2008 |
49 | EE | Minyoung Kim,
Vladimir Pavlovic:
Dimensionality reduction using covariance operator inverse regression.
CVPR 2008 |
48 | EE | Minyoung Kim,
Sanjiv Kumar,
Vladimir Pavlovic,
Henry A. Rowley:
Face tracking and recognition with visual constraints in real-world videos.
CVPR 2008 |
47 | EE | Ameesh Makadia,
Vladimir Pavlovic,
Sanjiv Kumar:
A New Baseline for Image Annotation.
ECCV (3) 2008: 316-329 |
46 | EE | Pavel P. Kuksa,
Pai-Hsi Huang,
Vladimir Pavlovic:
Fast protein homology and fold detection with sparse spatial sample kernels.
ICPR 2008: 1-4 |
45 | EE | Pavel P. Kuksa,
Pai-Hsi Huang,
Vladimir Pavlovic:
Scalable Algorithms for String Kernels with Inexact Matching.
NIPS 2008: 881-888 |
44 | EE | Pai-Hsi Huang,
Vladimir Pavlovic:
Protein homology detection with biologically inspired features and interpretable statistical models.
IJDMB 2(2): 157-175 (2008) |
43 | EE | Yushi Jing,
Vladimir Pavlovic,
James M. Rehg:
Boosted Bayesian network classifiers.
Machine Learning 73(2): 155-184 (2008) |
2007 |
42 | EE | Minyoung Kim,
Vladimir Pavlovic:
Discriminative Learning of Dynamical Systems for Motion Tracking.
CVPR 2007 |
41 | EE | Minyoung Kim,
Vladimir Pavlovic:
Conditional State Space Models for Discriminative Motion Estimation.
ICCV 2007: 1-8 |
40 | EE | Rui Huang,
Vladimir Pavlovic,
Dimitris N. Metaxas:
Embedded Profile Hidden Markov Models for Shape Analysis.
ICCV 2007: 1-8 |
39 | EE | Minyoung Kim,
Vladimir Pavlovic:
A recursive method for discriminative mixture learning.
ICML 2007: 409-416 |
38 | EE | Rui Huang,
Vladimir Pavlovic,
Dimitris N. Metaxas:
Shape Analysis Using Curvature-Based Descriptors and Profile Hidden Markov Models.
ISBI 2007: 1220-1223 |
37 | EE | Pavel P. Kuksa,
Vladimir Pavlovic:
Fast Kernel Methods for SVM Sequence Classifiers.
WABI 2007: 228-239 |
36 | EE | Rui Huang,
Vladimir Pavlovic,
Dimitris N. Metaxas:
A Graphical Model Framework for Image Segmentation.
Applied Graph Theory in Computer Vision and Pattern Recognition 2007: 43-63 |
35 | EE | Mathias Kölsch,
Vladimir Pavlovic,
Branislav Kisacanin,
Thomas S. Huang:
Special issue on vision for human-computer interaction.
Computer Vision and Image Understanding 108(1-2): 1-3 (2007) |
34 | EE | Christian Vogler,
Siome Goldenstein,
Jorge Stolfi,
Vladimir Pavlovic,
Dimitris N. Metaxas:
Outlier rejection in high-dimensional deformable models.
Image Vision Comput. 25(3): 274-284 (2007) |
2006 |
33 | | Thomas S. Huang,
Nicu Sebe,
Michael S. Lew,
Vladimir Pavlovic,
Mathias Kölsch,
Aphrodite Galata,
Branislav Kisacanin:
Computer Vision in Human-Computer Interaction, ECCV 2006 Workshop on HCI, Graz, Austria, May 13, 2006, Proceedings
Springer 2006 |
32 | EE | Kooksang Moon,
Vladimir Pavlovic:
Impact of Dynamics on Subspace Embedding and Tracking of Sequences.
CVPR (1) 2006: 198-205 |
31 | EE | Minyoung Kim,
Vladimir Pavlovic:
Discriminative Learning of Mixture of Bayesian Network Classifiers for Sequence Classification.
CVPR (1) 2006: 268-275 |
30 | EE | Pai-Hsi Huang,
Vladimir Pavlovic:
Sparse Logistic Classifiers for Interpretable Protien Homology Detection.
ICDM Workshops 2006: 99-103 |
29 | EE | Rui Huang,
Vladimir Pavlovic,
Dimitris N. Metaxas:
A Profile Hidden Markov Model Framework for Modeling and Analysis of Shape.
ICIP 2006: 2121-2124 |
28 | EE | Rui Huang,
Vladimir Pavlovic,
Dimitris N. Metaxas:
A tightly coupled region-shape framework for 3D medical image segmentation.
ISBI 2006: 426-429 |
27 | EE | Steven Carroll,
Vladimir Pavlovic:
Protein classification using probabilistic chain graphs and the Gene Ontology structure.
Bioinformatics 22(15): 1871-1878 (2006) |
2005 |
26 | EE | Rui Huang,
Vladimir Pavlovic,
Dimitris N. Metaxas:
A Hybrid Framework for Image Segmentation Using Probabilistic Integration of Heterogeneous Constraints.
CVBIA 2005: 82-92 |
25 | EE | Yushi Jing,
Vladimir Pavlovic,
James M. Rehg:
Efficient discriminative learning of Bayesian network classifier via boosted augmented naive Bayes.
ICML 2005: 369-376 |
2004 |
24 | EE | Vladimir Pavlovic:
Model-Based Motion Clustering Using Boosted Mixture Modeling.
