Course Description:
40-712+ provides an insight to the fundamental theory and techniques for efficient representation and processing of video signals. Topics to be covered include: video formation and representation, Fourier analysis of video signals, properties of the human visual system, video sampling, video sampling rate conversion, video modeling, motion estimation, video segmentation, motion tracking, fundamentals of video compression techniques, stereo and multiview sequence processing, video compression standards, error control in video communications, and streaming video over the Internet and wireless networks. Additional topics may be included. A term-project is also required.

Prerequisites:
40-823 (Advanced Image Processing) or 40-933 (Digital Image Processing).

Credit:
3 units.

Course Schedule:
TBA


Website:
The course website can be found at CW.
Please check this site often for important announcements, files needed for computer exercises, and the PDF versions of handouts & homework.

Main Text Book:
Video Processing & Communications, by Yao Wang, Jom Ostermann, & Ya-Oin Zhang. Prentice Hall, 1st edition, 2001, ISBN: 0130175471. [SUT: TK 5105 .2 .W362001] Additional topics will be included.

Homework Policy:
Homework problems will be assigned during the course and solution provided. Some homework assignments will require programming and testing. Programming assignments can be submitted either in Matlab or C Languages.

Course Project:
There will be a course project, which can also be proposed by the student. Students are supposed to present the final result, associated with related software & technical report.

Grading Policy:
Written & programming assignments: 3 Points
Project: 3 Points
Project report: 1 Point
Project presentation: 1 Point
Midterm exam: 3 Points
Final exam: 9 Points
Class activities: 1 Point

Reference Books:

1. The Essential Guide to Video Processing, by Alan C. Bovik, Academic Press Elsevier Inc., 2009, ISBN: 978-0-12-374456-2.Digital Video Processing, by A. Murat Tekalp, Prentice Hall, 1995, ISBN: 0-13-190075-7.
2. Digital Video Processing, by A. Murat Tekalp, Prentice Hall, 1995, ISBN: 0-13-190075-7.
3. Image and Video Compression for Multimedia Engineering: Fundamentals, Algorithms, and Standards, by Yun Q. Shi & Huifang Sun. CRC Press, 2000, ISBN: 0-8493-3491-8. [SUT: QA 76 .575 .S555 1999 C.2] 3: Fundamentals of Digital Image Processing, by Anil K. Jain, Prentice Hall, 1989, ISBN: 0013-336165-9.
4. Digital Image Processing, by Rafael C. Gonzalez & Richard E. Woods, Addison-Wesley, 2nd edition, 2002.
5. Video Engineering, by Inglis & Luther, 2nd edition, McGraw Hill, 1996. (covers fundamentals of analog & digital video systems, including HDTV, CATV, terrestial & satellite video broadcast technologies.) [SUT: TK 6630 .I54 1996]
6. Video Dialtone Technology, by Minoli, McGraw Hill, 1995. (covers digital video over ADSL, HFC, FTTC & ATM technologies, including interactive TV & video-on-demand.)
7. Handbook of Image & Video Processing, by Al Bovik, Academic Press, 2000, ISBN: 0121197905. [SUT: TA 1637 . H26 2000]
8. Digital Video Compression (with CD-ROM), by Peter Symes. Bk &CD-Rom edition, 2003, ISBN: 0071424873.
9. H.264 and MPEG-4 Video Compression: Video Coding for Next Generation Multimedia, by Iain E. G. Richardson & Iain E. G. Richardson. John Wiley & Sons, 12, 2003, ISBN: 0470848375.
10. Multidimensional Digital Signal Processing, by Dan E. Dudgeon & Russel M. Mersereau, Prentice-Hall, 1984.
11. Computer & Robot Vision, by Robert M. Haralick & Linda G. Shapiro, Addison-Wesley, 1993.
12. Computer Vision, by Dana H. Ballard & Christopher M. Brown, Prentice-Hall, 1982.
13. Handbook of Pattern Recognition & Image Processing, by Tzay Y. Young & King-Sun Fu, Academic Press, 1986.
14. A Wavelet Tour on Signal Processing, by Stephane Mallat, Academic Press, 2nd edition, 1999, ISBN: 0-12-466606-X.
15. Wavelets and Subband Coding, by Martine Vetterli & Jelena Kovacevic, Prentice Hall, 1995, ISBN: 0-13-097080-8.
16. Probability, Random Variables, & Random Signal Principles, by Peyton Z. Peebles, JR., McGraw-Hill, 3rd edition, 1993, ISBN:0-07-112782-8.
17. Probability, Random Variables, & Stochastic Processes, by Athanasios Papoulis, McGraw-Hill, 1991 [SUT: QA 273 .P2 199].

