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Sample Publications
arranged by Topics
Manifold
Models for Human Motion Analysis
Gait Analysis, Tracking and
Recognition
Facial
Expression Analysis and Recognition
Scene Modeling, SfM, and
Background Subtraction
Object
Recognition - Feature Selection
Pervasive
Computing - Multimedia
Kernel Density Estimation,
Efficient Computation using Fast Gauss Transform, and it's applications
Document
Image Analysis and Recognition
[Publications by
date - click here]
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Manifold Models for Human Motion Analysis:
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C-S. Lee and A.
Elgammal “Coupled Visual and Kinematics Manifold Models for
Human Motion Analysis” International
Journal on Computer Vision. Volume 87, Numbers 1-2, March 2010. |
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C-S. Lee and A.
Elgammal “Dynamic shape outlier detection for human
locomotion” Computer Vision
and Image Understanding Journal (CVIU). Volume 113, Issue 3, March 2009. |
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C-S. Lee and A.
Elgammal “Tracking People on a Torus” IEEE transactions
on Pattern Analysis and Machine Intelligence, March 2009 |
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C.-S. Lee and A. Elgammal "Modeling View and Posture Manifolds for Tracking" ICCV'07
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A. Elgammal and C.-S. Lee “Nonlinear Manifold Learning for Dynamic Shape and Dynamic Appearance” Computer Vision and Image Understanding (CVIU) special issue on generative model based vision. April 2007
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C.-S. Lee and A. Elgammal “Tracking
People on a Torus” technical report DCS -
TR611 |
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C.-S. Lee A. Elgammal “Body Pose Tracking From Uncalibrated Camera Using Supervised Manifold Learning” NIPS- Workshop on Evaluation of Articulated Human Motion and Pose Estimation. EHuM06. [PDF] – more details can be found in this technical report [TR-611]
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C.-S. Lee and A. Elgammal “Simultaneous
Inferring View and Body Pose Using Torus Manifolds” ICPR'06
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C.-S. Lee and A. Elgammal “Human
Motion Synthesis by Motion Manifold Learning and Motion Primitive
Segmentation” AMDO'06 - LNCS 4069
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C.-S. Lee and A. Elgammal “Homeomorphic Manifold Analysis: Learning Decomposable Generative Models for Human Motion Analysis” Workshop on Dynamic Vision (WDV05), with ICCV'05
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A. Elgammal, C.-S. Lee “Separating Style and Content on a Nonlinear Manifold” CVPR'04
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A. Elgammal, C.-S. Lee “Inferring 3D Body Pose from Silhouettes using Activity Manifold Learning” CVPR'04
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A. Elgammal “Nonlinear Generative Models for Dynamic Shape and Dynamic Appearance” 2nd International Workshop on Generative-Model based vision. GMBV 2004, with CVPR'04.
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Gait
Analysis, Tracking and Recognition: |
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C.-S. Lee and A. Elgammal “Carrying Object Detection Using Pose Preserving Dynamic Shape Model” AMDO'06 - LNCS 4069
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C.-S. Lee
and A. Elgammal “Gait
Tracking and Recognition using Person-Dependent Dynamic Shape Models”, FGR'06
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C.-S. Lee and A. Elgammal “Style Adaptive Bayesian Tracking Using Explicit Manifold Learning” BMVC'05
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C.-S. Lee and A. Elgammal “Towards Scalable View-Invariant Gait Recognition: Multilinear Analysis for Gait” Audio- and Video-based Biometric Person Authentication Conference AVBPA'05
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A. Elgammal, C.-S. Lee “Gait Style and Gait Content: Bilinear Model for Gait Recognition Using Gait Re-sampling” FGR'04
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Facial Expression Analysis and Recognition
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C.-S. Lee
and A. Elgammal “Nonlinear
Shape and Appearance Models for Facial Expressions” ICPR'06
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C.-S. Lee, A. Elgammal and Dimitris
Metaxas, “Synthesis
and Control of High Resolution Facial Expressions for Visual Interactions” ICME'06
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R. Isukapalli, A. Elgammal and R.