CVPR (1) 2004: 811-818 |
23 | EE | Rui Huang,
Vladimir Pavlovic,
Dimitris N. Metaxas:
A Graphical Model Framework for Coupling MRFs and Deformable Models.
CVPR (2) 2004: 739-746 |
22 | EE | Rui Huang,
Dimitris N. Metaxas,
Vladimir Pavlovic:
A Hybrid Face Recognition Method using Markov Random Fields.
ICPR (3) 2004: 157-160 |
2003 |
21 | EE | Jonathan Alon,
Stan Sclaroff,
George Kollios,
Vladimir Pavlovic:
Discovering Clusters in Motion Time-Series Data.
CVPR (1) 2003: 375-381 |
20 | | Yang Su,
T. M. Murali,
Vladimir Pavlovic,
Michael Schaffer,
Simon Kasif:
RankGene: identification of diagnostic genes based on expression data.
Bioinformatics 19(12): 1578-1579 (2003) |
19 | EE | James M. Rehg,
Vladimir Pavlovic,
Thomas S. Huang,
William T. Freeman:
Guest Editors' Introduction to the Special Section on Graphical Models in Computer Vision.
IEEE Trans. Pattern Anal. Mach. Intell. 25(7): 785-786 (2003) |
2002 |
18 | EE | Ashutosh Garg,
Vladimir Pavlovic,
Thomas S. Huang:
Bayesian Networks as Ensemble of Classifiers.
ICPR (2) 2002: 779-784 |
17 | EE | Tanzeem Choudhury,
James M. Rehg,
Vladimir Pavlovic,
Alex Pentland:
Boosting and Structure Learning in Dynamic Bayesian Networks for Audio-Visual Speaker Detection.
ICPR (3) 2002: 789- |
16 | | Vladimir Pavlovic,
Ashutosh Garg,
Simon Kasif:
A Bayesian framework for combining gene predictions.
Bioinformatics 18(1): 19-27 (2002) |
2000 |
15 | EE | Vladimir Pavlovic,
James M. Rehg:
Impact of Dynamic Model Learning on Classification of Human Motion.
CVPR 2000: 1788-1795 |
14 | EE | Vladimir Pavlovic,
James M. Rehg,
Ashutosh Garg,
Thomas S. Huang:
Multimodal Speaker Detection Using Error Feedback Dynamic Bayesian Networks.
CVPR 2000: 2034- |
13 | EE | Ashutosh Garg,
Vladimir Pavlovic,
James M. Rehg:
Audio-Visual Speaker Detection Using Dynamic Bayesian Networks.
FG 2000: 384-390 |
12 | EE | Vladimir Pavlovic,
James M. Rehg,
Tat-Jen Cham:
A Dynamic Bayesian Network Approach to Tracking Using Learned Switching Dynamic Models.
HSCC 2000: 366-380 |
11 | EE | Vladimir Pavlovic,
Ashutosh Garg,
James M. Rehg:
Multimodal Speaker Detection Using Input/Output Dynamic Bayesian Networks.
ICMI 2000: 308-316 |
10 | | Vladimir Pavlovic,
James M. Rehg,
John MacCormick:
Learning Switching Linear Models of Human Motion.
NIPS 2000: 981-987 |
9 | EE | Rajeev Sharma,
Michael Zeller,
Vladimir Pavlovic,
Thomas S. Huang,
Zion Lo,
Stephen M. Chu,
Yunxin Zhao,
James C. Phillips,
Klaus Schulten:
Speech/Gesture Interface to a Visual-Computing Environment.
IEEE Computer Graphics and Applications 20(2): 29-37 (2000) |
1999 |
8 | EE | Vladimir Pavlovic,
Brendan J. Frey,
Thomas S. Huang:
Time-Series Classification Using Mixed-State Dynamic Bayesian Networks.
CVPR 1999: 2609- |
7 | EE | Vladimir Pavlovic,
James M. Rehg,
Tat-Jen Cham,
Kevin P. Murphy:
A Dynamic Bayesian Network Approach to Figure Tracking using Learned Dynamic Models.
ICCV 1999: 94-101 |
6 | EE | Vladimir Pavlovic,
Brendan J. Frey,
Thomas S. Huang:
Variational Learning in Mixed-State Dynamic Graphical Models.
UAI 1999: 522-530 |
1998 |
5 | | Vladimir Pavlovic:
Multimodal Tracking and Classification of Audio-Visual Features.
ICIP (1) 1998: 343-347 |
1997 |
4 | EE | Michael Zeller,
James C. Phillips,
A. Dalke,
W. Humphrey,
Klaus Schulten,
Thomas S. Huang,
Vladimir Pavlovic,
Yunxin Zhao,
Zion Lo,
Stephen M. Chu,
Rajeev Sharma:
A Visual Computing Environment for Very Large Scale Biomolecular Modeling.
ASAP 1997: 3- |
3 | EE | Vladimir Pavlovic,
G. A. Berry,
Thomas S. Huang:
Integration of Audio/Visual Information for Use in Human-Computer Intelligent Interaction.
ICIP (1) 1997: 121-124 |
2 | EE | Vladimir Pavlovic,
Rajeev Sharma,
Thomas S. Huang:
Visual Interpretation of Hand Gestures for Human-Computer Interaction: A Review.
IEEE Trans. Pattern Anal. Mach. Intell. 19(7): 677-695 (1997) |
1996 |
1 | EE | Vladimir Pavlovic,
Rajeev Sharma,
Thomas S. Huang:
Invited Speech: "Gestural Interface to a visual computing Environment for Molecular biologists".
FG 1996: 30-37 |