\n
Yizhe Zhu, Jianwen Xie, Zhiqiang Tang, Xi Peng , Ahmed Elgammal<\/p>\n
\u201cSemantic-Guided Multi-Attention Localization for Zero-Shot Learning,\u201d<\/p>\n
NeurIPS 2019.<\/p>\n
<\/p>\n
Yizhe Zhu, Jianwen Xie , Bingchen Liu, Ahmed Elgammal<\/p>\n
\u201cLearning Feature-to-Feature Translator by Alternating Back-Propagation for Zero-Shot Learning,\u201d<\/p>\n
ICCV 2019<\/p>\n
<\/p>\n
J. Zhang, K. Shih, A. Elgammal, A. Tao, B. Catanzaro.<\/p>\n
\u201cGraphical Contrastive Losses for Scene Graph Generation.\u201d<\/p>\n
CVPR 2019<\/p>\n
<\/p>\n
S. Geng*, J. Zhang*, H. Zhang, A. Elgammal, D. N. Metaxas,<\/p>\n
2nd Place Solution to the GQA Challenge 2019<\/strong>.<\/p>\nCVPR Workshops 2019<\/p>\n
<\/p>\n
J. Zhang, Y. Kalantidis, M. Rohrbach, M. Paluri, A. Elgammal, M. Elhoseiny.<\/p>\n
\u201cLarge-Scale Visual Relationship Understanding\u201d<\/p>\n
AAAI 2019<\/p>\n
<\/p>\n
A. Elgammal, M. Mazzone<\/p>\n
\u201cArt, Creativity and the Potential of Artificial Intelligence\u201d,<\/p>\n
Arts, 2019, 8, 26. Special issue on The Machine as Artist (for the 21st Century.<\/p>\n
<\/p>\n
D. Kim, A. Elgammal, M. Mazzone<\/p>\n
\u201cComputational Analysis of Content in Fine Art Paintings\u201d<\/p>\n
Proceedings of the 10th International Conference on Computational Creativity<\/p>\n
ICCC 2019<\/p>\n
<\/p>\n<\/div>\n<\/div>\n<\/div>\n
<\/div>\n<\/div>\n<\/div>\n<\/div>\n
\n
\n
\n
\n
\n
2018<\/strong><\/p>\n <\/p>\n<\/div>\n<\/div>\n
\n
\n
\n
[M. Khayatkhoei, M. Singh, A. Elgammal<\/p>\n
\u201cDisconnected Manifold Learning for Generative Adversarial Networks\u201d<\/p>\n
NeruIPS 2018<\/p>\n
<\/p>\n
Zhang, K. Shih, A. Tao, B. Catanzaro, A. Elgammal.<\/p>\n
\u201cAn Interpretable Model for Scene Graph Generation\u201d.<\/p>\n
NeurIPS Workshops, 2018<\/p>\n
<\/p>\n
Zhang, K. Shih, A. Tao, B. Catanzaro, A. Elgammal.<\/p>\n
\u201cIntroduction to the 1st Place Winning Model of Open Images Relationship Detection Challenge<\/strong>\u201d.<\/p>\nECCV Workshops, 2018<\/p>\n
<\/p>\n
Y. Zhu, M. Elhoseiny, B. Liu, X. Peng, and A. Elgammal,<\/p>\n
\u201cA generative adversarial approach for zero-shot learning from noisy texts\u201d<\/p>\n
CVPR 2018<\/p>\n
<\/p>\n
A. Elgammal, B. Liu, D. Kim, M. Elhoseiny, M. Mazzone<\/p>\n
“The Shape of Art History in the Eyes of the Machine”<\/p>\n
AAAI 2018<\/p>\n
<\/p>\n
A. Elgammal, Y. Kang, M. Den Leeuv<\/p>\n
“Picasso, Matisse, or a Fake? Automated Analysis of Drawings at the Stroke Level for Attribution and Authentication”<\/p>\n
AAAI 2018<\/p>\n
<\/p>\n
D. Kim, B. Liu, A. Elgammal, M. Mazzone<\/p>\n
“Finding Principal Semantics of Style in Art\u201d<\/p>\n
The 12th IEEE International Conference on Semantic Computing (ICSC),<\/p>\n
<\/p>\n
<\/p>\n<\/div>\n<\/div>\n<\/div>\n
<\/div>\n<\/div>\n<\/div>\n<\/div>\n
\n
\n
\n
\n
\n
2017<\/strong><\/p>\n <\/p>\n<\/div>\n<\/div>\n
