Publications

2014 | 2013 | 2012 | 2011 | 2010 | 2009 | 2008 | 2007 | 2006 | 2005 | 2004 | 2003 | 2002 | 2001 | 2000 | 1999 | 1998 | 1997 | 1995 | 1993

2014
  • Andrew Kae, Ben Marlin, and Erik Learned-Miller.
    The Shape-Time Random Field for Semantic Video Labeling
    Computer Vision and Pattern Recognition (CVPR), 2014.
    [pdf] [supplementary material]
  • Jacqueline Feild.
    Improving Text Recognition in Images of Natural Scenes.
    PhD Thesis, University of Massachusetts Amherst, 2014.
    [pdf]

2013
  • Manjunath Narayana, Allen Hanson, Erik Learned-Miller.
    Coherent Motion Segmentation in Moving Camera Videos using Optical Flow Orientations
    International Conference on Computer Vision (ICCV), 2013.
    [pdf] [supplementary material]
  • Manjunath Narayana, Allen Hanson, Erik Learned-Miller.
    Background Subtraction - Separating the Modeling and the Inference
    Machine Vision and Applications (MVA) journal, 2013.
    [pdf]
  • Andrew Kae*, Kihyuk Sohn*, Honglak Lee, and Erik Learned-Miller
    Augmenting CRFs with Boltzmann Machine Shape Priors for Image Labeling
    Computer Vision and Pattern Recognition (CVPR), 2013.
    *The first and second authors made equal contributions and should be considered co-first authors.
    [pdf]
  • Jacqueline Feild, Erik Learned-Miller.
    Improving Open-Vocabulary Scene Text Recognition
    In Proceedings of the International Conference on Document Analysis and Recognition (ICDAR), 2013.
    [pdf]
  • Jacqueline Feild, Erik Learned-Miller, David A. Smith.
    Using a Probabilistic Syllable Model to Improve Scene Text Recognition
    In Proceedings of the International Conference on Document Analysis and Recognition (ICDAR), 2013.
    [pdf]
  • Yahan Zhou, Jacqueline Feild, Rui Wang, Erik Learned-Miller
    Scene Text Segmentation via Inverse Rendering
    In Proceedings of the International Conference on Document Analysis and Recognition (ICDAR), 2013.
    [pdf]
  • Benjamin Mears, Laura Sevilla-Lara, Erik Learned-Miller.
    Adaptive kernels for improved local patch alignment.
    In Proceedings of the British Machine Vision Conference (BMVC), 2013.
    [pdf]

2012
  • Gary B. Huang, Marwan Mattar, Honglak Lee, Erik Learned-Miller.
    Learning to Align from Scratch
    Advances in Neural Information Processing Systems (NIPS), 2012.
    [pdf]
  • Manjunath Narayana, Allen Hanson, and Erik Learned-Miller.
    Improvements in Joint Domain-Range Modeling for Background Subtraction
    Proceedings of the British Machine Vision Conference (BMVC), 2012.
    [pdf]
  • Marwan Mattar, Allen Hanson, Erik Learned-Miller
    Unsupervised Joint Alignment and Clustering using Bayesian Nonparametrics
    Conference on Uncertainty in Artifical Intelligence (UAI), 2012.
    [pdf]
  • Gary B. Huang, Andrew Kae, Carl Doersch, Erik Learned-Miller
    Bounding the Probability of Error for High Precision Optical Character Recognition
    Journal of Machine Learning Research (JMLR), 2012.
    [pdf]
  • Laura Sevilla-Lara and Erik Learned-Miller.
    Distribution Fields for Tracking
    IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2012.
    [pdf]
  • Manjunath Narayana, Allen Hanson, and Erik Learned-Miller.
    Background Modeling using Adaptive Pixelwise Kernel Variances in a Hybrid Feature Space
    IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2012.
    [pdf]
  • Gary B. Huang, Honglak Lee, and Erik Learned-Miller.
    Learning Hierarchical Representations for Face Verification with Convolutional Deep Belief Networks
    IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2012.
    [pdf]