Greiner “Learning
to Identify Facial Expression During Detection using Markov Decision Process”, FGR'06 |
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C.-S. Lee and A. Elgammal “Facial Expression Analysis using Nonlinear Decomposable Generative Models” IEEE International Workshop on Analysis and Modeling of Faces and Gestures (AMFG05) with ICCV'05.
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R. Isukapalli, A. Elgammal, and R. Greiner “Learning a Dynamic Classification Method to Detect Faces and Identify Facial Expression” IEEE International Workshop on Analysis and Modeling of Faces and Gestures (AMFG05) with ICCV'05.
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Y. Wang, X. Huang, C.-S. Lee, S. Zhang, Z. Li, D. Samaras, D. Metaxas, A. Elgammal, P. Huang “High Resolution Acquisition, Learning and Transfer of Dynamic 3D Facial Expressions” Eurographics 2004
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M. Abdel-Moteleb and A. Elgammal “Face Detection in Complex Environment from Color Images”, ICIP'99
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T. Paraq, F.
Porikli and A. Elgammal “Boosting Adaptive Linear Weak
Classifiers for Online learning and Tracking” CVPR’08 |
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A. Elgammal “Learning to Track: Conceptual Manifold Map for Closed-form Tracking”, CVPR'05
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A. Elgammal, R. Duraiswami, and L. S. Davis “Probabilistic Tracking in Joint Feature-Spatial Spaces” CVPR'03
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A. Elgammal and L. S. Davis “Probabilistic Framework for Segmenting People Under Occlusion” ICCV'01
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Scene Modeling, SfM, and Background Subtraction:
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A. Elqursh and A.
Elgammal “Line-Based
Relative Pose Estimation” CVPR’11 |
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T. Parag, A. Elgammal and A. Mittal “A Framework for Feature Selection for Background Subtraction” CVPR'06
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S.-N. Lim, A. Elgammal, L. S. Davis "A Scalable Image-Based Multi-Camera Visual Surveillance System" IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS 2003)
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S.-N. Lim, A. Elgammal, L. S. Davis " Image-based Pan-Tilt Camera Control in a Multi-Camera Surveillance Environment" ICME'03
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A. Elgammal, R. Duraiswami, D. Harwood and L. S. Davis “Background and Foreground Modeling using Non-parametric Kernel Density Estimation for Visual Surveillance”, Proceedings of the IEEE, July 2002.
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A. Elgammal, D. Harwood, L. S. Davis “Non-parametric Model for Background Subtraction” ECCV'00
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Object
Recognition - Feature Selection: |
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T. Parag and A.
Elgammal “Supervised
Hypergraph Labeling” CVPR’11 |
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I. Chakraborty
and A. Elgammal "Object Localization by Propagating
Connectivity via Superfeatures” ICPR’10 |
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M. Torki and A.
Elgammal “One-Shot Multi-Set Non-rigid Feature-Spatial
Matching” CVPR’10 |
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M. Torki and A.
Elgammal “Putting Local Features on a Manifold” CVPR’10 |
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I. Chakraborty
and A. Elgammal "Contour segment matching by
integrating intra and inter shape cues of objects." BMVC’09 |
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T. Parag and
A. Elgammal “Unsupervised
Learning of Boosted Tree Classifier using Graph Cuts for Hand Pose
Recognition” BMVC'06, |
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Z. Zhao and A. Elgammal “A
statistically selected Part-Based Probabilistic Model for Object Recognition”, International Workshop on Intelligent
Computing in Pattern Analysis/Synthesis, IWICPAS 2006.
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R. Isukapalli, A. Elgammal and R.