\n
\n
\n
M. Elhoseiny, S. Cohen, W. Chang, B. Price, and A. Elgammal,
\n\u201cTowards Richer and Scalable Understanding of Facts in Images\u201d
\nAAAI 2017<\/p>\n
<\/p>\n
M. Elhoseiny, A. Elgammal, and B. Saleh,
\n\u201cWrite a Classifier: Predicting Visual Classifiers from Unstructured Text Descriptions\u201d,
\nTPAMI – December 2017<\/p>\n
<\/p>\n
S. Huang, A. Elgammal, and D. Yang,
\n\u201cOn the Effect of Hyperedge Weights on Hypergraph Learning\u201d
\nImage and Vision Computing – 2017<\/p>\n
<\/p>\n
Y. Zhu and A. Elgammal \u201c<\/i><\/p>\n
“A Multilayer-Based Framework for Online Background Subtraction With Freely Moving Cameras\u201d<\/p>\n
ICCV 2017<\/p>\n
<\/p>\n
J. Zhang, M. Elhoseiny, W. Chang, S. Cohen, A. Elgammal,<\/p>\n
\u201cRelationship Proposal Networks\u201d<\/p>\n
CVPR 2017<\/p>\n
<\/p>\n
M. Elhoseiny, Y. Zhu, H. Zhang, A. Elgammal,<\/p>\n
\u201cLink the head to the \u2018peak\u2019: Zero Shot Learning from Noisy Text descriptions at Part Precision\u201d<\/p>\n
CVPR 2017<\/p>\n
<\/p>\n
A. Elgammal, B. Liu, M. Elhoseiny and M. Mazzone<\/p>\n
\u201cCAN: Creative Adversarial Networks\u201d,<\/p>\n
Proceedings of the International Conference on Computational Creativity<\/p>\n
ICCC 2017<\/p>\n
<\/p>\n
M. Elhoseiny, S. Cohen, W. Chang, B. Price, and A. Elgammal,<\/p>\n
\u201cTowards Richer and Scalable Understanding of Facts in Images\u201d,<\/p>\n
AAAI 2017<\/p>\n
<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n
<\/div>\n
\n
\n
\n
\n
\n
2016<\/strong><\/p>\n <\/p>\n<\/div>\n<\/div>\n
\n
\n
\n
B. Saleh, A. Elgammal, and J. Feldman,
\n\u201cThe Role of Typicality in Object Classification: Improving The Generalization Capacity of Convolutional Neural Networks\u201d
\nIJCAI 2016<\/p>\n
<\/p>\n
M. Elhoseiny, T. El-Gaaly, A. Bakry, and A. Elgammal,
\n\u201cA Comparative Analysis and Study of Multiview Convolutional Neural Network Models for Joint Object Categorization and Pose Estimation\u201d,
\nICML 2016<\/p>\n
<\/p>\n
H. Zhang, T. Xu, M. Elhoseiny, X. Huang, S. Zhang, A. Elgammal, D. Metaxas,
\n\u201cSPDA-CNN: Unifying Semantic Part Detection and Abstraction for Fine-grained Recognition\u201d
\nCVPR 2016<\/p>\n
<\/p>\n
A. Bakry, M. Elhoseiny, T. El-Gaaly, and A. Elgammal,
\n\u201cDigging Deep into the layers of CNNs: In Search of How CNNs Achieve View Invariance\u201d
\nICLR 2016<\/p>\n
<\/p>\n
B. Saleh, A. Elgammal, J. Feldman and A. Farhadi
\n\u201cToward a Taxonomy and Computational Models of Abnormalities in Images\u201d,
\nAAAI 2016
\nRecipient of the Outstanding Student Paper Award<\/em><\/strong><\/p>\n <\/p>\n
M. Ehoseiny and J. Liu and H. Cheng and H. Sawhney and A. Elgammal
\n\u201cZero Shot Event Detection by Multimodal Distributional Semantic Embedding of Videos\u201d,
\nAAAI 2016<\/p>\n
<\/p>\n
S. Huang, Y. Yu, D. Yang, A. Elgammal and D. Yang,