Course Description:
40-933+ provides an insight to image processing theory and techniques. Topics include: 2D signals & systems, 2D random processing, image perception & formation, color image processing, image sampling & quantization, image transforms, image enhancement, image filtering & restoration (Wiener filtering), image analysis (edge detection, region representation, scene matching, image segmentation, image classification, morphological filtering, Hough transform), image data compression (predictive, transform, Huffman, and arithmetic coding), and deep learning in image processing.

Prerequisites:
40-763 (Digital Signal Processing) or 40-933 (Digital Image Processing).

Credit:
3 units.

Course Schedule:
TBA

Website:
The course website can be found at CW.
Please check this site often for important announcements, files needed for computer exercises, and the PDF versions of handouts & homework.

Main Text Book:
Fundamentals of Digital Image Processing, by Anil K. Jain, Prentice Hall, 1989, ISBN: 0013-336165-9. Additional topics will be included (e.g., video compression standards, wavelet transform).

Homework Policy:
Homework problems will be assigned during the course and solution provided. Some homework assignments will require programming and testing. Programming assignments can be submitted either in Matlab or C Languages.

Course Project:
There will be a course project/contest. Students are supposed to present the final result and deliver the related software & technical report.

Grading Policy:
Quizzes: 2 Points
Written & Programming Assignments: 3 Points
Final Project/contest: 3 Points
Project Report: .5 Points
Project Presentation: .5 Points
Class Activities: 1 Point


Reference Books:

1. Computer Imaging: Digital Image Analysis and Processing, by Scott E. Umbaugh, CRC Press, 2005, ISBN: 0-8493-2919-1.
2. Digital Image Processing, by Rafael C. Gonzalez & Richard E. Woods, Addison-Wesley, Addison-Wesley, 3rd edition, 2008, ISBN: 0-13-168728-x.
3. Digital Image Processing using Matlab, by Rafael C. Gonzalez, Richard E. Woods, & Stevev L. Eddins, Prentice-Hall, 1st edition, 2003, ISBN: 0130085197.
4. Digital Image Processing, by Kenneth R. Castelman, Prentice-Hall, 1996.
5. Algorithms for Image Processing and Computer Vision, by J.R. Parker, John Wiley & Sons, 1996, ISBN: 0471140562.
6. Multidimensional Digital Signal Processing, by Dan E. Dudgeon & Russel M. Mersereau, Prentice-Hall, 1984.
7. Two-Dimensional Signal & Image Processing, by J. S. Lim, Prentice-Hall, 1990.
8. Two-Dimensional Imaging, by Ronald N. Bracewell, Prentice-Hall, 1995.
9. Computer & Robot Vision, by Robert M. Haralick & Linda G. Shapiro, Addison-Wesley,1993.
10. Computer Vision, by Dana H. Ballard & Christopher M. Brown, Prentice-Hall, 1982.
11. Handbook of Pattern Recognition & Image Processing, by Tzay Y. Young & King-Sun Fu, Academic Press, 1986.
12. Digital Video Processing, by A. Murat Tekalp, Prentice Hall, 1995, ISBN: 0-13-190075-7.
13. Image and Video Compression for Multimedia Engineering: Fundamentals, Algorithms, and Standards, by Yun Q. Shi & Huifang Sun. CRC Press, 2000, ISBN: 0-8493-3491-8.(QA 76 .575 .S555 1999 C.2)
14. Wavelets and Subband Coding, by Martine Vetterli & Jelena Kovacevic, Prentice Hall, 1995, ISBN: 0-13-097080-8.
15. Wavelets and Subband Coding, by Martine Vetterli & Jelena Kovacevic, Prentice Hall, 1995, ISBN: 0-13-097080-8.
16. Probability, Random Variables, & Random Signal Principles, by Peyton Z. Peebles, JR., McGraw-Hill, 3rd edition, 1993, ISBN:0-07-112782-8.
17. Probability, Random Variables, & Stochastic Processes, by Athanasios Papoulis, McGraw-Hill, 1991 (QA 273 .P2 1991).

Course Description:
40-616+ provides an insight to advanced computer vision theory and techniques. Topics include: vision perception, geometry of single and multiple views, 3D Reconstruction and visualization, keypoint description, matching, alignment, natural features-based 3D tracking, numerical optimization and robust estimation, and deep learning in computer vision. A term-project is required.

Prerequisites:
40-933 (Digital Image Processing) and 40-625 (Stochastic Processing).

Credit:
3 units.

Course Schedule:
TBA

Website:
The course website can be found at CW.
Please check this site often for important announcements, files needed for computer exercises, and the PDF versions of handouts & homework.

Main Text Book:
An Invitation to 3-D Vision, by Yi Ma, Stefano Soatto, Jana Kosecka, & Shankar Sastry, Springer (Nov. 2, 2010), ISBN-10: 0387008934, ISBN-13: 978-0387008936.