2011
  • Laura Sevilla-Lara and Erik Learned-Miller
    Distribution Fields
    Technical Report UM-CS-2011-027, Dept. of Computer Science, University of Massachusetts Amherst, 2011.
    [pdf]
  • Andrew Kae, Kin Kan, Vijay K Narayanan, Dragomir Yankov
    Categorization of Display Ads using Image and Landing Page Features
    The Third Workshop on Large-scale Data Mining: Theory and Applications'11 (LDMTA'11), in conjunction with SIGKDD2011, to appear.
    [pdf]
  • Vidit Jain and Erik Learned-Miller.
    Online Domain-Adaptation of a Pre-Trained Cascade of Classifiers.
    IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2011.
    [pdf]
  • David L. Smith, Jacqueline Feild, Erik Learned-Miller.
    Enforcing Similarity Constraints with Integer Programming for Better Scene Text Recognition
    IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2011.
    [pdf]
  • Vidit Jain and Manik Varma.
    Learning to Re-Rank: Query-Dependent Image Re-Ranking Using Click Data.
    the International World Wide Web (WWW) Conference, 2011.
    [pdfsoon]
  • Andrew Kae, David A. Smith, and Erik Learned-Miller
    Learning on the Fly: A font-free approach towards multilingual OCR
    International Journal on Document Analysis and Recognition (IJDAR)
    [pdf] [Springer]

2010
  • Vidit Jain.
    Using Context to Enhance the Understanding of Face Images.
    PhD Thesis, University of Massachusetts Amherst, 2010.
    [pdf]
  • Vidit Jain and Erik Learned-Miller.
    FDDB: A Benchmark for Face Detection in Unconstrained Settings.
    Technical Report UM-CS-2010-009, Dept. of Computer Science, University of Massachusetts Amherst, 2010.
    [pdf]
  • Gary B. Huang and Erik Learned-Miller.
    Learning Class-Specific Image Transformations with Higher-Order Boltzmann Machines.
    In Structured Models in Computer Vision Workshop in CVPR, 2010.
    [pdf]
  • Andrew Kae, Gary Huang, Carl Doersch, and Erik Learned-Miller
    Improving State-of-the-Art OCR through High-Precision Document-Specific Modeling
    Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2010. [pdf]

2009
  • Vidit Jain.
    Naïve Bayes vs. Logistic Regression: An Assessment of the Impact of the Misclassification Cost.
    NIPS Workshop on the Generative and Discriminative Learning Interface (NIPS GDLI), 2009.
    [pdf]
  • Andrew Kae, Gary B. Huang, and Erik Learned-Miller
    Bounding the Probability of Error for High Precision Recognition.
    Technical Report UM-CS-2009-031, Dept. of Computer Science, University of Massachusetts, Amherst, 2009.
    [pdf] [arxiv.org]
  • Andrew Kae and Erik Learned-Miller
    Learning on the fly: Font free approaches to difficult OCR problems.
    Proceedings of the International Conference on Document Analysis and Recognition (ICDAR), 2009.
    [pdf]
  • Jerod Weinman, Erik Learned-Miller, and Allen Hanson
    Scene text recognition using similarity and a lexicon with sparse belief propagation.
    To appear in IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), Special Issue on Probabilistic Graphical Models, 2009.
    [pdf]
  • Marwan Mattar, Stephen Murtagh, and Allen Hanson
    Software Tools for Image Analysis.
    Technical Report UM-CS-2009-017, Dept. of Computer Science, University of Massachusetts, Amherst, 2009.
    [pdf]
  • Marwan Mattar, Michael Ross, and Erik Learned-Miller
    Nonparametric Curve Alignment.
    Intl. Conference on Acoustics, Speech and Signal Processing, 2009.
    [pdf]

