William T. Freeman

Selected papers, grouped by topic

(last updated: January, 2011. ) See other page for all publications.



Miscellaneous

W. T. Freeman, Where computer vision needs help from computer science, ACM-SIAM Symposium on Discrete Algorithms, January, 2011 [pdf],

Accidental pinhole and pinspeck cameras: revealing the scene outside the picture IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), June 2012. pdf

Computer graphics

A. Levin, D. Glasner, Y. Xiong, F. Durand, W. Freeman, W. Matusik, T. Zickler Fabricating BRDFs at High Spatial Resolution Using Wave Optics ACM Transactions on Graphics, Volume 32, Number 4 (Proc. SIGGRAPH) 2013 pdf, [Project web page, with presentations and videos]

Neal Wadhwa, Michael Rubinstein, Fredo Durand, William T. Freeman Phase-based Video Motion Processing ACM Transactions on Graphics, Volume 32, Number 4 (Proc. SIGGRAPH) 2013 pdf, [Project web page, with presentations and videos]

Hao-Yu Wu, Michael Rubinstein, Eugene Shih, John Guttag, Fredo Durand, William T. Freeman Eulerian Video Magnification for Revealing Subtle Changes in the World ACM Transactions on Graphics, Volume 31, Number 4 (Proc. SIGGRAPH) 2012 pdf Project web page

YiChang Shih, Abe Davis, Sam Hasinoff, Fredo Durand, William T. Freeman Laser Speckle Photography for Surface Tampering Detection IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), June 2012. pdf Project web page

Micah K. Johnson, Kevin Dale, Shai Avidan, Hanspeter Pfister, William T. Freeman, Wojciech Matusik. CG2Real: Improving the Realism of Computer Generated Images using a Large Collection of Photographs IEEE Transactions on Visualization and Computer Graphics (IEEE TVCG) 2011 pdf, [Project web page]

T. S. Cho, S. Avidan and W. T. Freeman, A Probabilistic Image Jigsaw Puzzle Solver , IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), June 2010. [pdf], [project page].

T. S. Cho, S. Avidan, and W. T. Freeman, The Patch Transform, EEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), vol. 32, issue 8, pages 1489 - 1501, August, 2010 [pdf]

Long Zhu, Yuanhao Chen, William Freeman, Antonio Torralba. Nonparametric Bayesian Texture Learning and Synthesis Neural Information Processing Systems (NIPS) 2009. pdf

S. W. Hasinoff, K. N. Kutulakos, F. Durand and W. T. Freeman, Time-constrained Photography, Proc. 12th IEEE International Conference on Computer Vision (ICCV 2009, oral presentation). software.

A. Levin, Y. Weiss, F. Durand, and W. T. Freeman, Efficient Marginal Likelihood Optimization in Blind Deconvolution, IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), June 2011. pdf extended TR Code by Anat Levin

A. Levin, Y. Weiss, F. Durand, and W. T. Freeman, Understanding and evaluating blind deconvolution algorithms, Best paper award runner up. IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), June 2009. pdf extended TR Motion blur data slides

A. Levin, S. Hasinoff, P. Green, F. Durand, W. T. Freeman, 4D Frequency Analysis of Computational Cameras for Depth of Field Extension, SIGGRAPH, ACM Transactions on Graphics, Aug 2009. pdf project page

A. Levin, P. Sand, T. S. Cho, F. Durand, W. T. Freeman, Motion-Invariant Photography, ACM Transactions on Graphics, 27(3), (Proc. SIGGRAPH), August, 2008. pdf file. , Project page.

A. Levin, W. T. Freeman, and F. Durand Understanding camera trade-offs through a Bayesian analysis of light field projections European Conference on Computer Vision, ECCV 2008 pdf file. , Longer Technical Report. , Code.

Taeg Sang Cho, Moshe Butman, Shai Avidan, William T. Freeman, "The patch transform and its applications to image editing" 2008 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) pdf file. , project web page. Best Poster Award, CVPR 2008.

J. Sivic, B. Kaneva, A. Torralba, S. Avidan and W. T. Freeman, Creating and exploring a large photorealistic virtual space, First IEEE Workshop on Internet Vision, associated with CVPR 2008. pdf file.

C. Liu, H. Y. Shum and W. T. Freeman, Face Hallucination: theory and practice, International Journal of Computer Vision, Vol. 75, no. 1, pp. 115-134, October, 2007. pdf file. See also web page.

