This page lists papers and other topics of interest for the weekly MIR seminar. In Fall 2004, the seminars are Thursdays from 1:30-2:30 in CS343.

Spring 2005 Papers and Discussion Topics

• April 14: A. Hyvärinen: Survey of Independent Component Analysis. Neural Computing Surveys 2 (1999) 94-128 PDF.
• April 7: cancelled
• March 31: cancelled
• March 24: N. R. Howe, T. M. Rath and R. Manmatha: Boosted Decision Trees for Word Recognition in Handwritten Document Retrieval PDF
• March 17: cancelled
• March 10: cancelled
• March 3: cancelled
• February 24: C. Raphael: Aligning Musical Scores with Audio using Hybrid Graphical Models PDF.
• February 17: D. Hoiem, R. Sukthankar, H. Schneiderman, L. Huston: Object-Based Image Retrieval Using the Statistical Structure of Images PDF.
• February 10: R. Manmatha and Jamie L. Rothfeder: A Scale Space Approach for Automatically Segmenting Words from Historical Handwritten Documents. PDF.
• February 3: cancelled
• January 27: X. Chen, J. Yang, J, Zhang and A. Waibel: Automatic Detection and Recognition of Signs From Natural Scenes. IEEE Trans. on Image Processing 13:1 (2004) 87-99.y

Fall 2004 Papers

• N. Mohanty, T. M. Rath, A. Lee and R. Manmatha: Learning Shape for Image Classification and Retrieval. PDF.
• J. Edwards, Y. W. Teh, D. A. Forsyth, M. Maire, R. Bock and Vesom: Making Latin Manuscripts Searchable using gHMM's. In: Advances in Neural Information Processing Systems, vol. 17, 2004 PDF.
• E. Hadjidemetriou, M. D. Grossberg and S. K. Nayar: Multiresolution Histograms and Their Use for Recognition. IEEE Trans. on Pattern Analysis and Machine Intelligence 26:7 2004 PDF.
• E. G. Miller, N. E. Matsakis and P. A. Viola: Learning from One Example Through Shared Densities on Transforms. In: Proc. of the Conference on Computer Vision and Pattern Recognition 2000 PDF.
• Nick Howe talked about his work on boosting to improve the recognition of handwritten historical documents.

Spring 2003 Papers

• T. M. Rath and R. Manmatha: Features for Word Spotting in Historical Manuscripts PDF.
• M. Weber, M. Welling and P. Perona: Unsupervised Learning of Models for Recognition PDF.
• R. Fergus, P. Perona and A. Zisserman: Object class recognition by unsupervised scale-invariant learning (best paper award at CVPR'03) PDF.
• J. Rothfeder, S. Feng and T. M. Rath: Using Corner Feature Correspondences to Rank Word Images by Similarity at the DIAR-03 workshop PDF.
• Henry Schneiderman and Takeo Kanade: A Statistical Method for 3D Object Detection Applied to Faces and Cars PDF
• Kobus Barnard, Pinar Duygulu, Raghavendra Guru, Prasad Gabbur, and David Forsyth: The effects of segmentation and feature choice in a translation model of object recognition. Computer Vision and Pattern Recognition, 2003. PDF
• G. Mori and J. Malik: Recognizing Objects in Adversarial Clutter: Breaking a Visual CAPTCHA PDF
• Rong Jin, ChengXiang Zhai, Alex G. Hauptmann: Information Retrieval for OCR Documents: A Content-based Probabilistic Correction Model PDF
• Rong Jin and Alex G. Hauptmann: Using a Probabilistic Source Model for Comparing Images PDF

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