\n\u201cCollaborative Graph Embedding: A Simple Way to Generally Enhance Subspace Learning Algorithms\u201d,
\nIEEE Transactions on Circuits and Systems for Video Technology (TCSVT),
\nOctober 2016<\/p>\n
<\/p>\n
P. Vepakomma and A. Elgammal
\n\u201cA fast algorithm for manifold learning by posing it as a symmetric diagonally dominant linear system\u201d,
\nApplied and Computational Harmonic Analysis Journal
\nMarch 2016<\/p>\n
<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n
<\/div>\n
\n
\n
\n
\n
\n
2015<\/strong><\/p>\n <\/p>\n<\/div>\n<\/div>\n
\n
\n
\n
A.Elgammal and B. Saleh
\n\u201cQuantifying Creativity in Art Networks\u201d,
\nthe 6th International Conference on Computational Creativity (ICCC\u201915)
\nM. Elhoseiny and A. Elgammal
\n\u201cGeneralized Twin Gaussian Processes using Sharma-Mittal Divergence\u201d
\nMachine Learning Journal
\n\u2013 Also will be presented in ECML PPKDD\u201915<\/p>\n
<\/p>\n
M. Elhoseiny, S. Huang, and A Elgammal
\n\u201cWeather Classification with Deep Convolution Neural Networks\u201d,
\nICIP 15<\/p>\n
<\/p>\n
S. Huang, M. Elhoseiny, A. Elgammal, D. Yang
\n\u201cLearning Hypergraph-regularized Attribute Predictors\u201d
\nCVPR 15<\/p>\n
<\/p>\n
T. El-Gaaly, V. Froyen, A. Elgammal, J. Feldman, M. Singh
\n\u201cA Bayesian Approach to Perceptual 3D Object-Part Decomposition Using Skeleton-Based Representations\u201d
\nAAAI 15<\/p>\n
<\/p>\n
H. Zhang, T. El-Gaaly, Z. Jiang, A. Elgammal
\n\u201cFactorization on View-Object Manifold for Joint Object Recognition and Pose Estimation\u201d
\nCVIU 2015<\/p>\n
<\/p>\n
X. Peng, J. Huang; Q. Hu; S. Zhang; A. Elgammal, and D. Metaxas
\n\u201cFrom Circle to 3-Shpere: Robust Head Pose Estimation by Instance Parameterization\u201d
\nCVIU 2015<\/p>\n
<\/p>\n
M. Elhoseiny and A. Elgammal
\n\u201cText to Multi-level MindMaps: A Novel Method for Hierarchical Visual Abstraction of Natural Language Text\u201d
\nMultimedia Tools and Applications Journal, Springer, April 2015<\/p>\n
<\/p>\n
A. Elgammal
\n\u201cHomeomorphic Manifold Analysis (HMA): Untangling Complex Manifolds\u201d
\nAdvances in Imaging and Electron Physics<\/p>\n
<\/p>\n<\/div>\n
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\n
\n
\n
\n
2014<\/strong><\/p>\n <\/p>\n<\/div>\n<\/div>\n
\n
\n
\n
S. Huang, A. Elgammal, M. Elhoseiny, D. Yang, X. Zhang
\n\u201cImproving Non-Negative Matrix Factorization via Ranking Its Bases\u201d,
\nICIP 2014<\/p>\n
<\/p>\n
E. L. Spratt and A. Elgammal
\n\u201cComputational Beauty: Aesthetic Judgment at the Intersection of Art and Science\u201d
\nWhen Vision Meets Art (VisArt) Workshop 2014<\/p>\n
<\/p>\n
B. Saleh, K. Abe, R. Arora, A. Elgammal
\n\u201cToward Automated Discovery of Artistic Influence\u201d
\nMultimedia Tools and Applications \u2013 Springer \u2013 2014<\/p>\n
<\/p>\n
