ECE 904 Computer Vision Seminar

Fall 2007

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.

Schedule

Week	Date	Paper	Discussion leader
1	8/27	D. Marr and T. Poggio, Cooperative Computation of Stereo Disparity, Science, v. 194, pp. 283-287, Oct. 1976	Stan Birchfield
2	9/3	[break]
3	9/10	Thomas B. Sebastian, Philip N. Klein and Benjamin B. Kimia, On Aligning Curves, PAMI, Vol. 25, No. 1, January 2003	Neeraj Kanhere
4	9/17	Josh Wills, Sameer Agarwal, and Serge Belongie, A feature based approach for dense segmentation and estimation of large disparity motion, IJCV 2006	Shrinivas Pundlik
5	9/24	K. Choo and D. J. Fleet,  People tracking using hybrid Monte Carlo filtering, ICCV 2001	Kenneth Rice
6	10/1	O. Jenkins and M. Mataric, A Spatio-temporal Extension to Isomap Nonlinear Dimension Reduction. Proceedings of the Twenty-First International Conference on Machine Learning (ICML-2004), July 4-8, 2004, Banff, Alberta, Canada	Nikhil Rane
7	10/8	M. Plumpe, T. Quatier, and D. Reynolds, Modeling of the Glottal Flow Derivative Waveform with Application to Speaker Identification, IEEE Trans. on Speech and Audio Processing, 7(5), 1999	Trupti Patil
8	10/15	[break]
9	10/22	D. Zhang, W. Kong, J. You and M. Wong, Online Palmprint Identification, IEEE Transactions on Pattern Analysis and Machine Intelligence, 25(9):1041-1050, Sept. 2003	Guang Zeng
10	10/29	T. Brox, A. Bruhn, N. Papenberg, J. Weickert, High Accuracy Optical Flow Estimation Based on a Theory for Warping, In Proc. 8th European Conference on Computer Vision (ECCV), vol 4, pp.25-36, May 2004	Vidya Murali
11	11/5	[canceled]
12	11/12	Z. Chen and S. T. Birchfield, Person Following with a Mobile Robot Using Binocular Feature-Based Tracking, Proceedings of the IEEE International Conference on Intelligent Robots and Systems (IROS), San Diego, California, October 2007	Zhichao Chen
13	11/19	Huang, K., Wang, L., Tan, T., and Maybank, S. A real-time object detecting and tracking system for outdoor night surveillance. Pattern Recogn. 41(1):432-444,  Jan. 2008.	Yingyun Mao
14	11/26	Steven Mills, Kevin Novins, Motion Segmentation in Long Image Sequences, British Machine Vision Conference (BMVC) pages 162-171, 2000	Trupti Patil
15	12/3	J. Sun et al., Low resolution character recognition by dual eigenspace and synthetic degraded patterns, Proceeding of the 1st ACM workshop on hardcopy document processing, Washington, DC, pp.15-22, November 2004	Kenneth Rice

