UCLA VISION LAB COURSES
 
  1. C. Chen and D. Freedman. On the hardness of computing the size of homology classes. Submitted to Computational Geometry: Theory and Applications. Arxiv version
  2. D. Freedman and M. Turek. Dealing with strongly varying illumination: tracking via computation of the motion field. Submitted to International Journal of Computer Vision.
  3. C. Chen and D. Freedman. Finding natural generators for homology groups. Submitted to Discrete and Computational Geometry. Arxiv version
  4. D. Freedman and M. Turek. Graph cuts with many-pixel interactions: theory and applications to shape modelling. Submitted to Image and Vision Computing.
  5. A. Ayvaci and D. Freedman. Interactive segmentation of medical imagery. Submitted to Biomedical Signal Processing and Control.
  6. M. Turek and D. Freedman. Generalized multi-object tracking via joint label and motion estimation. Submitted to Computer Vision and Image Understanding.
  7. C. Chen and D. Freedman. Quantifying homology classes. In International Symposium on Theoretical Aspects of Computer Science (STACS 08). .
  8. M. Turek and D. Freedman. Multiscale modeling and constraints for segmentation, restoration, and optical flow. Submitted to Computer Vision and Image Understanding.
  9. A. Ayvaci and D. Freedman. Joint segmentation-registration of organs using geometric models. International Conference of the IEEE Engineering in Medicine and Biology Society, 2007. pdf
  10. D. Freedman. An incremental algorithm for reconstruction of surfaces of arbitrary codimension. Computational Geometry: Theory and Applications, 36(2):106-116, 2007. pdf
  11. M. Turek and D. Freedman. Multiscale modeling and constraints for max-flow/min- cut problems in computer vision. IEEE Computer Society Workshop on Perceptual Organization in Computer Vision (in conjunction with IEEE CVPR 2006). pdf
  12. D. Freedman and P. Drineas. Energy minimization via graph cuts: settling what is possible. In IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), volume 2, pages 939-946, 2005. pdf
  13. D. Freedman and M. Turek. Illumination-invariant tracking via graph cuts. In IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), volume 2, pages 10-17, 2005. pdf
  14. D. Freedman and T. Zhang. Interactive graph cut based segmentation with shape priors. In IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), volume 1, pages 755-762, 2005. pdf
  15. D. Freedman, R. J. Radke, T. Zhang, Y. Jeong, D. M. Lovelock, and G. T. Y. Chen. Model-based segmentation of medical imagery by matching distributions. IEEE Transactions on Medical Imaging, 24(3):281-292, 2005. pdf
  16. T. Zhang and D. Freedman. Improving performance of distribution tracking through background mismatch. IEEE Transactions on Pattern Analysis and Machine Intelligence, 27(2):282-287, 2005. pdf
  17. D. Freedman. Surface reconstruction, one triangle at a time. In Proceedings of the Sixteenth Canadian Conference of Computational Geometry (CCCG), pages 15-19, 2004. pdf
  18. D. Freedman, R.J. Radke, T. Zhang, Y. Jeong, and G.T.Y Chen. Model-based multi-object segmentation via distribution matching. In Proceeding of the Third IEEE Workshop on Articulated and Nonrigid Motion (in conjunction with IEEE CVPR 2004), June 27, 2004, Baltimore, MD. pdf
  19. D. Freedman and T. Zhang. Active contours for tracking distributions. IEEE Transactions on Image Processing, 13(4):518-526, 2004. pdf
  20. T. Zhang and D. Freedman. Tracking objects using density matching and shape priors. Accepted to the Ninth IEEE International Conference on Computer Vision (ICCV). pdf
  21. D. Freedman. Effective tracking through tree-search. IEEE Transactions on Pattern Analysis and Machine Intelligence, 25(5):604-615, 2003. pdf
  22. D. Freedman. Combinatorial curve reconstruction in Hilbert Spaces: a new sampling theory and an old result revisited. Computational Geometry: Theory and Applications, 23(2):227-241, 2002. pdf
  23. Y. Shao, M. Magdon-Ismail, D. Freedman, S. Akella, M. Zaki, and C. Bystroff. Compression of protein conformational space. In 6th Annual International Conference on Research in Computational Molecular Biology (RECOMB02), Washington, DC, April 2002 (poster). pdf
  24. D. Freedman. Efficient simplicial reconstructions of manifolds from their samples. IEEE Transactions on Pattern Analysis and Machine Intelligence, 24(10):1349 -1357, 2002. pdf
  25. D. Freedman. Manifold reconstruction from unorganized points. In Proceedings of the Thirty Fourth Annual Asilomar Conference on Signals, Systems, and Computers, 2000. pdf
  26. D. Freedman and M. Brandstein. Contour tracking in clutter: a subset approach. International Journal of Computer Vision, 38(2):173-186, 2000. pdf
  27. D. Freedman and M. Brandstein. Provably fast algorithms for contour tracking. In Proceedings of the 2000 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, volume 1, pages 139-144, 2000. pdf
  28. D. Freedman and M. Brandstein. Methods of global optimization in contour tracking. In Proceedings of the Thirty Third Annual Asilomar Conference on Signals, Systems, and Computers, volume 1, pages 725-729,1999. pdf
  29. D. Freedman and M. Brandstein. A subset approach to contour tracking in clutter. In Proceedings of the Seventh IEEE International Conference on Computer Vision, volume 1, pages 242-247, 1999. pdf
  30. R. Taylor, A. Sachrajda, D. Freedman, and P. Kelly. Density of electrons in a lateral quantum dot by semi-classical trajectory analysis. Solid State Communications, 89(7):579-582, 1994.