C. Liu, R. Szeliski, S. B. Kang, C. L. Zitnick, and W. T. Freeman, Automatic estimation and removal of noise from a single image, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), Vol 30, No. 2, pp. 299-314, Feb., 2008. pdf file.

N. Joshi, W. Matusik, S. Avidan, H. Pfister, and W. T. Freeman, Exploring defocus matting: non-parametric acceleration, super-resolution, and off-center matting, to appear in IEEE Computer Graphics and Applications, special issue on Computational Photography, 2007. pdf file. See also project page.

R. Fergus, B. Singh, A. Hertzmann, S. Roweis, and W. T. Freeman", Removing camera shake from a single image, SIGGRAPH 2006. pdf file. See also web page.

A. Levin, R. Fergus, F. Durand, and W. T. Freeman", Image and depth from a conventional camera with a coded aperture, ACM Trans. On Graphics (Proc. SIGGRAPH 2007) pdf file. See also web page.

Ce Liu, Antonio Torralba, William Freeman, Fredo Durand, and Edward Adelson, Motion Magnification, SIGGRAPH 2005. pdf file. See also web page.

C. Liu, W. T. Freeman, E. H. Adelson and Y. Weiss, Human-assisted motion annotation. IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2008. pdf file. , Project page.

William T. Freeman, Thouis R. Jones, and Egon C. Pasztor, Example-based super-resolution, IEEE Computer Graphics and Applications, March/April, 2002. (pdf);
MERL technical report: software and images

A. Efros and W. T Freeman, Image quilting for texture synthesis and transfer, SIGGRAPH 2001. pdf file.

W. T Freeman and H. Zhang, Shapetime photography, IEEE Computer Vision and Pattern Recognition (CVPR), Madison, WI, June, 2003. (pdf file).

G. Dalley, W. T. Freeman, and J. Marks Single-frame Text Super-resolution: A Bayesian Approach International Conference on Image Processing (ICIP), Oct. 2004. (pdf file).

Style and content

Joshua B. Tenenbaum, William T. Freeman Separating style and content with bilinear models Neural Computation 12(6), pp. 1247-1283, 2000. (pdf file).

W. T. Freeman and J. B. Tenenbaum, Learning bilinear models for two-factor problems in vision , IEEE Conference on Computer Vision and Pattern Recognition (CVPR '97), Puerto Rico, U. S. A., June, 1997. Received Outstanding Paper prize, CVPR '97 MERL-TR96-37.

W. T. Freeman, J. B. Tenenbaum, E. Pasztor, Learning style translation for the lines of a drawing. ACM Transactions on Graphics, January, 2003 (pdf file).

Belief propagation and applications in vision

Michael Rubinstein, Ce Liu, Peter Sand, Fredo Durand, Bill Freeman Motion Denoising with Application to Time-lapse Photography Proc. 23rd IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2011. [pdf], [project page],

Erik B. Sudderth, Alexander T. Ihler, Michael Isard, William T. Freeman, and Alan S. Willsky, Nonparametric Belief Propagation, Communications of the ACM, October, 2010.

E. Sudderth and W. T. Freeman, Signal and Image Processing with Belief Propagation, DSP Application Column, IEEE Signal Processing Magazine, Mar. 2008. pdf file.

E. Sudderth, A. Torralba, W. T. Freeman, and A. Willsky, Describing visual scenes using transformed objects and parts, International Journal of Computer Vision, 77, May 2008. pdf file.

M. F. Tappen, B. C. Russell, and W. T. Freeman, Efficient graphical models for processing images IEEE Conf. on Computer Vision and Pattern Recognition (CVPR) Washington, DC, 2004. (pdf file).

J. Yedidia, W. T. Freeman, and Y. Weiss Generalized Belief Propagation in Advances in Neural Information Processing Systems 13, edited by T. K. Leen, T. G. Dietterich, and V. Tresp, pp. 689-695, 2001. MERL-TR2000-26.

J. Yedidia, W. T. Freeman and Y. Weiss, Understanding belief propagation and its generalizations International Joint Conference on Artificial Intelligence (IJCAI 2001), Distinguished Papers Track. pdf file.

Y. Weiss and W. T. Freeman Correctness of Belief Propagation in Gaussian Graphical Models of Arbitrary Topology. Neural Computation, Vol. 13, No. 10, Oct., 2001, pp. 2173--2200.

Y. Weiss and W. T. Freeman On the optimality of solutions of the max-product belief propagation algorithm in arbitrary graphs. IEEE Trans. Information Theory, Special Issue on Codes on Graphs and Iterative Algorithms, 47(2), pp. 723-735, 2001. MERL-TR99-39.