T. Senlet, T. El-Gaaly, A. Elgammal,
\n\u201cHierarchical Semantic Hashing: Visual Localization from Buildings on Maps\u201d
\nICPR 2014<\/p>\n
<\/p>\n
T. El-Gaaly, M. Torki, A. Elgammal
\n\u201cSpatial-Visual Label Propagation for Local Feature Classification\u201d
\nICPR 2014.<\/p>\n
<\/p>\n
A. Bakry and A. Elgammal
\n\u201cUntangling Object-View Manifold for Multiview Recognition and Pose Estimation\u201d
\nECCV 2014<\/p>\n
<\/p>\n
C. Tonde and A. Elgammal
\n\u201cSimultaneous Twin Kernel Learning using Polynomial Transformations for Structured Prediction\u201d
\nCVPR 2014<\/p>\n
<\/p>\n
B. Saleh, K. Abe and A. Elgammal
\n\u201cKnowledge Discovery of Artistic Influences: A Metric Learning Approach\u201d
\nICCC 2014<\/p>\n
<\/p>\n<\/div>\n<\/div>\n<\/div>\n
<\/p>\n
<\/div>\n<\/div>\n<\/div>\n<\/div>\n
\n
\n
\n
\n
\n
2013<\/strong><\/p>\n <\/p>\n<\/div>\n<\/div>\n
\n
\n
\n
A. Elqursh and A. Elgammal
\nOnline Motion Segmentation using Dynamic Label Propagation\u201d
\nICCV 2013<\/p>\n
<\/p>\n
M. Elhoseiny, B. Saleh, and A.Elgammal
\n\u201cWrite a Classifier: Zero Shot Learning Using Purely Textual Descriptions\u201d
\nICCV 2013<\/p>\n
<\/p>\n
Haopeng Zhang, Zhiguo Jiang, and Ahmed Elgammal
\n\u201cVision-Based Pose Estimation for Cooperative Space Objects\u201d,
\nActa Astronautica Volume 91, October\u2013November 2013<\/p>\n
<\/p>\n
Sheng Huang, Ahmed Elgammal, and Dan Yang
\n\u201cLearning Speed Invariant Gait Template via Thin Plate Spline Kernel Manifold Fitting\u201d
\nBMVC 2013<\/p>\n
<\/p>\n
Haopeng Zhang, Tarek El-Gaaly, Ahmed Elgammal, Zhiguo Jiang
\n\u201cJoint Object and Pose Recognition Using Homeomorphic Manifold Analysis\u201d
\nAAAI 2013<\/p>\n
<\/p>\n
B. Saleh, A. Farhadi, A. Elgammal
\n\u201cObject-Centric Anomaly Detection by Attribute-Based Reasoning\u201d
\nCVPR 2013
\nA. Bakry, A. Elgammal
\n\u201cManifold Kernel Partial Least Squares for Lipreading and Speaker identification\u201d
\nCVPR 2013<\/p>\n
<\/p>\n
A. Elgammal and C.-S Lee
\n\u201cHomeomorphic Manifold Analysis (HMA): Generalized Separation of Style and Content on Manifolds\u201d,
\nImage and Vision Computing Journal, April 2013 – Editor Choice Article<\/strong><\/em><\/p>\n <\/p>\n
I. Chakraborty, A. Elgammal, and R. Burd
\n\u201cVideo based Activity Recognition in Trauma Resuscitation\u201d
\nFG 2013<\/p>\n
<\/p>\n
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\n
2012<\/strong><\/p>\n <\/p>\n<\/div>\n<\/div>\n
\n
\n
\n
T. Senlet and A. Elgammal
\n\u201cSegmentation of Occluded Sidewalks in Satellite Images\u201d,
\nICPR 2012<\/p>\n
<\/p>\n
T. El-Gaaly, M. Torki, A. Elgammal and M. Singh
\n\u201cRGBD Object Pose Recognition Using Local-Global Multi-Kernel Regression\u201d
\nICPR 2012<\/p>\n
<\/p>\n
A. Elqursh and A. Elgammal
\n\u201cVideo Figure Ground Labeling\u201d
\nICPR 2012<\/p>\n
<\/p>\n
R. Arora and A. Elgammal