2008
  • Dan Xie, Tingxin Yan, Deepak Ganesan, and Allen R. Hanson
    Design and Implementation of a Dual-Camera Wireless Sensor Network for Object Retrieval.
    Intl. Conference on Information Processing in Sensor Networks (IPSN), 2008.
    [pdf]
  • Jerod J. Weinman, Erik Learned-Miller, and Allen R. Hanson.
    A Discriminative Semi-Markov Model for Robust Scene Text Recognition.
    Intl. Conference on Pattern Recognition (ICPR), 2008.
    [pdf]
  • Gary B. Huang, Michael J. Jones, and Erik Learned-Miller.
    LFW Results Using a Combined Nowak Plus MERL Recognizer.
    Faces in Real-Life Images Workshop in European Conference on Computer Vision (ECCV), 2008.
    [pdf]
  • Gary B. Huang, Marwan Mattar, Tamara Berg, and Erik Learned-Miller.
    Labeled Faces in the Wild: A Database for Studying Face Recognition in Unconstrained Environments.
    Faces in Real-Life Images Workshop in European Conference on Computer Vision (ECCV), 2008.
    [pdf]
  • Vidit Jain, Amit Singhal, and Jiebo Luo.
    Selective Hidden Random Fields: Exploiting Domain Specific Saliency for Event Classification.
    IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2008.
    [pdf]
  • Gary B. Huang, Manjunath Narayana, and Erik Learned-Miller.
    Towards unconstrained face recognition.
    The Sixth IEEE Computer Society Workshop on Perceptual Organization in Computer Vision IEEE CVPR, 2008.
    [pdf]
  • Andras Ferencz, Erik Learned-Miller, and Jitendra Malik.
    Learning to locate informative features for visual identification.
    International Journal of Computer Vision: Special Issue on Learning and Vision, Volume 77, Number 1, pp. 3-24, May, 2008.
    [pdf]
  • Tamara L. Berg, Alex C. Berg, Jaety Edwards, Michael Maire, Ryan White, Yee Whye Teh, Erik Learned-Miller, and David Forsyth.
    Names and Faces.
    To appear International Journal of Computer Vision, 2008.
  • Erik Learned-Miller and Joseph DeStefano.
    A probabilistic upper bound on differential entropy.
    Under revision IEEE Transactions on Information Theory, 2008.
    [pdf]
  • P.E. Dickson, W.R.Adrion, A.R. Hanson AR.
    Automatic Capture and Presentation Creation from Multimedia Lectures.
    Frontiers in Education, 2008.
    [pdf]
  • P.E. Dickson, W.R. Adrion, A.R. Hanson.
    Automatic Creation of Indexed Presentations from Classroom Lectures.
    Proceedings of the 13th Annual Conference on Innovation and Technology in Computer Science Education, 2008.
    [pdf]
  • Jerod J. Weinman.
    Unified Detection and Recognition for Reading Text in Scene Images.
    PhD Thesis, University of Massachusetts Amherst, 2008.
    [pdf]