W. T. Freeman, E. C. Pasztor, O. T. Carmichael Learning Low-Level Vision International Journal of Computer Vision, 40(1), pp. 25-47, 2000. MERL-TR2000-05.

E. B. Sudderth, A. T. Ihler, W. T. Freeman and A. S. Willsky Nonparametric Belief Propagation and Facial Appearance Estimation, IEEE Computer Vision and Pattern Recognition (CVPR), Madison, WI, June, 2003. (pdf file). Web page and code are here.

E. Sudderth, M. Mandel, W. Freeman, and A. Willsky, Distributed Occlusion Reasoning for Tracking with Nonparametric Belief Propagation. in Advances in Neural Information Processing Systems 17 (NIPS), Vancouver, BC, MIT Press, 2005. (pdf file). Web page and code are here.

M. F. Tappen and W. T. Freeman, Comparison of graph cuts with belief propagation for stereo, using identical MRF parameters, IEEE Intl. Conference on Computer Vision (ICCV), Nice, France, October, 2003. (pdf file).

Recovering intrinsic images.

R. Grosse, M.K. Johnson, E.H. Adelson, and W.T. Freeman Ground-truth dataset and baseline evaluations for intrinsic image algorithms International Conference on Computer Vision, 2009. pdf MIT intrinsic images web page.

M. F. Tappen, W. T. Freeman, and E. H. Adelson, Recovering Intrinsic Images from a Single Image, In IEEE Transactions on Pattern Analysis and Machine Intelligence, Volume 27, Issue 9, September 2005, Pages 1459 - 1472 pdf file.

M. Tappan, E. Adelson, and W. T. Freeman, Estimating Intrinsic Component Images using Non-Linear Regression. IEEE Conf. on Computer Vision and Pattern Recognition (CVPR) New York, NY, June, 2006. (pdf file). The training and test data from this paper is also available as a .MAT file [.ZIP (10 MB)]

Y. Weiss and W. T. Freeman, What makes a good model of natural images?, IEEE Computer Vision and Pattern Recognition (CVPR) 2007 pdf file. See also MATLAB code from Y.W. and training data.

T. S. Cho, W. T. Freeman and H. Tsao, A reliable skin mole localization scheme, IEEE Computer Society Workshop on Mathematical Methods in Biomedical Image Analysis, In the Proceedings of International Conference of Computer Vision Oct. 14-17, 2007 pdf file.

B. C. Russell, A. Torralba, K. P. Murphy, and W. T. Freeman, LabelMe: a Database and Web-based Tool for Image Annotation International Journal of Computer Vision, 77(1-3):157-173, 2008. pdf file. , Project page.

A. Torralba and W. T. Freeman, Properties and Applications of Shape Recipes, IEEE Computer Vision and Pattern Recognition (CVPR), Madison, WI, June, 2003. (pdf file).

William T. Freeman and Antonio Torralba Shape Recipes: Scene Representations that Refer to the Image in Advances in Neural Information Processing Systems 15 (NIPS), MIT Press, 2003 (pdf file).

Marshall F. Tappen, William T. Freeman and Edward H. Adelson Recovering Intrinsic Images from a Single Image in Advances in Neural Information Processing Systems 15 (NIPS), MIT Press, 2003 (pdf file).

M. Bell and W. T. Freeman, Learning local evidence for shading and reflectance, , International Conference on Computer Vision, Vancouver, BC, CANADA, 2001. MERL-TR2001-04.

W. T. Freeman and P. A. Viola, Bayesian model of surface perception, Neural Information Processing Systems, volume 10, pp. 787-793, 1998. MERL-TR98-05.

Bayesian models for vision

Roger B. Grosse, Ruslan Salakhutdinov, William T. Freeman, and Joshua B. Tenenbaum, Exploiting compositionality to explore a large space of model structures, Conf. on Uncertainty in Artificial Intelligence (UAI), August 2012. pdf

Michael Rubinstein, Ce Liu, William T. Freeman, Towards Longer Long-Range Motion Trajectories, British Machine Vision Conference (BMVC) 2012.