\n\u201cTowards Automated Classification of Fine-Art Painting Style: A Comparative Study\u201d
\nICPR 2012<\/p>\n
<\/p>\n
A. Elqursh and A. Elgammal
\n\u201cSingle Axis Relative Rotation from Orthogonal Lines\u201d
\nICPR 2012<\/p>\n
<\/p>\n
A. Elqursh and A. Elgammal
\n\u201cOnline Moving Camera Background Subtraction\u201d
\nECCV 2012<\/p>\n
<\/p>\n
T. Senlet and A. Elgammal
\n\u201cSatellite Image Based Precise Robot Localization on Sidewalks\u201d
\nICRA 2012<\/p>\n
<\/p>\n
C.-S. Lee and A. Elgammal
\n\u201cStyle Adaptive Contour Tracking of Human Gait Using Explicit Manifold Models\u201d
\nMachine vision and applications journal,
\nMay 2012<\/p>\n
<\/p>\n
<\/p>\n<\/div>\n<\/div>\n<\/div>\n
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\n
\n
\n
\n
\n
2011<\/strong><\/p>\n <\/p>\n<\/div>\n<\/div>\n
\n
\n
\n
E. K. Gnang, A. Elgammal, V. Retakh
\n\u201cA Spectral Theory for Tensors\u201d
\nThe Annales de la Facult\u00e9 des Sciences de Toulouse, S\u00e9r. 6, 20 no. 4 (2011), p. 801-841.
\nAvailable at arXiv::1008.:2923v4 [math.SP]<\/p>\n
<\/p>\n
M. Torki and A. Elgammal
\n\u201cRegression from Local Features for Viewpoint and Posture Estimation\u201d
\nICCV\u201911<\/p>\n
<\/p>\n
T. Senlet and A. Elgammal
\n\u201cA Framework for Global Vehicle Localization Using Stereo Images and Satellite and Road Maps\u201d
\n2nd IEEE Workshop on Computer Vision in Vehicle Technology: From Earth to Mars, in conjunction with ICCV 2011<\/p>\n
<\/p>\n
T. Parag and A. Elgammal
\n\u201cHigher Order Markov Networks for Model Estimation\u201d
\nInternational Symposium on Visual Computing (ISVC\u201911)<\/p>\n
<\/p>\n
T. Parag and A. Elgammal
\n\u201cSupervised Hypergraph Labeling\u201d
\nCVPR\u201911<\/p>\n
<\/p>\n
A. Elqursh and A. Elgammal
\n\u201cLine-Based Relative Pose Estimation\u201d
\nCVPR\u201911<\/p>\n
<\/p>\n
S. Smaldone, C. Tonde, V. K. Ananthanarayanan, A. Elgammal, and L. Iftode
\n\u201cThe Cyber-Physical Bike: A Step Towards Safer Green Transportation\u201d
\nHotMobile\u201911<\/p>\n
<\/p>\n<\/div>\n<\/div>\n<\/div>\n
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\n
\n
2010<\/strong><\/p>\n <\/p>\n<\/div>\n<\/div>\n
\n
\n
\n
M. Torki, A. Elgammal, and C-S. Lee
\n“Learning a Joint Manifold Representation from Multiple Data Sets\u201d
\nICPR\u201910<\/p>\n
<\/p>\n
I. Chakraborty and A. Elgammal
\n“Object Localization by Propagating Connectivity via Superfeatures\u201d
\nICPR\u201910<\/p>\n
<\/p>\n
M. Torki and A. Elgammal
\n\u201cOne-Shot Multi-Set Non-rigid Feature-Spatial Matching\u201d
\nCVPR\u201910<\/p>\n
<\/p>\n
M. Torki and A. Elgammal
\n\u201cPutting Local Features on a Manifold\u201d
\nCVPR\u201910<\/p>\n
<\/p>\n
C-S. Lee and A. Elgammal
\n\u201cCoupled Visual and Kinematics Manifold Models for Human Motion Analysis\u201d
