ECE 904 Computer Vision Seminar
Fall 2008

In this course we review recent research publications related to visual detection, recognition, and tracking of people (or other objects), visual motion analysis, visual reconstruction, stereo vision, acoustic localization, robotic sensing, and other related topics. Each week we meet to discuss one paper from the recent literature.  Students should read the paper beforehand and prepare questions and comments in order to participate fully in the discussion.  In addition, students are encouraged to volunteer to lead the discussion at least once during the semester.  All students are welcome to attend, whether or not they are signed up for the course. (For details on how to get credit, see the bottom of this page.)

Here are some miscellaneous computer vision resources.





Discussion leader



Thomas Brox, Andres Bruhn, and Joachim Weickert, Variational Motion Segmentation with Level Sets, ECCV 2006

Stan Birchfield



A.B. Ashraf, S. Lucey, and T. Chen, Learning Patch Correspondences for Improved Viewpoint Invariant Face Recognition, CVPR 2008.   Manish Shiralkar



Alper Yilmaz, Xin Li, and Mubarak Shah, Contour-Based Object Tracking with Occlusion Handling in Video Acquired Using Mobile Cameras, PAMI 26(11), 2004 Wayne Ryan



Dileep George and Jeff Hawkins, A Hierarchical Bayesian Model of Invariant Pattern Recognition in the Visual Cortex, IJCNN 2005
Sumod Mohan



Changki Min and Gerard Medioni, Tensor Voting Accelerated by Graphics
Processing Units (GPU)
, ICPR 2006.
Trupti Patil



A. Sarti, R. Malladi, and J.A. Sethian, Subjective Surfaces: A Geometric Model for Boundary Completion, IJCV 46(3), 201-221, 2002. Nikhil Rane



N. Vlassis and A. Likas, A Greedy EM Algorithm for Gaussian Mixture
, Neural Processing Letters, 2002
Prakash C



B. Daubney, D. Gibson, N. Campbell, Real-time pose estimation of articulated objects using low-level motion, CVPR 2008.
Shrinivas Pundlik



A. Torralba, R. Fergus, and W. T. Freeman, 80 Million Tiny Images: A Large Data Set for Nonparametric Object and Scene Recognition, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.30, no.11, pp.1958-1970, Nov. 2008 Vidya Murali



Manish P. Shiralkar and Robert J. Schalkoff, Multiple-Class Spatiotemporal Flow Estimation Using a Modified Neural Gas Algorithm, submitted to Optical Engineering Manish Shiralkar






W. J. Ryan, D. L. Woodard, A. T. Duchowski, and S. T. Birchfield, Adapting Starburst for Elliptical Iris Segmentation, Proceedings of the IEEE Second International Conference on Biometrics: Theory, Applications and Systems (BTAS), Washington, D.C., September 2008. Wayne Ryan



A. Adam, E. Rivlin, and I. Shimshoni, Robust Fragments-based Tracking using the Integral Histogram, Computer Vision and Pattern Recognition, 2006 Nalin Pradeep



Ashutosh Saxena, Min Sun, Andrew Y. Ng, Make3D: Learning 3-D Scene Structure from a Single Still Image, To appear in IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 2008. Sumod Mohan
15 12/2 J. Sivic, B. Russell, A.A. Efros, A. Zisserman, and B. Freeman, Discovering Objects and Their Location in Images, International Conference on Computer Vision (ICCV 2005), October, 2005 Nikhil Rane