Hyun Sung Chang, Yair Weiss, William T. Freeman Informative Sensing of Natural Images IEEE Int. Conf. Image Processing, Egypt, Nov. 2009. pdf

M. F. Tappen, C. Liu, W. T. Freeman, and E. H. Adelson, Learning Gaussian Conditional Random Fields for Low-Level Vision, IEEE Computer Vision and Pattern Recognition (CVPR) 2007. pdf file. A sample training implementation is also available [.ZIP]

A. Torralba, R. Fergus, and W. T. Freeman, 80 million tiny images: a large dataset for non-parametric object and scene recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence., Volume 30 , Issue 11 (November 2008), Pages: 1958-1970. [pdf file]. [project page].

B. C. Russell, A. Torralba, C. Liu, R. Fergus, W. T. Freeman, Object Recognition by Scene Alignment, Advances in Neural Information Processing Systems (NIPS), 2007. pdf file. , project page.

J. Sivic, B. C. Russell, A. Zisserman, W. T. Freeman, and A. A. Efros, Unsupervised Discovery of Visual Object Class Hierarchies IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2008. pdf file.

K. Murphy, A. Torralba, D. Eaton, W. T. Freeman, Object detection and localization using local and global features, Lecture Notes in Computer Science (unrefeered). Sicily workshop on object recognition, 2005. pdf file.

B. C. Russell, A. Torralba, C. Liu, R. Fergus, W. T. Freeman, Object Recognition by Scene Alignment, To appear in Advances in Neural Information Processing Systems, 2007.

D. H. Brainard, P. Longere, P. B. Delahunt, W. T. Freeman, J. M. Kraft, and B. Xiao, Bayesian model of human color constancy, Journal of Vision, 6, 1267-1281, http://journalofvision.org/6/11/10/, doi:10.1167/6.11.10. 2006.

C. Liu, W. T. Freeman and E. H. Adelson, Analysis of contour motions, Advances in Neural Information Processing Systems (NIPS 2006). Received Outstanding Student Paper Award. pdf file. December, 2006.

B. C. Russell, , A. Efros, J. Sivic, W. T. Freeman, and A. Zisserman, Using multiple segmentations to discover objects and their extent in image collections, IEEE Conf. on Computer Vision and Pattern Recognition (CVPR) New York, NY, June, 2006. (pdf file). (web page).

E. Sudderth, A. Torralba, W. T. Freeman, and A. Willsky, Depth from familiar objects: a hierarchical model for 3d scenes, IEEE Conf. on Computer Vision and Pattern Recognition (CVPR) New York, NY, June, 2006. (pdf file).

C. Liu, W. T. Freeman, R. Szeliski, and S. B. Kang, Noise estimation from a single image, IEEE Conf. on Computer Vision and Pattern Recognition (CVPR) New York, NY, June, 2006. (pdf file).

E. Sudderth, A. Torralba, W. Freeman, and A. Willsky Describing Visual Scenes using Transformed Dirichlet Processes. Neural Information Processing Systems (NIPS), Vancouver, B.C., Dec. 2005. (pdf file).

J. Sivic, B. Russell, A. A. Efros, A. Zisserman, W. T. Freeman, Discovering Objects and their Location in Images International Conference on Computer Vision (ICCV), Beijing, China, Oct. 2005. (pdf file).

E. Sudderth, A. Torralba, W. Freeman, and A. Willsky Learning Hierarchical Models of Scenes, Objects, and Parts International Conference on Computer Vision (ICCV), Beijing, China, Oct. 2005. (pdf file).

Antonio Torralba, Kevin P. Murphy, William T. Freeman Contextual Models for Object Detection Using Boosted Random Fields Neural Information Processing Systems (NIPS), Vancouver, B.C., Dec. 2004. (pdf file).

A. Torralba, K. P. Murphy, and W. T. Freeman Sharing visual features for multiclass and multiview object detection IEEE Conf. on Computer Vision and Pattern Recognition (CVPR) Washington, DC, 2004. And MIT CSAIL technical report (pdf file).

A. Torralba, K. P. Murphy, and W. T. Freeman Sharing visual features for multiclass and multiview object detection IEEE Transactions on Pattern Analysis and Machine Intelligence , vol. 29, no. 5, pp. 854-869, May, 2007. (pdf file).

K. Murphy, A. Torralba, and W. T. Freeman, Using the forest to see the trees: a graphical model relating features, objects, and scenes, in Advances in Neural Information Processing Systems 16 (NIPS), Vancouver, BC, MIT Press, 2004. (pdf file).

A. Torralba, K. P. Murphy, W. T. Freeman, and M. A. Rubin, Context-based vision system for place and object recognition, IEEE Intl. Conference on Computer Vision (ICCV), Nice, France, October, 2003. (pdf file).

