ECE 893-5 Computer Vision Seminar
Spring 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

1/11

Intro / overview

Stan Birchfield

2

1/18

 N. K. Kanhere, S. J. Pundlik, and S. T. Birchfield, Vehicle Segmentation and Tracking from a Low-Angle Off-Axis Camera, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), San Diego, California, June 2005   Neeraj Kanhere

3

1/25

 W.E.L. Grimson,C. Stauffer, R. Romano, L. Lee, Using adaptive tracking to classify and monitor activities in a site, CVPR 1998 Nikhil Rane
(slides)

4

2/1

 Nikos Paragios and Rachid Deriche, Geodesic Active Contours and Level Sets for the Detection and Tracking of Moving Objects, PAMI, 22(3):266-280, March 2000 Shrinivas Pundlik

5

2/8

 Horprasert, Harwood, Davis, A robust background subtraction and shadow detection, ACCV 2000 Joshua Hughes

6

2/15

 Hammadi Nait-Charif & Stephen J. McKenna, Head Tracking and Action Recognition in a Smart Meeting Room, PETS 2003 Nikhil Rane
(slides)

7

2/22

 Louka Dlagnekov and Serge Belongie, Recognizing Cars, UCSD CSE Tech Report CS2005-0833 Akshay Katrekar

8

3/1

 Etienne Grossmann, Amit Kale, Christopher Jaynes, Towards Interactive Generation of "Ground Truth" in Background Subtraction from Partially Labeled Examples, Proceedings of the IEEE Workshop on Visual Surveillance and Performance Evaluation of Tracking and Surveillance, Beijing China, October 2005. Guang Zeng

9

3/8

 Ahmed Elgammal, David Harwood, Larry Davis, Non-parametric Model for Background Subtraction. ECCV, 2000 Prashant Oswal

10

3/15

 Hwann-Tzong Chen, Tyng-Luh Liu. Real-time tracking using trust-region methods. IEEE Transactions on Pattern Analysis and Machine Intelligence, 26(3): 397-402, 2004. Zhichao Chen

11

3/22

 [break]  

12

3/29

 H. Schneiderman, T. Kanade. A Statistical Method for 3D Object Detection Applied to Faces and Cars, CVPR 2000. Ronnie Dasgupta

13

4/5

 Sivic, J. , Schaffalitzky, F. and Zisserman, A. Object Level Grouping for Video Shots Proceedings of the 8th European Conference on Computer Vision (ECCV), Prague, Czech Republic, 2004 Thomas Polon

14

4/12

 Mike Montemerlo, Perspectives on Autonomous Desert Driving (talk on DARPA Grand Challenge), Part I  
15 4/19 Mike Montemerlo, Perspectives on Autonomous Desert Driving (talk on DARPA Grand Challenge), Part II  

16

 4/26 Z. Chen and S. Birchfield, Qualitative Vision-Based Mobile Robot Navigation, ICRA 2006. Zhichao Chen

Papers covered in previous semesters


Potential future papers

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

Administrivia

Instructor: Stan Birchfield, 207-A Riggs Hall, 656-5912, email: stb at clemson
Meetings: 4 - 5 pm Wednesdays, 303D 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.)