Papers covered in previous semesters

Potential future papers

  1. Pedro F. Felzenszwalb and Daniel P. Huttenlocher, Efficient Graph-Based Image Segmentation, International Journal of Computer Vision, Volume 59, Number 2, September 2004.
  2. E. Royer et al., Monocular Vision for Mobile Robot Localization and Autonomous Navigation, IJCV 2007
  3. G. Guo and C. R. Dyer, Patch-based Image Correlation with Rapid Filtering, CVPR 2007
  4. G. J. Brostow, R. Cipolla, Unsupervised Bayesian Detection of Independent Motion in Crowds, CVPR 2006.
  5. Denis McCarthy and Frank Boland, A Method for Source-Microphone Range Estimation in Reverberant Environments Using Arrays of Unknown Geometry, EURASIP Journal on Advances in Signal Processing, 2008
  6. Willert, V.; Eggert, J.; Adamy, J.; Stahl, R.; Korner, E., A Probabilistic Model for Binaural Sound Localization, IEEE Trans. on Systems, Man, and Cybernetics B, 36(5): 982-994, 2006
  7. Zezhi Chen, Nick Pears and Bojian Liang, Monocular obstacle detection using reciprocal-polar rectification, Image and Vision Computing, 24(12): 1301–1312, 2006
  8. Arthur E.C. Pece, Anthony D. Worrall, A comparison between feature-based and EM-based contour tracking, Image and Vision Computing, 24(12): 1218-1232, 2006
  9. Sun et al., "Bi-directional Tracking using Trajectory Segment Analysis", ICCV 2005.
  10. T.-J. Cham and J. M. Rehg, A Multiple Hypothesis Approach to Figure Tracking, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), volume 2, pages 239–245, Ft. Collins, CO, June 1999.
  11. Jean-Yves Bouguet, Pyramidal Implementation of the Lucas Kanade Feature Tracker
  12. Zoran Zivkovic, Ferdinand van der Heijden, Better features to track by estimating the tracking convergence region, ICPR 2002
  13. Eric Marchand, Francois Chaumette.  Features Tracking For Visual Servoing Purpose, 2004
  14. P. Bouthemy, "A Maximum Likelihood Framework for Determining Moving Edges," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 11,  no. 5,  pp. 499-511,  May 1989.
  15. J. Sivic, B. Russell, A.A. Efros, A. Zisserman, and B. Freeman, Discovering Objects and Their Location in Images,
    International Conference on Computer Vision (ICCV 2005), October, 2005.
  16. D. Beymer and K. Konolige.  Tracking People from a Mobile Platform.  International Symposium on Experimental Robotics, 2002.
  17. P. Felzenszwalb and D. Huttenlocher, Efficient Belief Propagation for Early Vision, CVPR 2004.
  18. A.R. Mansouri, “Region tracking via level set PDEs without motion computation,” PAMI, vol. 24, no. 7, pp. 947–961, 2002
  19. Yogesh Rathi Namrata Vaswani Allen Tannenbaum Anthony Yezzi, Particle Filtering for Geometric Active Contours with Application to Tracking Moving and Deforming Objects, CVPR 2005
  20. F. Rothganger, S. Lazebnik, C. Schmid, and J. Ponce.
    Segmenting, Modeling, and Matching Video Clips Containing Multiple Moving Objects.
    Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Washington, DC, June
    2004, vol. 2, pp. 914-921.
  21. Sifakis et al., Video Segmentation Using Fast Marching and Region Growing Algorithms, EURASIP Journal on Applied Signal Processing 2002:4, 379–388
  22. A. M. Martinez and M. Zhu, Where Are Linear Feature Extraction Methods Applicable?, IEEE Transactions on Pattern Analysis and Machine Intelligence, Volume 27, Issue 12, pp. 1934-1944, December 2005
  23. J. Xiao and M. Shah, Motion layer extraction in the presence of occlusion using graph cut, CVPR 2004
  24. Henele Adams, Sanjiv Singh, and Dennis Strelow. An empirical comparison of methods for image-based motion estimation. IEEE/RSJ International Conference on Intelligent Robots and Systems, October 2002. (PDF)
  25. A. Barbu, S.C. Zhu, Graph Partition By Swendsen-Wang Cuts, ICCV 2003
  26. S. Avidan, Support vector tracking, CVPR 2001
  27. Black and Jepson, Eigentracking:  Robust matching and tracking of articulated objects using a view-based representation, IJCV, 26(1), 1998