W. T. Freeman, The generic viewpoint assumption in a framework for visual perception, Nature, vol. 368, p. 542 - 545, April 7, 1994. reprint.

W. T. Freeman, Exploiting the generic viewpoint assumption, International Journal Computer Vision, 20 (3), 243-261, 1996. MERL-TR93-15a.

D. H. Brainard and W. T. Freeman, Bayesian Color Constancy, Journal of the Optical Society of America, A, 14(7), pp. 1393-1411, July, 1997. pdf file.

Michael E. Leventon, William T. Freeman, Bayesian Estimation of 3-D Human Motion MERL-TR98-06.

Nicholas R. Howe, Michael E. Leventon, William T. Freeman, Bayesian Reconstruction of 3D Human Motion from Single-Camera Video To appear in: Advances in Neural Information Processing Systems 12, edited by S. A. Solla, T. K. Leen, and K-R Muller, 2000. MERL-TR99-37.

Computer vision for interactive computer graphics

W. T. Freeman, D. Anderson, P. Beardsley, C. Dodge, H. Kage, K. Kyuma, Y. Miyake, M. Roth, K. Tanaka, C. Weissman, W. Yerazunis, Computer vision for interactive computer graphics , in IEEE Computer Graphics and Applications, volume 18, number 3, May--June, pp. 42-53, 1998. (pdf);
MERL-TR99-02.

W. T. Freeman, K. Tanaka, J. Ohta, and K. Kyuma, Computer vision for computer games, 2nd International Conference on Automatic Face and Gesture Recognition, Killington, VT, USA, pp. 100--105. MERL-TR96-35.

W. T. Freeman and C. Weissman, Television control by hand gestures, International Workshop on Automatic Face- and Gesture- Recognition, IEEE Computer Society, Zurich, Switzerland, June, 1995, pp. 179--183. MERL-TR94-24.

W. T. Freeman and M. Roth, Orientation histograms for hand gesture recognition, International Workshop on Automatic Face- and Gesture- Recognition, IEEE Computer Society, Zurich, Switzerland, June, 1995, pp. 296--301. Winner, 2013 Test-of-time award from Face and Gesture Recognition conference. MERL-TR94-03. Here is a 6-minute video prepared to accept the test-of-time award for the paper below, describing the work in its context, in .mov format , or in .mpeg format.

Joe Marks, William Freeman, and Henry Leitner, Teaching applied computing without programming: a case-based introductory course for general education, Proceedings of the thirty-second SIGCSE technical symposium on Computer Science Education, Charlotte, North Carolina, 2001. pdf file.

Steerable filters and the steerable pyramid

E. P. Simoncelli and W. T. Freeman, The steerable pyramid: a flexible architecture for multi-scale derivative computation, 2nd Annual IEEE International Conference on Image Processing, Washington, DC. October, 1995. MERL-TR95-15.

E. P. Simoncelli, W. T. Freeman, E. H. Adelson and D. J. Heeger. Shiftable Multi-Scale Transforms. IEEE Trans. Information Theory, Special Issue on Wavelets. Vol. 38, No. 2, pp. 587-607, March 1992. Abstract / Full (1.1M) pdf (2.1M)

W. T. Freeman and E. H. Adelson, The design and use of steerable filters, IEEE Trans. on Pattern Analysis and Machine Intelligence, vol. 13, no. 9, pp. 891 - 906, September, 1991. MIT Vision and Modeling Group TR 126. Also available as pdf file.

W. T. Freeman, E. H. Adelson, and D. J. Heeger, Motion without movement, ACM Computer Graphics, vol. 25, no. 4, (SIGGRAPH '91), pp. 27 - 30, July, 1991.

W. T. Freeman, Steerable Filters and Local Analysis of Image Structure, Ph.D. Thesis, Massachusetts Institute of Technology, 1992. Abstract , pdf file of thesis (2.3 Mbytes). Also available as Vision and Modeling Technical Report 190, MIT Media Laboratory.

Radar astronomy and electron microscopy

V. R. Eschleman, G. L. Tyler and W. T. Freeman, Deep Radio Occultations and 'Evolute Flashes': Their Characteristics and Utility for Planetary Studies, Icarus 37, 612-26 (1979).

E. J. Kirkland, W. T. Freeman, M. Ohtsuki, M. S. Isaacson, and B. S. Siegal, Computer Image Processing of STEM Images of Tobacco Mosaic Virus, Ultramicroscopy 6, 367-76 (1981).