic Cardiac MR Sequences Using Priors on Shape, Intensity, and Dynamics, in a Level Set Framework.  IEEE International Symposium on Biomedical Imaging.  860–863.
  • Vidal, R. (2007).  Identification of Spatial-Temporal Hybrid Systems.  IEEE Conference on Decision and Control.
  • Ravichandran, A., Vidal, R. (2007).  Mosaicing Nonrigid Dynamical Scenes.  International Workshop on Dynamic Vision.
  • Li, T., Kallem, V., Singaraju, D., Vidal, R. (2007).  Projective Factorization of Multiple Rigid-Body Motions.  IEEE Conference on Computer Vision and Pattern Recognition.
  • Petreczky, M., Vidal, R. (2007).  Realization Theory for Stochastic Jump-Markov Linear Systems.  IEEE Conference on Decision and Control.
  • Goh, A., Vidal, R. (2007).  Segmenting Motions of Different Types by Unsupervised Manifold Clustering.  IEEE Conference on Computer Vision and Pattern Recognition.
  • Singaraju, D., Vidal, R. (2006).  A Bottom up Algebraic Approach to Motion Segmentation.  Asian Conference on Computer Vision.  1.  286–296.
  • Goh, A., Vidal, R. (2006).  Algebraic Methods for Direct and Feature Based Registration of Diffusion Tensor Images.  European Conference on Computer Vision.  514–525.
  • Goh, A., Vidal, R. (2006).  An Algebraic Solution to Rigid Registration of Diffusion Tensor Images.  IEEE International Symposium on Biomedical Imaging.  642–645.
  • Lu, L., Vidal, R. (2006).  Combined Central and Subspace Clustering on Computer Vision Applications.  International Conference on Machine Learning.  593–600.
  • Singaraju, D., Vidal, R. (2006).  Direct Segmentation of Multiple Motion Models of Different Types.  International Workshop on Dynamical Vision.
  • Vidal, R., Abretske, D. (2006).  Nonrigid Shape and Motion from Multiple Perspective Views.  European Conference on Computer Vision.  205–218.
  • Vidal, R. (2006).  Online clustering of moving hyperplanes.  Neural Information Processing Systems, NIPS.
  • Ravichandran, A., Vidal, R., Halperin, H. (2006).  Segmenting a Beating Heart Using PolySegment and Spatial GPCA.  IEEE International Symposium on Biomedical Imaging.  634–637.
  • Ghoreyshi, A., Vidal, R. (2006).  Segmenting Dynamic Textures with Ising Descriptors, ARX Models and Level Sets.  International Workshop on Dynamic Vision.  127–141.
  • Vidal, R., Singaraju, D. (2005).  A Closed-Form Solution to Direct Motion Segmentation.  IEEE Conference on Computer Vision and Pattern Recognition.  II.  510–515.
  • Vidal, R. (2005).  Multi-Subspace Methods for Motion Segmentation from Affine, Perspective and Central Panoramic Cameras.  IEEE Conference on Robotics and Automation.  1753–1758.
  • Vidal, R., Ravichandran, A. (2005).  Optical Flow Estimation and Segmentation of Multiple Moving Dynamic Textures.  IEEE Conference on Computer Vision and Pattern Recognition.  II.  516–521.
  • Hashambhoy, Y., Vidal, R. (2005).  Recursive Identification of Switched ARX Models with Unknown Number of Models and Unknown Orders.  IEEE Conference on Decision and Control.  6115–6121.
  • Fan, X., Vidal, R. (2005).  The Space of Multibody Fundamental Matrices: Rank, Geometry and Projection.  International Workshop on Dynamical Vision.  1–17.
  • Vidal, R., Ma, Y., Piazzi, J. (2004).  A New GPCA Algorithm for Clustering Subspaces by Fitting, Differentiating and Dividing Polynomials.  IEEE Conference on Computer Vision and Pattern Recognition.  I.  510–517.
  • Vidal, R., Ma, Y. (2004).  A Unified Algebraic Approach to 2-D and 3-D Motion Segmentation.  European Conference on Computer Vision.  1–15.
  • Vidal, R. (2004).  Identification of PWARX Hybrid Models with Unknown and Possibly Different Orders.  American Control Conference.  547–552.
  • Huang, K., Ma, Y., Vidal, R. (2004).  Minimum Effective Dimension for Mixtures of Subspaces: A Robust GPCA Algorithm and its Applications.  IEEE Conference on Computer Vision and Pattern Recognition.  II.  631–638.
  • Vidal, R., Hartley, R. (2004).  Motion Segmentation with Missing Data by PowerFactorization and Generalized PCA.  IEEE Conference on Computer Vision and Pattern Recognition.  II.  310–316.
  • Vidal, R., Anderson, B. (2004).  Recursive Identification of Switched ARX Hybrid Models: Exponential Convergence and Persistence of Excitation.  IEEE Conference on Decision and Control.  32–37.
  • Hartley, R., Vidal, R. (2004).  The Multibody Trifocal Tensor: Motion Segmentation from 3 Perspective Views.  IEEE Conference on Computer Vision and Pattern Recognition.  I.  769–775.
  • Mery, D., Ochoa, F., Vidal, R. (2004).  Tracking of Points in a Calibrated and Noisy Image Sequence.  International Conference on Image Analysis and Recognition.
  • Vidal, R., Soatto, S., Ma, Y., Sastry, S. (2003).  An Algebraic Geometric Approach to the Identification of a Class of Linear Hybrid Systems.  IEEE Conference on Decision and Control.  167–172.