2007
  • Gary B. Huang, Vidit Jain, and Erik Learned-Miller.
    Unsupervised joint alignment of complex images.
    International Conference on Computer Vision (ICCV), 2007.
    [pdf]
  • Vidit Jain, Erik Learned-Miller, and Andrew McCallum.
    People-LDA: Anchoring topics to people using face recognition.
    International Conference on Computer Vision (ICCV), 2007.
    [pdf]
  • Wallace B, Adrion WR, Dickson P, Cooper W, Ros I, Watts K.
    Evolution of a cross-platform, multimedia courseware presentation system.
    ACM Transactions on Internet Technology, 2007.
    [pdf]
  • P. Dickson, W.R. Adrion, A. Hanson.
    Automatic Identification and Storage of Significant Points in a Computer-based Presentation.
    International Journal of Interactive Technology and Smart Education, 2007.
    [pdf]
  • Gary B. Huang, Manu Ramesh, Tamara Berg and Erik Learned-Miller.
    Labeled Faces in the Wild: A database for studying face recognition in unconstrained environments.
    UMass Amherst Technical Report 07-49, 11 pages, 2007.
    [pdf]
  • Michael Wick, Michael G. Ross and Erik Learned-Miller.
    Context-Sensitive Error Correction: Using Topic Models to Improve OCR.
    Proceedings of the International Conference on Document Analysis and Recognition (ICDAR), 2007.
    [pdf]
  • Jerod Weinman, Erik Learned-Miller, and Allen Hanson.
    Fast Lexicon-Based Scene Text Recognition with Sparse Belief Propagation.
    Proceedings of the International Conference on Document Analysis and Recognition (ICDAR), 2007.
    [pdf]
  • Gary C. Huang, Erik Learned-Miller, and Andrew McCallum.
    Cryptogram Decoding for OCR using Numerization Strings.
    Proceedings of the International Conference on Document Analysis and Recognition (ICDAR), 2007.
    [pdf]
  • David Walker Duhon, Jerod Weinman and Erik Learned-Miller.
    Techniques and applications for persistent backgrounding in a humanoid torso robot.
    IEEE International Conference on Robotics and Automation (ICRA), 2007.
    [pdf]

2006
  • Dickson P, Adrion WR, Hanson A.
    Automatic Capture of Significant Points in a Computer Based Presentation.
    Proceedings of the Eighth IEEE International Symposium on Multimedia. IEEE Computer Society, 2006.
    [pdf]
  • Marwan Mattar and Erik Learned-Miller.
    Improved generative models for continuous image features through tree-structured non-parametric distributions.
    UMass Amherst Technical Report 06-57, 10 pages, 2006.
    [pdf]
  • Dov Katz, Emily Horrell, Yuandong Yang, Brendan Burns, Thomas Buckley, Anna Grishkan, Volodymyr Zhylkovskyy, Oliver Brock, and Erik Learned-Miller.
    The UMass mobile manipulator UMan: An experimental platform for autonomous mobile manipulation.
    In Workshop on Manipulation in Human Environments, at Robotics: Science and Systems, 2006.
    [pdf]
  • Vidit Jain, Andras Ferencz, and Erik Learned-Miller.
    Discriminative training of hyper-feature models for object identification.
    Proceedings of the British Machine Vision Conference (BMVC), Volume 1, pp. 357-366, 2006.
    [pdf]
  • Erik Learned-Miller, Qifeng Lu, Angela Paisley, Peter Trainer, Volker Blanz, Katrin Dedden, and Ralph E. Miller.
    Detecting acromegaly: Screening for disease with a morphable model.
    Medical Image Computing and Computer-Assisted Intervention (MICCAI), Volume 2, pp. 495-503, 2006.
    [pdf]
  • Jerod Weinman and Erik Learned-Miller.
    Improving recognition of novel input with similarity.
    In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Volume 1, pp. 308-315, 2006.
    [pdf]
  • Ron Bekkerman, Mehran Sahami and Erik Learned-Miller.
    Combinatorial Markov random fields.
    Proceedings of the European Conference on Machine Learning (ECML) 17, pp. 30-41, 2006.
    [pdf]
  • Erik Learned-Miller.
    Data driven image models through continuous joint alignment.
    In IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 28:2, pp. 236-250, 2006.
    [pdf]
  • Manjunatha N. Jagalur, Chris Pal, Erik Learned-Miller, R. T. Zoeller and David Kulp.
    The processing and analysis of in situ gene expression images of the mouse brain.
    Workshop on New Problems and Methods in Computational Biology, at Neural Information Processing Systems, 2006.
    [pdf]
  • Jerod J. Weinman, Allen Hanson and Erik Learned-Miller.
    Joint feature selection for object detection and recognition.
    UMass Amherst Technical Report 06-54, 8 pages, 2006.
    [pdf]
  • Gary Huang, Erik Learned-Miller and Andrew McCallum.
    Cryptogram decoding for optical character recognition.
    UMass Amherst Technical Report 06-45, 12 pages, 2006.
    [pdf]
  • Dimitri Lisin.
    Image Classification with Bags of Local Features.
    PhD Thesis, University of Massachusetts Amherst, 2006.
    [pdf]