Greiner “Learning
Policies for Efficiently Identifying Objects of Many Classes” ICPR'06 |
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I. Chakraborty and A. Elgammal “Combining
Low and High Level Features for Object Recognition” ICPR'06
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Z. Zhao, A. Vashist, A.
Elgammal, I. Muchnik and C. Kulikowski “Discriminative
Part Selection using Combinatorial and Statistical Models for Part-Based
Object Recognition” Beyond Patches Workshop - with
CVPR'06
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R. Isukapalli, A. Elgammal and R. Greiner “Learning Efficient Multiclass Object Detection Hierarchy” ECCV'06
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A. Elgammal “Human-centered Multimedia, Representations and Challenges” The 1st ACM international Workshop on Human-Centered Multimedia HCM '06 -- with ACM- Multimedia 2006. Invited Position Paper.
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N. Ravi, P.Shankar, A. Frankel, A. Elgammal and L. Iftode “Indoor Localization Using Camera Phones”, The 7th IEEE Workshop on Mobile Computing Systems and Applications, WMCSA 2006, April 2006.
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I. Awasthi and A. Elgammal “Learning Nonlinear Manifolds of Dynamic Textures”, International Conference on Computer Vision Theory and Applications VISAPP'06
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Gesture Analysis and Recognition:
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V. Shet, V. Shiv Naga Prasad, A. Elgammal, L. S. Davis, Y. Yacoob “Multi-Cue Exemplar-Based Nonparametric Model for Gesture Recognition”, 4th Indian Conference on Computer Vision, Graphics and Image Processing ICVGIP04 Recipient of Honorary Mention for Best Paper Award.
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A. Elgammal, V. Shet, Y. Yacoob, and L. S. Davis “Learning Dynamics for Exemplar-based Gesture Recognition” CVPR'03
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A. Elgammal, V. Shet, Y. Yacoob, L. S. Davis “Gesture Recognition using a Probabilistic Framework for Pose Matching” The Seventh International Conference on Control, Automation, Robotics and Vision, ICARCV'02
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Kernel Density Estimation, Efficient Computation using Fast Gauss Transform, and it's applications:
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A. Elgammal, R. Duraiswami and L. S. Davis “Efficient Kernel Density Estimation Using the Fast Gauss Transform for Computer Vision” IEEE Transactions on Pattern Analysis and Machine Intelligence. Dec 2003.
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A. Elgammal, R. Duraiswami, and L. S. Davis “Probabilistic Tracking in Joint Feature-Spatial Spaces” CVPR'03
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A. Elgammal, R. Duraiswami, D. Harwood and L. S. Davis “Background and Foreground Modeling using Non-parametric Kernel Density Estimation for Visual Surveillance”, Proceedings of the IEEE, July 2002.
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A. Elgammal, R. Duraiswami and L. S. Davis “Efficient Non-parametric Adaptive Color Modeling Using Fast Gauss Transform” CVPR'01
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Ph. D. dissertation, “Efficient Nonparametric Kernel Density Estimation for Real-time Computer Vision”, Department of computer science, University of Maryland, College Park, 2002.
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A. Elgammal, R. Duraiswami and L. S. Davis “Efficient Computation of Kernel Density Estimation using Fast Gauss Transform with Applications for Segmentation and Tracking” Second International Workshop on Statistical and Computational Theories of Vision, -- with ICCV'01
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Document Analysis and Recognition:
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A. Elgammal and M. A. Ismail “A Graph-Based Segmentation and Feature-extraction Framework for Arabic Text Recognition” Sixth International Conference on Document Analysis and Recognition (ICDAR'01)
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A. Elgammal and M. A. Ismail “Techniques for Language Identification for Hybrid Arabic-English Document Images” Sixth International Conference on Document Analysis and Recognition (ICDAR'01)
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M.Sc. thesis “Bilingual (Arabic/Latin) Document Image analysis with Font independent Arabic Character Recognition”, Faculty of Engineering, University of Alexandria. July 1996.
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