Web references:

 

DARPA Grand Challenge:

http://en.wikipedia.org/wiki/Darpa_grand_challenge

http://www.darpa.mil/grandchallenge/index.asp

 

History of autonomous vehicles:

http://www.idsia.ch/~juergen/robotcars.html

 

Introduction to robot mapping with statistics:

http://www.cs.washington.edu/homes/fox/ecai-tutorial/ecai-02.htm

 

Computer Vision and Stat by Yuille

http://www.stat.ucla.edu/~yuille/courses/Stat238/

 

Lecture Notes on Probability and Statistics by D. C. Agnew and C. Constable

http://mahi.ucsd.edu/cathy/Classes/SIO223/Part1/

 

Robots Incorporated

http://www.spectrum.ieee.org/aug07/5391

 

PBS did a NOVA show on the race and showed it on TV
http://www.pbs.org/wgbh/nova/darpa/program.html

 

 

Course Topics:

Shape similarity [12, 13]

Image Segmentation with EM (Chapter 16 in Forsyth and Ponce book) and [9]

Range data analysis (Chapter 21 in Forsyth and Ponce book)

Markov Random Fields (tutorial by C. Bouman)

Conditional Random Fields (chapter by C. Sutton and A. McCallum)

Contour grouping [11,17]

Contour grouping with Multiscale Random Fields

Contour grouping with particle filters [15]

Visual SLAM [16]

Contour Extraction with Particles [15]

Semi-Supervised Learning [18]

Bayesian Classifier

Object Perception as Bayesian Inference [10, 14]

Diffusion Maps [19]

Singular Value Decomposition [20, 21]

 

Books:

 

Christopher M. Bishop. Pattern Recognition and Machine Learning. Springer 2006. book website

David A. Forsyth and Jean Ponce . Computer Vision: A Modern Approach. Prentice Hall 2003.  website

Richard O. Duda, Peter E. Hart, and David G. Stork. Pattern Classification. (2nd ed.), Wiley 2000. website

 

Papers related to Robot Mapping:

[1]   Sebastian Thrun et al., Stanley: The Robot that Won the DARPA Grand Challenge. Journal of Field Robotics 23(9), 661–692, 2006. pdf

[2]   Ernst D. Dickmanns. Vehicles Capable of Dynamic Vision. IJCAI 1997. pdf

[3]   Pierre Lamon, et al. Mapping with an Autonomous Car. In Proc. of the Workshop on Safe Navigation in Open and Dynamic Environments at the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS), Beijing, China, 2006. paper

[4]   Giorgio Grisetti, Cyrill Stachniss, and Wolfram Burgard. Improved Techniques for Grid Mapping with Rao-Blackwellized Particle Filters. Transactions on Robotics, Volume 23, pages 34-46, 2007 paper

[5]   Dieter Fox. Adapting the Sample Size in Particle Filters Through KLD-Sampling. IJRR 2003. pdf

Papers on Particle Filters:

[6]   Dieter Fox, Jeffrey Hightower, Lin Liao, Dirk Schulz, Gaetano Borriello. Bayesian Filters for Location Estimation. PERVASIVE Computing, July-September 2003. pdf

[7]   CHRISTOPHE ANDRIEU, NANDO DE FREITAS, ARNAUD DOUCET, MICHAEL I. JORDAN. An Introduction to MCMC for Machine Learning. Machine Learning 50, 5-43, 2003. pdf

[8]   M. Sanjeev Arulampalam, Simon Maskell, Neil Gordon, and Tim Clapp. A Tutorial on Particle Filters for Online Nonlinear/Non-Gaussian Bayesian Tracking. IEEE Trans. on SIGNAL PROCESSING, VOL. 50, NO. 2, 2002. pdf

 

Papers related to Image and Object Recognition:

[9]   Nuno Vasconcelos. From Pixels to Semantic Spaces: Advances in Content-Based Image Retrieval. IEEE Computer, July 2007. pdf

[10]  D. Kersten, P. Mamassian, and A.L. Yuille. Object Perception as Bayesian Inference. Annual Review of Psychology, 2003. pdf

[11]   V. Ferrari, F. Jurie, and C. Schmid, Accurate object detection with deformable shape models learnt from images, CVPR, June 2007. pdf TRpdf

[12]   G. McNeill and S. Vijayakumar. Part-based Probabilistic Point Matching using Equivalence Constraints. NIPS 2006. pdf

[13]    Pedro Felzenszwalb and Joshua Schwartz. Hierarchical Matching of Deformable Shapes. CVPR 2007. pdf

[14]    J. SULLIVAN, A. BLAKE, M. ISARD, AND J. MACCORMICK. Bayesian Object Localisation in Images. Int. Journal of Computer Vision 44(2), 111–135, 2001. pdf

[15]     Patrick Perez, Andrew Blake, Michel Gangnet. JetStream: Probabilistic Contour Extraction with Particles, ICCV 2001 (II: 524-531). pdf

[16]     Mark Cummins and Paul Newman. Accelerated Appearance-Only SLAM. ICRA Pasadena, 2008. pdf

[17]      Y. Chen, C. Lin, L. Zhu, A. Yuille, H. Zhang. Rapid Inference on a Novel AND/OR graph for Object Detection, Segmentation and Parsing. NIPS 2007. pdf

[18]       Zhu, X., Ghahramani, Z., Lafferty., J.: Semi-supervised learning using Gaussian fields and harmonic functions. In: ICML. (2003) pdf

[19]  Ronald R. Coifman and Stéphane Lafon. Diffusion maps. Appl. Comput. Harmon. Anal. 21 (2006) 5–30. pdf

[20]  Emmett J. Ientilucci. Using the Singular Value Decomposition. Report RIT 2003. pdf

[21]  Colm Mulcahy and John Rossi. A Fresh Approach to the Singular Value Decomposition The College Mathematics Journal, 29(3), pp. 199-207, 1998. pdf