. CSE397-011/497-011 Real-time Image Processing for Autonomous Robot Systems TR 7:55-9:10 PM, Fall 2006

• 18 Dec 06:  We had a thrilling finish to the RIP Grand Challenge, with all teams completing the course using strictly vision for feedback.  Great job Everyone!  Results and videos for the teams are as follows.  
• First Place:  Team Aether   divx  wmv  (2:32)  and with obstacle avoidance   divx  wmv
• Second Place:  Team 1  divx  wmv (2:38)
• Third Place (tied):  Team 2   divx  wmv  / Team Chuck Norris  divx (2:44) 
• 08 Dec 06:  The grand challenge will be held at 0800 on Monday, 8 Dec.  This is the date of the regularly scheduled final and will ensure that there are no scheduling conflicts.
• 21 Nov 06:  Graduate student presentation start today!  
• 12 Nov 06:  Lab 7 is due 21 Nov 06.  
• 06 Nov 06:  Homework 4 is posted!  
• 02 Nov 06:  ATTENTION GRADUATE STUDENTS:  The presentation schedule is posted.  This is ~20% of your grade, so let's get moving!
• 31 Oct 06:  Happy Halloween!  The RIP06 Grand Challenge Rules are posted here!
• 24 Oct 06:  We will be meeting for lab this Thursday in PL322.
• 19 Oct 06:  The remainder of the course syllabus is posted, FYI.  This is more or less how we will finish out the semester.  
• 18 Oct 06:  Homework 3 is posted.  It is due 31 Oct 06 prior to the start of class.  
• 16 Oct 06:  Calibration lab tomorrow in PL322.  The report portion of this is an indvidual assignment. 
• 25 Sep 06:  We will be having lab tomorrow in PL 322
• 20 Sep 06:  Homework 2 is posted.  It is due on 28 Sep 06 before class.  Do NOT work together on this homework!  
• 18 Sep 06:  There will NOT be a lab this week.  The next lab will be on Tuesday, 26 Sep 06  
• 11 Sep 06:  As part of my effort to give you a higher value education, I've assigned a bonus homework that is due on 19 Sep 06 BEFORE the start of class.  This is an individual assignment.  Do NOT work together on this.     
• 11 Sep 06:  Reminder that your labs are due this Thursday, 14 Sep 06 BEFORE the start of class.  Submissions are via blackboard.  I want a single file (no source code).  
• 06 Sep 06:  First lab will be tomorrow.  We will meet in PL322 at 0755
• 29 Aug 06:  First day of classes.  Welcome!

The Mars Exploration Rover (MER) employs no less than 8 cameras for sensing its environment.  Cameras are a popular choice for robot sensing as they are compact, passive, require little power, and are a natural medium for human/robot interaction.  This course will explore fundamental image processing and computer vision algorithms for autonomous robot operations, with additional applications to autonomous surveillance.  In addition to lectures, classroom time will include laboratory sessions where algorithms will be implemented on camera and/or robot vision systems.     

Topics will include (among others):

• Image formation
• Filtering Operations
  
• Point operations
• Feature Detection (colors, edges, corners, etc.)
• Geometric Transformations
  
• Pyramids
• Image warping and alignment
• Motion Dectection/Estimation
• Target tracking
  

• Math 23 Analytic Geometry and Calculus III or equivalent
• Math 205 Linear Methods or equivalent or equivalent
• CSE 109 Systems Programming or equivalent programming experience in C/C++

1. HyperMedia Image Processing Reference
   
2. CVOnline
3. Computer Vision Home Page
4. OpenCV - Intel's Open Source Computer Vision Library
   
5. Random Sample Consensus (RANSAC)
1. A one page summary from CVOnline
2. The original paper (15 pages - you can only access this from the Lehigh server)
6. The University of Leeds Vision Group Calibration Page.  This covers Tsai's method, and includes a link to a related paper by Horn.
7. Caltech's Matlab Calibration Toolbox
8. An INRIA paper on real-time correlation based stereo by Faugeras et al
9. The Middlebury Stereo Vision Research Page has resources for regarding steropsis.
10. Pyramids:
• Adelson et al, "Pyramid Methods in Image Processing"
• Burt et al, "The Laplacian Pyramid as Compact Image Code"
  
• R. Szeliski, ""Image Moasicing for Tele-Reality Applications"
  

• Laboratory assignments/reports:  60%
• RIP Grand Challenge:  20%
• Lecture attendance/participation - particularly for the paper presentations (undergrad):  20%
• Paper presentation (graduate credit):  20%