Syllabus 146
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EE 146 COMPUTER VISION Department of Electrical & Computer Engineering University of California at Riverside Winter Quarter 2015 Lectures: Tu & Thurs. 12:40 - 2:00 pm, WCH 142 Laboratory: Wed. 8:10 - 11:00 am; 11:10 – 2:00 pm Prerequisite: Senior Standing in EE or CSE or Consent of Instructor Instructor: Bir Bhanu, e-mail: [email protected] Teaching Assistant: Asongu Tambo, e-mail: [email protected] Instructor Office Hours: Tue. 10-11, WCH 216 TA Office Hours: Mon, Tues. (based on input from students in class), Room - EE TA Room WCH 109 Textbook: L. Shapiro and G. Stockman, “Computer Vision,” Prentice Hall 2001. References: 1. M. Sonka, V. Hlavac and R. Boyle, “Image Processing, Analysis, and Machine Vision,” 4 th Edition, Cengage Learning, 2015. 2. T. Svoboda, J. Kybic and V. Hlavac,”Image Processing, Analysis and Machine Vision – A MATLAB Companion, Paperback, Cengage Learning, August 2007. 3. R. Szeliski, “Computer Vision: Algorithms and Applications,” Springer 2010. 4. R. Jain, R. Kasturi and B.G. Schunck, “Machine Vision,” McGraw-Hill, Inc. 1995. 5. R. Haralick and L. Shapiro, “Computer and Robot Vision,” Vol. 1 (1992) and Vol. 2 (1993) Addison Wesley. 6. O. Faugeras, “Three-Dimensional Computer Vision – a Geometric Viewpoint,” MIT Press, 1993. 7. D.A. Forsyth and J. Ponce, “Computer Vision – A Modern Approach,” Prentice Hall 2003. 8. M. Bennamoun and G.J. Mamic, “Object Recognition – Fundamentals and Case Studies,” Springer 2002. 9. W.E.L. Grimson, “Object Recognition by Computer: The Role of Geometric Constraints,” The MIT Press, 1990.
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Syllabus
Transcript of Syllabus 146
EE 146 COMPUTER VISION
Department of Electrical & Computer Engineering University of California at Riverside
Winter Quarter 2015
Lectures: Tu & Thurs. 12:40 - 2:00 pm, WCH 142 Laboratory: Wed. 8:10 - 11:00 am; 11:10 – 2:00 pm Prerequisite: Senior Standing in EE or CSE or Consent of Instructor Instructor: Bir Bhanu, e-mail: [email protected] Teaching Assistant: Asongu Tambo, e-mail: [email protected] Instructor Office Hours: Tue. 10-11, WCH 216 TA Office Hours: Mon, Tues. (based on input from students in class), Room - EE TA Room WCH 109 Textbook: L. Shapiro and G. Stockman, “Computer Vision,” Prentice Hall 2001. References: 1. M. Sonka, V. Hlavac and R. Boyle, “Image Processing, Analysis, and Machine Vision,” 4th
Edition, Cengage Learning, 2015. 2. T. Svoboda, J. Kybic and V. Hlavac,”Image Processing, Analysis and Machine Vision – A
MATLAB Companion, Paperback, Cengage Learning, August 2007. 3. R. Szeliski, “Computer Vision: Algorithms and Applications,” Springer 2010. 4. R. Jain, R. Kasturi and B.G. Schunck, “Machine Vision,” McGraw-Hill, Inc. 1995. 5. R. Haralick and L. Shapiro, “Computer and Robot Vision,” Vol. 1 (1992) and Vol. 2 (1993)
Addison Wesley. 6. O. Faugeras, “Three-Dimensional Computer Vision – a Geometric Viewpoint,” MIT Press,
1993. 7. D.A. Forsyth and J. Ponce, “Computer Vision – A Modern Approach,” Prentice Hall 2003. 8. M. Bennamoun and G.J. Mamic, “Object Recognition – Fundamentals and Case Studies,”
Springer 2002. 9. W.E.L. Grimson, “Object Recognition by Computer: The Role of Geometric Constraints,”
The MIT Press, 1990.
Examination and Grading:
Ten Home works 20% (one every week- Assigned on Tues.) (Your Solution - Typed, no handwritten documents) Ten Labs 20% (Typed, no handwritten documents) (1/2 graded in lab on work done, 1/2 graded on written report) Two Midterms 30% (each 15%) One Final 30% (Comprehensive) Total 100%
Important Dates
Midterm 1 Thursday, January 29, 2015 Midterm 2 Thursday, February 26, 2015 Final Wednesday, March 18, 2015, 8:00 a.m. – 11:00 a.m.
EE 146 COMPUTER VISION Department of Electrical & Computer Engineering
University of California at Riverside Winter 2015
Course Outline
We will cover the first 10 chapters of the book. Jan 6 Chapter 1, 2 Jan 8 Chapter 2, 3, Part Chapter 10 Jan 13, 15, 20 Chapter 3 Jan 22 Chapter 4 Jan 27 Chapter 4 Jan 29, Thursday Midterm 1 Feb 3, 5, 10, 12 Chapter 5 Feb 17 Chapter 6 Feb 19 Chapter 7 Feb 24 Chapter 8 Feb 26, Thursday Midterm 2 March 3, 5 Chapter 9 March 10, 12 Chapter 10 Final Wednesday, March 18, 8:00 a.m. – 11:00 a.m. Holidays Monday Jan 19 (Martin Luther King)
Monday Feb. 16 (President Day)
EE 146 COMPUTER VISION
Department of Electrical & Computer Engineering University of California at Riverside
Winter 2015
Labs
Jan 7 Lab 1: Matlab Image Processing Toolbox, JPEG compression Jan 14 Lab 2: Thresholding for binarization Jan 21 Lab 3: Connected component labeling, region properties Jan 28 Lab 4: Binary image morphology Feb 4 Lab 5: K-NN classification Feb 11 Lab 6: Image filtering, edge detection Feb 18 Lab 7: Gaussian filter, corner detector Feb 25 Lab 8: Color image segmentation using K-means classification Mar 4 Lab 9: Texture (co-occurrence matrices) Mar 11 Lab 10: Change detection, feature correspondence
