ECE 904 Computer Vision Seminar

Fall 2006

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	8/29	Pantelis Elinas, Robert Sim, and James J. Little,  σSLAM: Stereo Vision SLAM Using the Rao-Blackwellised Particle Filter and a Novel Mixture Proposal Distribution,  ICRA 2006.	Stan Birchfield
2	9/5	[STB out of town]
3	9/12	Changjiang Yang, Ramani Duraiswami and Larry Davis, Fast multiple object tracking via hierarchical particle filter, ICCV 2005	Neeraj Kanhere
4	9/19	Ulrich and Nourbakhsh, Appearance based obstacle detection with monocular color vision, AAAI 2000	Shrinivas Pundlik
5	9/26	Fatih Porikli, Road Extraction by Point-wise Gaussian Models, SPIE AeroSense Technologies and Systems for Defense and Security, volume 5093, pages 758--764, 2003.	Guang Zeng
6	10/3	Antonio Criminisi, Geoff Cross, Andrew Blake, and Vladimir Kolmogorov, Bilayer Segmentation of Live Video, CVPR 2006	Shrinivas Pundlik
7	10/10	Andres Bruhn, Joachim Weickert,and Christoph Schnorr, Lucas/Kanade Meets Horn/Schunck: Combining Local and Global Optic Flow Methods, IJCV 61(3):211-231, 2005	Stan Birchfield
8	10/17	M. Agrawal, K. Konolige and L. Iocchi, Real-time detection of independent motion using stereo, IEEE Workshop on Motion and Video Computing (WACV/MOTION'05), vol. 2,  pp. 207-214, 2005	Zhichao Chen
9	10/24	I. Laptev, H. Mayer, T. Lindeberg, W. Eckstein, C. Steger, A. Baumgartner, Automatic extraction of roads from aerial images based on scale space and snakes, Machine Vision and Applications 12:23–31, 2000	Guang Zeng
10	10/31	S. Segvic, A. Remazeilles, and F. Chaumette, Enhancing the point feature tracker by adaptive modelling of the feature support, ECCV 2006	Stan Birchfield
11	11/7	[break]
12	11/14	M. P. Kumar, P. H. S. Torr, and A. Zisserman, Learning Layered Motion Segmentations of Video, ICCV 2005	Neeraj Kanhere
13	11/21	Paul Viola, Michael Jones, Rapid object detection using a boosted cascade of simple features, CVPR 2001	Zhichao Chen
14	11/28	I. Matthews, T. Ishikawa, and S. Baker, The Template Update Problem, BMVC, 2003; Journal version in PAMI, 26(6):810-815, 2004	Stan Birchfield
15	12/5	J. Melo, A. Naftel, A. Bernardino, and J. Santos­Victor, ``Detection and classification of highway lanes using vehicle motion trajectories,'' IEEE Transactions on Intelligent Transportation Systems, 7(2):188-200, 2006.	Stan Birchfield
16