\nInternational Journal on Computer Vision. Volume 87, Numbers 1-2, March 2010.<\/p>\n
<\/p>\n<\/div>\n<\/div>\n<\/div>\n
<\/div>\n<\/div>\n<\/div>\n<\/div>\n
\n
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\n
\n
2009<\/strong><\/p>\n <\/p>\n<\/div>\n<\/div>\n
\n
\n
\n
I. Chakraborty and A. Elgammal
\n“Contour segment matching by integrating intra and inter shape cues of objects”;
\nBMVC\u201909,<\/p>\n
<\/p>\n
C-S. Lee and A. Elgammal
\n\u201cDynamic shape outlier detection for human locomotion\u201d
\nComputer Vision and Image Understanding Journal (CVIU). Volume 113, Issue 3, March 2009.<\/p>\n
<\/p>\n
C-S. Lee and A. Elgammal
\n\u201cTracking People on a Torus\u201d
\nIEEE transactions on Pattern Analysis and Machine Intelligence, March 2009<\/p>\n
<\/p>\n<\/div>\n<\/div>\n<\/div>\n
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\n
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\n
\n
2008<\/strong><\/p>\n <\/p>\n<\/div>\n<\/div>\n
\n
\n
\n
Z. Zhao and A. Elgammal
\n“Information Theoretic Key Frame Selection for Action Recognition”
\nBMVC\u201908<\/p>\n
<\/p>\n
Z. Zhao and A. Elgammal
\n\u201cHuman Activity Recognition from Frames\u2019 Spatiotemporal Representation\u201d
\nICPR\u201908<\/p>\n
<\/p>\n
I. Chakraborty and A. Elgammal
\n\u201cObject Detection based on Substructure Grouping\u201d
\nICPR\u201908<\/p>\n
<\/p>\n
Z. Zhao and A. Elgammal
\n\u201cSpatiotemporal Pyramid Representation for Recognition of Facial Expressions and Hand Gestures\u201d
\nFGR\u201908<\/p>\n
<\/p>\n
T. Paraq, F. Porikli and A. Elgammal
\n\u201cBoosting Adaptive Linear Weak Classi\ufb01ers for Online learning and Tracking\u201d
\nCVPR\u201908<\/p>\n
<\/p>\n<\/div>\n<\/div>\n<\/div>\n
<\/div>\n<\/div>\n<\/div>\n<\/div>\n
\n
\n
\n
\n
\n
2007<\/strong><\/p>\n <\/p>\n<\/div>\n<\/div>\n
\n
\n
\n
C.-S. Lee and A. Elgammal
\n“Modeling View and Posture Manifolds for Tracking”
\nICCV’07<\/p>\n
<\/p>\n
A. Elgammal and C.-S. Lee
\n\u201cNonlinear Manifold Learning for Dynamic Shape and Dynamic Appearance\u201d
\nComputer Vision and Image Understanding (CVIU) special issue on generative model based vision. April 2007<\/p>\n
<\/p>\n
C.-S. Lee and A. Elgammal
\n\u201cTracking People on a Torus\u201d
\ntechnical report DCS – TR611<\/p>\n
<\/p>\n<\/div>\n<\/div>\n<\/div>\n
<\/div>\n<\/div>\n<\/div>\n<\/div>\n
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\n
\n
\n
\n
2006<\/strong><\/p>\n <\/p>\n<\/div>\n<\/div>\n
\n
\n
\n
C.-S. Lee A. Elgammal
\n\u201cBody Pose Tracking From Uncalibrated Camera Using Supervised Manifold Learning\u201d
\nNIPS- Workshop on Evaluation of Articulated Human Motion and Pose Estimation. EHuM06.<\/p>\n
<\/p>\n
A. Elgammal
\n\u201cHuman-centered Multimedia, Representations and Challenges\u201d
\nThe 1st ACM international Workshop on Human-Centered Multimedia HCM ’06 — with ACM- Multimedia 2006.
