CS-598 MAAV - Lecture materials

Lecture materials and resources here.

Texts:

Week Starting Topic Reading Materials Movie List
26 Aug Administration Nothing so far! Nothing so far!
26 Aug Intellectual Context Nothing so far! Here is an intro lecture, with some remarks about safety.
26 Aug Basic Convolutional Neural Networks
  • Deep nets: Units; AML: 16.1
  • Deep nets: Gradients; AML: 16.2
  • Deep nets: Backpropagation; AML 16.3
  • Deep nets: Gradient tricks; AML 16.4
  • Deep nets: Convolutional layers; AML 17.1
  • Deep nets: More on convolutional layers; AML 17.1, 17.2
31 Aug Image classification and simple detection
7 Sep Safety lookout training No reading
7 Sep Simple PID Control My PID control slides
14 Sep ROS and PACMOD and Registration
21 Sep Kalman and Particle Filters
28 Sep Finish Particle Filters; Cameras and pairs of cameras
9 Oct Finish pairs of cameras; flow and stereo; SFM, SLAM and visual odometry
  • Slides on pairs of cameras (slightly revised)
  • Multiple View Geometry in Computer Vision Second Edition Richard Hartley and Andrew Zisserman, Cambridge University Press, March 2004.
  • Y. Boykov, O. Veksler and R. Zabih (2001), "Fast approximate energy minimisation via graph cuts", IEEE Transactions on Pattern Analysis and Machine Intelligence, 29, 1222–1239.
  • Li Hong and G. Chen, "Segment-based stereo matching using graph cuts," Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004., Washington, DC, USA, 2004, pp. I-I, doi: 10.1109/CVPR.2004.1315016.
  • R. Szeliski et al., "A Comparative Study of Energy Minimization Methods for Markov Random Fields with Smoothness-Based Priors," in IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 30, no. 6, pp. 1068-1080, June 2008, doi: 10.1109/TPAMI.2007.70844.
  • T. Brox, C. Bregler and J. Malik, "Large displacement optical flow", CVPR 2009
  • High Accuracy Optical Flow Estimation Based on a Theory for Warping, Thomas Brox, Andr´es Bruhn, Nils Papenberg, and Joachim Weickert, ECCV, 2004
  • My slides on very simplest SFM and SLAM
  • My slides on basic visual odometry
  • Tutorial on visual slam at CVPR2014

    I found the following particularly helpful

16 Oct EKFSLAM, FastSLAM, Direct methods
  • Slides on EKF SLAM
  • Slides on FastSLAM
  • Slides on Features and Interest points
  • Slides on Direct SLAM
  • Great notes on EKF-SLAM by Joan Sola, with Matlab code, etc
  • Slides from Ben Kuipers on FastSLAM
  • Slides from Burgard et al on FastSLAM
  • FastSLAM: A Factored Solution to the Simultaneous Localization and Mapping Problem Michael Montemerlo and Sebastian Thrun and Daphne Koller and Ben Wegbreit AAAI 02
  • FastSLAM 2.0: an improved particle filtering algorithm for simultaneous localization and mapping that provably converges Michael Steven Montemerlo and Sebastian B Thrun and Daphne Koller and Ben Wegbreit IJCAI -03
  • lsdSLAM website - there is a pointer to a github site with code here.
  • SVO (fast semi-direct visual odometry) there is a pointer to code here, too.
  • Christian Forster, Zichao Zhang, Michael Gassner, Manuel Werlberger, Davide Scaramuzza SVO: Semi-Direct Visual Odometry for Monocular and Multi-Camera Systems IEEE Transactions on Robotics, Vol. 33, Issue 2, pages 249-265, Apr. 2017.
  • Dense visual slam an earlier version of lsd-slam for RGB-D cameras, code too
  • Dense Visual SLAM for RGB-D Cameras (C. Kerl, J. Sturm and D. Cremers), In Proc. of the Int. Conf. on Intelligent Robot Systems (IROS), 2013.
23 Oct Fall viruses and Semantic Segmentation