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  • CMPEN/EE 455 Digital Image Processing

  •    Introduction to Digital Image Processing
    Dr. Robert Collins
    Fall 2011, Fall 2012
  • CMPEN/EE 454 Computer Vision I

  •    Introduction to Computer Vision
    Dr. Robert Collins
    Fall 2007, Fall 2008, Fall 2009, Fall 2010
  • CMPSC 458 Fundamentals of Computer Graphics

  •   Fundamentals of computer graphics; approaches and mathematical techniques that allow a computer to digitally render a scene, advanced methods of image analysis yielding more realistic textures and environments. Topics include transformation, projection, illumination models, shading, hidden lines/surface elimination, viewing, color, raytracing, physics-base graphics, and IRB, in particular image-based texture synthesis.
      Spring 09 Highlights   Fall 09 Highlights   Fall 15 Highlights
    Dr. Yanxi Liu
    Spring 2007, Spring 2008, Spring 2009, Fall 2009, Fall 2010, Fall 2011, Fall 2012, Fall 2014, Fall 2015
    Graduate Level Courses
  • CSE 583 Pattern Recognition and Artificial Intelligence

  •   Decision-theoretic classification, discriminant functions, pattern processing and feature selection, syntactic pattern recognition, shape analysis and recognition.
    Dr. Yanxi Liu
    Fall 2008, Fall 2009, Spring 2011, Spring 2012, Spring 2013, Spring 2015, Spring 2016
  • CSE 586/EE 554 Topics in Computer Vision

  •   Mathematical Tools for Computer Vision
    Dr. Robert Collins
    Spring 2010, Spring 2011, Spring 2012, Spring 2013
  • CSE 598C Vision-Based Tracking

  •   Detecting and Tracking Moving Objects in Video
    Dr. Robert Collins
    Spring 2006, Fall 2010, Fall 2012
  • CSE 598D Computational Regularity on Interdisciplinary, Large Data Sets

  •   This is a course on computational methods from real world digital data, across scale, modality and application domains, for pattern discovery, comparison and learning. The content is based on a unique combination of group theory, statistical learning theory, and human/animal perception, with an emphasis on discovering visually appealing patterns automatically and hands-on trainings on large data sets.
    Dr. Yanxi Liu
    Fall 2012
  • CSE 598G Computational Regularity

  •   This is a course on computational methods for real applications, based on a unique combination of group theory, pattern theory, statistical learning theory and human/animal/machine perception models.
    Dr. Yanxi Liu
    Fall 2011
  • CSE 597F Computational Photography

  •   Computational photography combines elements of optics, graphics, and computer vision to enhance or extend the capabilities of digital photography.
    Dr. Robert Collins, Dr. David Capel and Dr. Yanxi Liu
    Spring 2010
  • CSE 598E Machine Learning for Computational Regularity

  •   Symmetry perception and saliency detection, regularity-based segmentation, and group theory.
    Dr. Yanxi Liu
    Fall 2009
  • CSE 597E Visual Salience Seminar

  •   What Captures our Attention, and Why?
    Dr. Robert Collins
    Spring 2007
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