\nInvited Position Paper.<\/strong><\/em><\/p>\n <\/p>\n
T. Parag and A. Elgammal
\n\u201cUnsupervised Learning of Boosted Tree Classifier using Graph Cuts for Hand Pose Recognition\u201d
\nBMVC’06,<\/p>\n
<\/p>\n
Z. Zhao and A. Elgammal
\n\u201cA statistically selected Part-Based Probabilistic Model for Object Recognition\u201d,
\nInternational Workshop on Intelligent Computing in Pattern Analysis aand Synthesis, IWICPAS 2006.<\/p>\n
<\/p>\n
R. Isukapalli, A. Elgammal and R. Greiner
\n\u201cLearning Policies for Efficiently Identifying Objects of Many Classes\u201d
\nICPR’06<\/p>\n
I. Chakraborty and A. Elgammal
\n\u201cCombining Low and High Level Features for Object Recognition\u201d
\nICPR’06<\/p>\n
<\/p>\n
C.-S. Lee and A. Elgammal
\n\u201cNonlinear Shape and Appearance Models for Facial Expressions\u201d
\nICPR’06<\/p>\n
<\/p>\n
C.-S. Lee and A. Elgammal
\n\u201cSimultaneous Inferring View and Body Pose Using Torus Manifolds\u201d
\nICPR’06<\/p>\n
<\/p>\n
C.-S. Lee, A. Elgammal and Dimitris Metaxas,
\n\u201cSynthesis and Control of High Resolution Facial Expressions for Visual Interactions\u201d
\nICME’06<\/p>\n
<\/p>\n
C.-S. Lee and A. Elgammal
\n\u201cCarrying Object Detection Using Pose Preserving Dynamic Shape Model\u201d
\nAMDO’06 – LNCS 4069<\/p>\n
<\/p>\n
C.-S. Lee and A. Elgammal
\n\u201cHuman Motion Synthesis by Motion Manifold Learning and Motion Primitive Segmentation\u201d
\nAMDO’06 – LNCS 4069<\/p>\n
<\/p>\n
Z. Zhao, A. Vashist, A. Elgammal, I. Muchnik and C. Kulikowski
\n\u201cDiscriminative Part Selection using Combinatorial and Statistical Models for Part-Based Object Recognition\u201d
\nBeyond Patches Workshop – with CVPR’06<\/p>\n
<\/p>\n
T. Parag, A. Elgammal and A. Mittal
\n\u201cA Framework for Feature Selection for Background Subtraction\u201d
\nCVPR’06<\/p>\n
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R. Isukapalli, A. Elgammal and R. Greiner
\n\u201cLearning Efficient Multiclass Object Detection Hierarchy\u201d
\nECCV’06 – LNCS 3951 Vol. I<\/p>\n
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N. Ravi, P.Shankar, A. Frankel, A. Elgammal and L. Iftode
\n\u201cIndoor Localization Using Camera Phones\u201d
\nThe 7th IEEE Workshop on Mobile Computing Systems and Applications, WMCSA 2006, April 2006.<\/p>\n
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C.-S. Lee and A. Elgammal
\n\u201cGait Tracking and Recognition using Person-Dependent Dynamic Shape Models\u201d
\nFGR’06<\/p>\n
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R. Isukapalli, A. Elgammal and R. Greiner
\n\u201cLearning to Identify Facial Expression During Detection using Markov Decision Process\u201d,
\nFGR’06<\/p>\n
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I. Awasthi and A. Elgammal
\n\u201cLearning Nonlinear Manifolds of Dynamic Textures\u201d
\nInternational Conference on Computer Vision Theory and Applications VISAPP’06<\/p>\n
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2005<\/strong><\/p>\n <\/p>\n<\/div>\n<\/div>\n
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C.-S. Lee and A. Elgammal
\n\u201cHomeomorphic Manifold Analysis: Learning Decomposable Generative Models for Human Motion Analysis\u201d
\nWorkshop on Dynamic Vision (WDV05), with ICCV’05<\/p>\n
<\/p>\n
C.-S. Lee and A. Elgammal
\n\u201cFacial Expression Analysis using Nonlinear Decomposable Generative Models\u201d
\nIEEE International Workshop on Analysis and Modeling of Faces and Gestures (AMFG05) with ICCV’05.<\/p>\n
<\/p>\n
R. Isukapalli, A. Elgammal, and R. Greiner
\n\u201cLearning a Dynamic Classification Method to Detect Faces and Identify Facial Expression\u201d