  28. Khan, Balch, Dellaert, A Rao-Blackwellized particle filter for eigentracking, CVPR 2004
  29. Freeman and Roth, Orientation histograms for hand gesture recognition, Workshop on AFGR, 1995
  30. Perez, Hue, Vermaak, Gangnet, Color-based probabilistic tracking, ECCV 2002
  31. Y. Wu, Robust visual tracking by integrating multiple cues based on co-inference learning, IJCV, 58(1), 2004
  32. Philomin, Duraiswami, Davis, Quasi-random sampling for condensation, ECCV 2000
  33. Brown, Burschka, and Hager, Advances in Computational Stereo, PAMI 2003.
  34. Tao Zhang, Daniel Freedman, Tracking Objects using Density Matching and Shape Priors, ICCV 2003
  35. Manifold learning web page
  36. Belkin, Niyogi, Laplacian eigenmaps for dimensionality reduction and data representation, Neural Comptuation, Vol. 15, Issue 6, June 2003
  37. Antonio Torralba Kevin P. Murphy William T. Freeman, Sharing features: efficient boosting procedures for multiclass object detection, CVPR 2004
  38. Baker and Matthews, Lucas-Kanade 20 years on:  A unifying framework, IJCV 56(3):221-255, 2004  webpage
  39. Molton, Davison, and Reid, Parameterisation and probability in image alignment, ACCV 2004.
  40. A. Davison, "3D Simultaneous Localisation and Map-Building Using Active Vision for a Robot Moving on Undulating Terrain", CVPR 2001
  41. Yann, LeNet-5 convolutional neural networks -- homepage
  42. Kass, Witkin, and Terzopoulos, Snakes:  Active Contour Models, ICCV 1987
  43. Grimson et al., Using adaptive tracking to classify and monitor activities in a site, CVPR 1998
  44. M. J. Jones and J. M. Rehg, Statistical Color Models with Application to Skin Detection, Int. J. of Computer Vision, 46(1):81-96, Jan 2002.
  45. Morency, Rahimi, Darrell, Adaptive View-based Appearance Model, CVPR, 2003
  46. M. Irani, Multi-Frame Optical Flow Estimation Using Subspace Constraints, ICCV 1999
  47. Wu and Huang,  A Co-inference Approach to Robust Visual Tracking
  48. Sigal, Sclaroff, and Athitsos,  Estimation and prediction of evolving color distributions for skin segmentation under varying illumination, CVPR 2000
  49. Elgammal and Davis, Probabilistic framework for segmenting people under occlusion, ICCV 2001
  50. Rui and Chen, Better proposal distributions:  Object tracking using unscented particle filter, CVPR 2001
  51. Toyama and Blake, Probabilistic Tracking in a Metric Space, ICCV 2001
  52. H. Schneiderman, T. Kanade. A Statistical Method for 3D Object Detection Applied to Faces and Cars, CVPR 2000
  53. Belhumeur, P.N., Hespanha, J.P., Kriegman, D.J., Eigenfaces vs. Fisherfaces: Recognition Using Class-Specific Linear Projection, PAMI(19), No. 7, July 1997, pp. 711-720. 
  54. Veksler, Fast Variable Window for Stereo Correspondence using Integral Images, CVPR 2003
  55. Sullivan, Blake, Isard, and MacCormick, Object Localization by Bayesian Correlation, ICCV 1999
  56. Javed, Shafique, Shah, A hierarchical approach to robust background subtraction using color and gradient information,
  57. Jianbo Shi, Serge Belongie, Thomas Leung, Jitendra Malik, Image And Video Segmentation: The Normalized Cut Framework, ICIP 1998
  58. Boykov, Veksler, Zabih, Markov Random fields with efficient approximations, CVPR 1998
  59. Chafik KERMAD, Christophe COLLEWET, Improving Feature Tracking by Robust Points of Interest Selection,
  60. Torresani and Bregler, Space-time tracking, ECCV 2002


Instructor: Stan Birchfield, 207-A Riggs Hall, 656-5912, email: stb at clemson
Meetings: 3:30-4:30 T, 307 Riggs Hall

To receive the 1-hour credit, students must

One absence is allowed per semester, as well as three late summaries. (The summaries are checked once per week, so three late summaries could be three separate summaries each of which is one week late, or it could be one summary that is three weeks late, or any combination thereof.)  Any delinquencies beyond the allowed amount will result in grade reduction.