2005
  • Andras Ferencz, Erik Learned-Miller, and Jitendra Malik.
    Building a classification cascade for visual identification from one example.
    In International Conference on Computer Vision (ICCV), pp. 286-293, 2005.
    [pdf]
  • Andras Ferencz, Erik Learned-Miller, and Jitendra Malik.
    Learning hyper-features for visual identification.
    In Neural Information Processing Systems (NIPS) 17, pp. 425-432, 2005.
    [pdf]
  • Erik Learned-Miller and Parvez Ahammad.
    Joint MRI bias removal using entropy minimization across images.
    In Neural Information Processing Systems (NIPS) 17, pp. 761-768, 2005.
    [pdf]
  • Lilla Zollei, Erik Learned-Miller, Eric Grimson, and William Wells.
    Efficient population registration of 3D data.
    In Workshop on Computer Vision for Biomedical Image Applications: Current Techniques and Future Trends, at the International Conference of Computer Vision (best paper award), 2005.
    [pdf]
  • Erik Learned-Miller and Vidit Jain.
    Many heads are better than one: Jointly removing bias from multiple MRs using nonparametric maximum likelihood.
    In Proceedings of Information Processing in Medical Imaging, pp. 615-626, 2005.
    [pdf]
  • Dimitri A. Lisin, Marwan A. Mattar, Matthew B. Blaschko, Mark C. Benfield, and Erik G. Learned-Miller.
    Combining local and global features for object class recognition.
    In Workshop on Learning in Computer Vision and Pattern Recognition at IEEE CVPR, 2005.
    [pdf]
  • Marwan A. Mattar, Allen R. Hanson, and Erik G. Learned-Miller.
    Sign classification using local and meta-features.
    In Proceedings of the IEEE Workshop on Computer Vision Applications for the Visually Impaired (in conjunction with CVPR), 2005.
    [pdf]
  • Erik Learned-Miller, Qifeng Lu, Angela Paisley, Peter Trainer, Volker Blanz, Katrin Dedden, and Ralph Miller.
    Early diagnosis of acromegaly by facial pattern recognition.
    Abstract for The Ninth International Pituitary Congress, San Diego, CA, 2005.
  • Joseph DeStefano, Qifeng Lu, and Erik Learned-Miller.
    A probabilistic upper bound on differential entropy.
    UMass Amherst Technical Report 05-12, 2005.
    [pdf]
  • Marwan A. Mattar, Allen R. Hanson, and Erik G. Learned-Miller.
    Sign classification for the visually impaired.
    University of Massachusetts Technical Report 05-14, 2005.
    [pdf]
  • Qifeng Lu, Erik Learned-Miller, Angela Paisley, Peter Trainer, Volker Blanz, Katrin Dedden, and Ralph Miller.
    Detecting acromegaly: Screening for diseases with a morphable model.
    UMass Amherst Technical Report 05-37, 2005.
    [pdf]

2004
  • Tamara Berg, Alex Berg, Jaety Edwards, Michael Maire, Ryan White, Yee Whye Teh, Erik Learned-Miller and David Forsyth.
    Names and faces in the news.
    In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Vol. 2, pp. 848-854, 2004.
    [pdf]
  • Erik Learned-Miller.
    Hyperspacings and the estimation of information theoretic quantities.
    UMass Amherst Technical Report 04-104, 2004.
    [pdf]