\nIEEE International Workshop on Analysis and Modeling of Faces and Gestures (AMFG05) with ICCV’05.<\/p>\n
C.-S. Lee and A. Elgammal
\n\u201cStyle Adaptive Bayesian Tracking Using Explicit Manifold Learning\u201d
\nBMVC’05<\/p>\n
C.-S. Lee and A. Elgammal
\n\u201cTowards Scalable View-Invariant Gait Recognition: Multilinear Analysis for Gait\u201d
\nAudio- and Video-based Biometric Person Authentication Conference AVBPA’05<\/p>\n
A. Elgammal
\n\u201cLearning to Track: Conceptual Manifold Map for Closed-form Tracking\u201d
\nCVPR’05<\/p>\n
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2004<\/strong><\/p>\n <\/p>\n<\/div>\n<\/div>\n
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V. Shet, V. Shiv Naga Prasad, A. Elgammal, L. S. Davis, Y. Yacoob
\n\u201cMulti-Cue Exemplar-Based Nonparametric Model for Gesture Recognition\u201d,
\n4th Indian Conference on Computer Vision, Graphics and Image Processing ICVGIP04
\nRecipient of Honorary Mention for Best Paper Award.<\/strong><\/em><\/p>\n <\/p>\n
Y. Wang, X. Huang, C.-S. Lee, S. Zhang, Z. Li, D. Samaras, D. Metaxas, A. Elgammal, P. Huang
\n\u201cHigh Resolution Acquisition, Learning and Transfer of Dynamic 3D Facial Expressions\u201d
\nEurographics 2004<\/p>\n
<\/p>\n
A. Elgammal, C.-S. Lee
\n\u201cSeparating Style and Content on a Nonlinear Manifold\u201d
\nCVPR’04<\/p>\n
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A. Elgammal, C.-S. Lee
\n\u201cInferring 3D Body Pose from Silhouettes using Activity Manifold Learning\u201d
\nCVPR’04<\/p>\n
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A. Elgammal
\n\u201cNonlinear Generative Models for Dynamic Shape and Dynamic Appearance\u201d
\n2nd International Workshop on Generative-Model based vision. GMBV 2004, with CVPR’04.<\/p>\n
<\/p>\n
A. Elgammal, C.-S. Lee
\n\u201cGait Style and Gait Content: Bilinear Model for Gait Recognition Using Gait Re-sampling\u201d
\nFGR’04<\/p>\n
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2003<\/strong><\/p>\n <\/p>\n<\/div>\n<\/div>\n
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A. Elgammal, R. Duraiswami and L. S. Davis
\n\u201cEfficient Kernel Density Estimation Using the Fast Gauss Transform for Computer Vision\u201d
\nIEEE Transactions on Pattern Analysis and Machine Intelligence. Dec 2003.<\/p>\n
<\/p>\n
S.-N. Lim, A. Elgammal, L. S. Davis
\n\u201cA Scalable Image-Based Multi-Camera Visual Surveillance System\u201d
\nIEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS 2003)<\/p>\n
<\/p>\n
S.-N. Lim, A. Elgammal, L. S. Davis
\n\u201cImage-based Pan-Tilt Camera Control in a Multi-Camera Surveillance Environment\u201d
\nICME’03<\/p>\n
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A. Elgammal, V. Shet, Y. Yacoob, and L. S. Davis
\n\u201cLearning Dynamics for Exemplar-based Gesture Recognition\u201d
\nCVPR’03<\/p>\n
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A. Elgammal, R. Duraiswami, and L. S. Davis
\n\u201cProbabilistic Tracking in Joint Feature-Spatial Spaces\u201d
\nCVPR’03<\/p>\n
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2002<\/strong><\/p>\n <\/p>\n<\/div>\n<\/div>\n
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A. Elgammal, R. Duraiswami, D. Harwood and L. S. Davis
\n\u201cBackground and Foreground Modeling using Non-parametric Kernel Density Estimation for Visual Surveillance\u201d,
\nProceedings of the IEEE, July 2002.<\/p>\n
<\/p>\n
A. Elgammal, V. Shet, Y. Yacoob, L. S. Davis
\n\u201cGesture Recognition using a Probabilistic Framework for Pose Matching\u201d
\nThe Seventh International Conference on Control, Automation, Robotics and Vision, ICARCV’02<\/p>\n
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