Papers covered in previous semesters

Potential future papers

1. 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
2. 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
3. Zezhi Chen, Nick Pears and Bojian Liang, Monocular obstacle detection using reciprocal-polar rectification, Image and Vision Computing, 24(12): 1301–1312, 2006
4. 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
5. Sun et al., "Bi-directional Tracking using Trajectory Segment Analysis", ICCV 2005.
6. 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.
7. Jean-Yves Bouguet, Pyramidal Implementation of the Lucas Kanade Feature Tracker
8. Zoran Zivkovic, Ferdinand van der Heijden, Better features to track by estimating the tracking convergence region, ICPR 2002
9. Eric Marchand, Francois Chaumette.  Features Tracking For Visual Servoing Purpose, 2004
10. 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.
11. Alper Yilmaz, Xin Li, and Mubarak Shah, Contour-Based Object Tracking with Occlusion Handling in Video Acquired Using Mobile Cameras, PAMI 26(11), 2004
12. 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.
13. D. Beymer and K. Konolige.  Tracking People from a Mobile Platform.  International Symposium on Experimental Robotics, 2002.
14. P. Felzenszwalb and D. Huttenlocher, Efficient Belief Propagation for Early Vision, CVPR 2004.
15. A.R. Mansouri, “Region tracking via level set PDEs without motion computation,” PAMI, vol. 24, no. 7, pp. 947–961, 2002
16. Yogesh Rathi Namrata Vaswani Allen Tannenbaum Anthony Yezzi, Particle Filtering for Geometric Active Contours with Application to Tracking Moving and Deforming Objects, CVPR 2005
17. 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.
18. Sifakis et al., Video Segmentation Using Fast Marching and Region Growing Algorithms, EURASIP Journal on Applied Signal Processing 2002:4, 379–388
19. 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
20. J. Xiao and M. Shah, Motion layer extraction in the presence of occlusion using graph cut, CVPR 2004
21. 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)
22. A. Barbu, S.C. Zhu, Graph Partition By Swendsen-Wang Cuts, ICCV 2003
23. S. Avidan, Support vector tracking, CVPR 2001
24. Black and Jepson, Eigentracking:  Robust matching and tracking of articulated objects using a view-based representation, IJCV, 26(1), 1998
25. Khan, Balch, Dellaert, A Rao-Blackwellized particle filter for eigentracking, CVPR 2004
26. Freeman and Roth, Orientation histograms for hand gesture recognition, Workshop on AFGR, 1995
27. Perez, Hue, Vermaak, Gangnet, Color-based probabilistic tracking, ECCV 2002
28. Y. Wu, Robust visual tracking by integrating multiple cues based on co-inference learning, IJCV, 58(1), 2004
29. Philomin, Duraiswami, Davis, Quasi-random sampling for condensation, ECCV 2000
30. Brown, Burschka, and Hager, Advances in Computational Stereo, PAMI 2003.
31. Tao Zhang, Daniel Freedman, Tracking Objects using Density Matching and Shape Priors, ICCV 2003
32. Manifold learning web page
33. Belkin, Niyogi, Laplacian eigenmaps for dimensionality reduction and data representation, Neural Comptuation, Vol. 15, Issue 6, June 2003
34. Antonio Torralba Kevin P. Murphy William T. Freeman, Sharing features: efficient boosting procedures for multiclass object detection, CVPR 2004
35. Baker and Matthews, Lucas-Kanade 20 years on:  A unifying framework, IJCV 56(3):221-255, 2004  webpage
36. Molton, Davison, and Reid, Parameterisation and probability in image alignment, ACCV 2004.
37. A. Davison, "3D Simultaneous Localisation and Map-Building Using Active Vision for a Robot Moving on Undulating Terrain", CVPR 2001
38. Yann, LeNet-5 convolutional neural networks -- homepage
39. Kass, Witkin, and Terzopoulos, Snakes:  Active Contour Models, ICCV 1987
40. Grimson et al., Using adaptive tracking to classify and monitor activities in a site, CVPR 1998
41. 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.
42. Morency, Rahimi, Darrell, Adaptive View-based Appearance Model, CVPR, 2003
43. M. Irani, Multi-Frame Optical Flow Estimation Using Subspace Constraints, ICCV 1999
44. Wu and Huang,  A Co-inference Approach to Robust Visual Tracking
45. Sigal, Sclaroff, and Athitsos,  Estimation and prediction of evolving color distributions for skin segmentation under varying illumination, CVPR 2000
46. Elgammal and Davis, Probabilistic framework for segmenting people under occlusion, ICCV 2001
47. Rui and Chen, Better proposal distributions:  Object tracking using unscented particle filter, CVPR 2001
48. Toyama and Blake, Probabilistic Tracking in a Metric Space, ICCV 2001
49. H. Schneiderman, T. Kanade. A Statistical Method for 3D Object Detection Applied to Faces and Cars, CVPR 2000
50. 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. 
51. Veksler, Fast Variable Window for Stereo Correspondence using Integral Images, CVPR 2003
52. Sullivan, Blake, Isard, and MacCormick, Object Localization by Bayesian Correlation, ICCV 1999
53. Javed, Shafique, Shah, A hierarchical approach to robust background subtraction using color and gradient information,
54. Jianbo Shi, Serge Belongie, Thomas Leung, Jitendra Malik, Image And Video Segmentation: The Normalized Cut Framework, ICIP 1998
55. Boykov, Veksler, Zabih, Markov Random fields with efficient approximations, CVPR 1998
56. Chafik KERMAD, Christophe COLLEWET, Improving Feature Tracking by Robust Points of Interest Selection,
57. Torresani and Bregler, Space-time tracking, ECCV 2002

Administrivia

Instructor: Stan Birchfield, 207-A Riggs Hall, 656-5912, email: stb at clemson
Meetings: 3:35-4:35 M, 226 Riggs Hall

To receive the 1-hour credit, students must

• sign up for the course at the beginning of the semester
• attend each week
• write a brief summary of each paper covered (five sentences minimum), answering
  • What did the authors do?
  • What are the strengths / weaknesses / potential improvements?
Summaries should be turned in via email to the instructor with a subject line of
    Paper summary: Author
where Author is replaced by the name of the first author of the paper. Non-conforming emails will be returned.  Summaries are due 15 minutes before the beginning of the seminar.
• lead the discussion at least twice during the semester. You may select a paper either from the suggested list above or you may find one yourself. Either way, you should notify the instructor and get approval of the paper at least one week before your presentation.
  (Note:  A paper summary is not required for the week that you lead the discussion.)