2003
  • Erik Learned-Miller and John W. Fisher, III.
    ICA using spacings estimates of entropy.
    Journal of Machine Learning Research (JMLR), Volume 4, pp. 1271-1295, 2003.
    [pdf]
  • Erik Miller and Christophe Chefd'hotel.
    Practical non-parametric density estimation on a transformation group for vision.
    In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Volume 2, pp. 114-121, 2003.
    [pdf]
  • Kinh Tieu and Erik Miller.
    Unsupervised color constancy.
    In Neural Information Processing Systems (NIPS) 15, pp. 1303-1310, 2003.
    [pdf]
  • Erik Miller.
    A new class of entropy estimators for multi-dimensional densities.
    International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2003.
    [pdf]
  • Erik Miller and John W. Fisher, III.
    ICA using spacings estimates of entropy.
    Fourth International Symposium on Independent Components Analysis and Blind Signal Separation, 2003.
    [pdf]
  • Erik Miller and John W. Fisher, III.
    Independent components analysis by direct entropy minimization.
    UC Berkeley Technical Report CSD-03-1221, 25 pages, 2003.
    [pdf]

2002
  • Chris Stauffer, Erik Miller and Kinh Tieu.
    Transform-invariant image decomposition with similarity templates.
    In Neural Information Processing Systems (NIPS) 14, pp. 1295-1302, 2002.
    [pdf]
  • Erik Miller.
    Learning from one example in machine vision by sharing probability densities.
    Ph.D. Thesis, Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2002.
    [pdf]

2001
  • Simon Warfield, Jan Rexilius, Petra Huppi, Terrie Inder, Erik Miller, William Wells, Gary Zientara, Ferenc Jolesz, and Ron Kikinis.
    A binary entropy measure to assess nonrigid registration algorithms.
    Proceedings of Medical Image Computing and Computer-Assisted Intervention (MICCAI), pp. 266-274, 2001.
    [pdf]
  • Erik Miller and Kinh Tieu.
    Color eigenflows: Statistical modeling of joint color changes.
    International Conference on Computer Vision (ICCV), Volume 1, pp. 607-614, 2001.
    [pdf]
  • Erik Miller, Kinh Tieu and Eric Grimson.
    Lighting invariance through joint color change models.
    Proceedings of Workshop on Identifying Object Across Variations in Lighting: Psychophysics and Computation, at IEEE Conference on Computer Vision and Pattern Recognition, 2001.
    [pdf]
  • Erik Miller, Kinh Tieu and Chris Stauffer.
    Learning object-independent modes of variation with feature flow fields.
    Massachusetts Institute of Technology, AI-Memo: AIM-2001-021, 9 pages, 2001.
    [pdf]
  • Simon Warfield, Petra Huppi, Terrie Inder, Erik Miller, William Wells, Gary Zientara, Ferenc Jolesz, and Ron Kikinis.
    An intrinsic coordinate system of the developing human brain.
    Fifth International Conference on Cognitive and Neural Systems, Boston, MA, page 28, 2001.
    [pdf]

2000
  • Erik Miller, Nick Matsakis, and Paul Viola.
    Learning from one example through shared densities on transforms.
    Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Volume 1, pp. 464-471, 2000.
    [pdf]

1999
  • Erik Miller.
    Alternative tilings for improved surface area estimates by local counting algorithms.
    In Computer Vision and Image Understanding (CVIU), Volume 74, pages 193-211, 1999.
    [pdf]

1998
  • Erik Miller and Paul Viola.
    Ambiguity and constraint in mathematical expression recognition.
    Proceedings of the National Conference of Artificial Intelligence (AAAI), pp. 784-791, 1998.
    [pdf]

1997
  • Erik Miller.
    An analysis of surface area estimates of binary volumes under three tilings.
    Masters Thesis, Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 1997.
    [pdf]

1995
  • Douglas Cohen, Jonathan Lustgarten, Erik Miller, Alexander Khandji and Robert Goodman.
    Effects of coregistration of MR to CT images on MR stereotactic accuracy.
    Journal of Neurosurgery, Volume 82, pp. 772-779, 1995.

1993
  • Robert Malison, Erik Miller, Robin Greene, Greg McCarthy, Dennis Charney and Robert Innis.
    Computer assisted coregistration of multislice SPECT and MR brain images by fixed external fiducials.
    Journal of Computer Assisted Tomography, Volume 17, pp. 952-960, 1993.