Papers covered in previous semesters

Potential future papers

1. 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
2. Zezhi Chen, Nick Pears and Bojian Liang, Monocular obstacle detection using reciprocal-polar rectification, Image and Vision Computing, 24(12): 1301–1312, 2006
3. 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
4. Sun et al., "Bi-directional Tracking using Trajectory Segment Analysis", ICCV 2005.
5. Chang Huang, Haizhou Ai, Yuan Li, and  Shihong Lao, Vector Boosting for Rotation Invariant Multi-View Face Detection, ICCV 2005, pages 446 - 453
6. F. Porikli, O. Tuzel, and P. Meer, Covariance Tracking using Model Update Based on Lie Algebra, IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), June 2006
7. 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.
8. Jean-Yves Bouguet, Pyramidal Implementation of the Lucas Kanade Feature Tracker
9. Zoran Zivkovic, Ferdinand van der Heijden, Better features to track by estimating the tracking convergence region, ICPR 2002
10. Eric Marchand, Francois Chaumette.  Features Tracking For Visual Servoing Purpose, 2004
11. 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.
12. Alper Yilmaz, Xin Li, and Mubarak Shah, Contour-Based Object Tracking with Occlusion Handling in Video Acquired Using Mobile Cameras, PAMI 26(11), 2004
13. 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.
14. D. Beymer and K. Konolige.  Tracking People from a Mobile Platform.  International Symposium on Experimental Robotics, 2002.
15. P. Felzenszwalb and D. Huttenlocher, Efficient Belief Propagation for Early Vision, CVPR 2004.
16. A.R. Mansouri, “Region tracking via level set PDEs without motion computation,” PAMI, vol. 24, no. 7, pp. 947–961, 2002
17. Yogesh Rathi Namrata Vaswani Allen Tannenbaum Anthony Yezzi, Particle Filtering for Geometric Active Contours with Application to Tracking Moving and Deforming Objects, CVPR 2005
18. 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.
19. Sifakis et al., Video Segmentation Using Fast Marching and Region Growing Algorithms, EURASIP Journal on Applied Signal Processing 2002:4, 379–388
20. 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
21. J. Xiao and M. Shah, Motion layer extraction in the presence of occlusion using graph cut, CVPR 2004
22. 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)
23. A. Barbu, S.C. Zhu, Graph Partition By Swendsen-Wang Cuts, ICCV 2003
24. S. Avidan, Support vector tracking, CVPR 2001
25. Black and Jepson, Eigentracking:  Robust matching and tracking of articulated objects using a view-based representation, IJCV, 26(1), 1998
26. Khan, Balch, Dellaert, A Rao-Blackwellized particle filter for eigentracking, CVPR 2004
27. Freeman and Roth, Orientation histograms for hand gesture recognition, Workshop on AFGR, 1995
28. Perez, Hue, Vermaak, Gangnet, Color-based probabilistic tracking, ECCV 2002
29. Y. Wu, Robust visual tracking by integrating multiple cues based on co-inference learning, IJCV, 58(1), 2004
30. Philomin, Duraiswami, Davis, Quasi-random sampling for condensation, ECCV 2000
31. Brown, Burschka, and Hager, Advances in Computational Stereo, PAMI 2003.
32. Tao Zhang, Daniel Freedman, Tracking Objects using Density Matching and Shape Priors, ICCV 2003
33. Manifold learning web page
34. Belkin, Niyogi, Laplacian eigenmaps for dimensionality reduction and data representation, Neural Comptuation, Vol. 15, Issue 6, June 2003
35. Antonio Torralba Kevin P. Murphy William T. Freeman, Sharing features: efficient boosting procedures for multiclass object detection, CVPR 2004
36. Baker and Matthews, Lucas-Kanade 20 years on:  A unifying framework, IJCV 56(3):221-255, 2004  webpage
37. Molton, Davison, and Reid, Parameterisation and probability in image alignment, ACCV 2004.
38. A. Davison, "3D Simultaneous Localisation and Map-Building Using Active Vision for a Robot Moving on Undulating Terrain", CVPR 2001
39. Yann, LeNet-5 convolutional neural networks -- homepage
40. Kass, Witkin, and Terzopoulos, Snakes:  Active Contour Models, ICCV 1987
41. Plumpe et al., Modeling of the Glottal Flow Derivative Waveform with Application to Speaker Identification, IEEE Transactions on speech and audio processing, 7(5), Sept. 1999
42. Grimson et al., Using adaptive tracking to classify and monitor activities in a site, CVPR 1998
43. 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.
44. Morency, Rahimi, Darrell, Adaptive View-based Appearance Model, CVPR, 2003
45. M. Irani, Multi-Frame Optical Flow Estimation Using Subspace Constraints, ICCV 1999
46. Wu and Huang,  A Co-inference Approach to Robust Visual Tracking
47. Sigal, Sclaroff, and Athitsos,  Estimation and prediction of evolving color distributions for skin segmentation under varying illumination, CVPR 2000
48. Choo and Fleet.  People tracking using hybrid Monte Carlo filtering, ICCV 2001
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

Administrivia

Instructor: Stan Birchfield, 207-A Riggs Hall, 656-5912, email: stb at clemson
Meetings: 3:30 - 4:30 pm Tuesdays, 301 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.)