  • Vidal, R., Shakernia, O., Sastry, S. (2003).  Formation Control of Nonholonomic Mobile Robots with OmnidirectionalVisual Servoing and Motion Segmentation.  IEEE International Conference on Robotics and Automation.  1.  584–589.
  • Vidal, R., Ma, Y., Sastry, S. (2003).  Generalized Principal Component Analysis (GPCA).  IEEE Conference on Computer Vision and Pattern Recognition.  I.  621–628.
  • Shakernia, O., Vidal, R., Sastry, S. (2003).  Multi-Body Motion Estimation and Segmentation From Multiple Central Panoramic Views.  IEEE International Conference on Robotics and Automation.  1.  571–576.
  • Shakernia, O., Vidal, R., Sastry, S. (2003).  Omnidirectional vision-based egomotion estimation from backprojection flow.  Workshop on Omnidirectional Vision.
  • Vidal, R., Sastry, S. (2003).  Optimal Segmentation of Dynamic Scenes from Two Perspective Views.  IEEE Conference on Computer Vision and Pattern Recognition.  2.  281–286.
  • Shakernia, O., Vidal, R., Sastry, S. (2003).  Structure from small baseline motion with central panoramic cameras.  Workshop on Omnidirectional Vision.
  • 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.
  • Vidal, R., Soatto, S., Sastry, S. (2002).  A Factorization Method for Multibody Motion Estimation and Segmentation.  Fortieth Annual Allerton Conference on Communication, Control and Computing.  1625–1634.
  • Shakernia, O., Vidal, R., Sastry, S. (2002).  Infinitesimal Motion Estimation from Multiple Central Panoramic Views.  IEEE Workshop on Motion and Video Computing.  229–234.
  • Shakernia, O., Vidal, R., Sharp, C., Ma, Y., Sastry, S. (2002).  Multiple View Motion Estimation and Control for Landing an Unmanned Aerial Vehicle.  IEEE International Conference on Robotics and Automation.  2793–2798.
  • Vidal, R., Chiuso, A., Soatto, S. (2002).  Observability and Identifiability of Jump Linear Systems.  IEEE Conference on Decision and Control.  3614–3619.
  • Vidal, R., Shakernia, O., Sastry, S. (2002).  Omnidirectional Vision-Based Formation Control.  Fortieth Annual Allerton Conference on Communication, Control and Computing.  1625–1634.
  • Vidal, R., Sastry, S. (2002).  Segmentation of Dynamic Scenes from Image Intensities.  IEEE Workshop on Motion and Video Computing.  44–49.
  • Vidal, R., Soatto, S., Ma, Y., Sastry, S. (2002).  Segmentation of Dynamic Scenes from the Multibody Fundamental Matrix.  ECCV Workshop on Visual Modeling of Dynamic Scenes.
  • Vidal, R., Oliensis, J. (2002).  Structure from planar motions with small baselines.  European Conference on Computer Vision.  383–398.
  • Vidal, R., Sastry, S., Kim, J., Shakernia, O., Shim, D. (2002).  The Berkeley Aerial Robot Project (BEAR).  Workshop on Aerial Robotics, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).  1–10.
  • Vidal, R., Sastry, S. (2002).  Vision based detection of multiple autonomous vehicles for pursuit-evasion games.  IFAC World Congress on Automatic Control.
  • Kim, H., Vidal, R., Shim, D., Shakernia, O., Sastry, S. (2001).  A hierarchical approach to Probabilistic Pursuit-Evasion games with unmanned ground and aerial vehicles.  IEEE Conference on Decision and Control.  1243–1248.
  • Vidal, R., Schaffert, S., Shakernia, O., Lygeros, J., Sastry, S. (2001).  Decidable and Semi-decidable Controller Synthesis for Classes of Discrete Time Hybrid Systems.  IEEE Conference on Decision and Control.  1243–1278.
  • Vidal, R., Ma, Y., Hsu, S., Sastry, S. (2001).  Optimal Motion Estimation from the Multiview Normalized Epipolar Constraint.  IEEE International Conference on Computer Vision.  1.  34–41.
  • Vidal, R., Rashid, S., Sharp, C., Shakernia, O., Kim, H., Sastry, S. (2001).  Pursuit-Evasion games with unmanned ground and aerial vehicles.  IEEE International Conference on Robotics and Automation.  2948–2955.
  • Ma, Y., Vidal, R., Kosecká, J., Sastry, S. (2000).  Kruppa’s Equations Revisited: its Degeneracy, Renormalization and Relations to Chirality.  European Conference on Computer Vision.  2.  561–577.
  • Vidal, R., Cipriano, A. (1998).  A Robotic Classifier of Rocks: an Integration of Artificial Vision and Robotics.  IFAC Workshop on Algorithms and Architectures for Real-Time Control.  120–125.
  • Vidal, R., Cipriano, A. (1997).  System for Classifying Rocks by using Artificial Vision and a Robot Arm.  IEEE International Symposium on Industrial Electronics.  2.  729–734.
  • Cipriano, A., Ramos, M., Vidal, R., Mery, D. (1996).  Parallel Processing Systems and their Application to Economic Dispatch with Environmental Constraints.  Latin-American Congress on Automatic Control.  115–121.
  • Vidal, R., Cipriano, A. (1996).  The Scorbot ER VII Robot Arm: Description and Applications.  Chilean Congress on Automatic Control.  17–22.
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