Homework Policy:
Will be assigned during the course and solution provided. Some homework assignments will require programming and testing. Programming assignments can be submitted either in Matlab or C Languages.

Course Project:
There will be a course project/contest, which can also be proposed by the student. Students are supposed to present the final result and deliver the related software & technical report.

Grading Policy:
Quizzes: 2 Points
Written & Programming Assignments: 3 Points
Final Project/contest: 3 Points
Project Report: .5 Points
Project Presentation: .5 Points
Class Activities: 1 Point

Main Reference Books:

1. Multiple View Geometry in Computer Vision, by Richard Hartley & Andrew Zisserman, Cambridge University Press, 2nd Edition (2003), ISBN-10: 0521540518.
2. Computer Vision: A Modern Approach, by David A. Forsyth & Jean Ponce, Prentice Hall; US Ed Edition (Aug. 24, 2002), ISBN-10: 0130851981, ISBN-13: 978-0130851987.
3. Data Clustering: Theory, Algorithms, and Applications, by Guojun Gan, Chaoqum Ma, & Jianhong Wu. SIAM, Society for Industrial and Applied Mathematics (May 30, 2007), ISBN-10: 0898716233, ISBN-13: 978-8716238.
4. Probability, Random Variables, & Stochastic Processes, by Athanasios Papoulis, McGraw-Hill, 991 [SUT: QA 273 .P2 199].

Course Description:
40-344 provides an introduction to computer vision theory and techniques. Topics include: image formation and color representation, a brief review on signal and image processing, 3D geometry, interest point extraction, robust model fitting, clustering and segmentation, object recognition, nearest neighbors, and deep learning in computer vision. A term project/contest is required.

Prerequisites:
40-242 (Signals & Systems), 40-181 (Statistics & Probabilities), and 22-261 (Linear Algebra).

Credit:
3 units.

Website:
The course website can be found at CW.
Please check this site often for important announcements, files needed for computer exercises, and the PDF versions of handouts & homework.

Main Text Book
Compute Vision: Algorithms and Applications, by Richard Szeliski.Springer; 1st Edition (Oct. 1, 2010), ISBN-10: 1848829345, ISBN-13: 978-1848829343. http://szeliski.org/Book/.
KTH Lecture Notes on Geometric Computing, by Stefan Carlsson, http://www.nada.kth.se/~stefanc/gc_lec_notes.pdf.

Homework Policy:
Will be assigned during the course and solution provided. Some homework assignments will require programming and testing. Programming assignments can be submitted either in Matlab or C Languages.

Course Project:
There will be a course project/contest. Students are supposed to present the final result and deliver the related software & technical report.

Grading Policy:
Final Exam: 8 Points
Midterm Exam: 3 Points
Quizzes: 2 Points
Written & Programming Assignments: 3 Points
Final Project/contest: 3 Points
Project Report: .5 Points
Project Presentation: .5 Points
Class Activities: 1 Point

Main Reference Books:

1. An Invitation to 3-D Vision, by Yi Ma, Stefano Soatto, Jana Kosecka, & Shankar Sastry, Springer (Nov. 2, 2010), ISBN-10: 0387008934, ISBN-13: 978-0387008936.
2. Computer Vision: A Modern Approach, by David A. Forsyth & Jean Ponc, Prentice Hall; US ed edition (Aug. 24, 2002), ISBN-10: 0130851981, ISBN-13: 978-0130851987.
3. Data Clustering: Theory, Algorithms, and Applications, by Guojun Gan, Chaoqum Ma, & Jianhong Wu. SIAM, Society for Industrial and Applied Mathematics (May 30, 2007), ISBN-10: 0898716233, ISBN-13: 978-0898716238.

Course Description:
40-242 provides an introduction to signals & systems fundamental principles & techniques.
Topics include: Linear time-invariant systems, Fourier series representation of periodic signals, continuous-time Fourier transform, discrete-time Fourier transform, time & frequency characterization of signals & systems, sampling, Laplace transform, and Z transform.

Prerequisites:
Electrical Circuits (40-121) & Engineering Mathematics (22-041).

Credit:
3 units.

Website:
The course website can be found at CW.
Please check this site often for important announcements, files needed for computer exercises, and the PDF versions of handouts & homework.

Main Text Book:
Signals & Systems, by Alan V. Oppenheim & Alan S. Willsky, with H. Nawab, Prentice-Hall, 2nd Edition, 1997 (translated by Mr. Dayyani). [Additional topics might be included.]

Other Reference Book:
Digital Signal Processing, by John G. Proakis & Dimitris G. Manolakis, Prentice-Hall, 3rd Edition, 1996.

Homework Policy:
Homework problems will be assigned during the course and solution provided. Some homework assignments will require programming and testing. Programming assignments can be submitted either in Matlab or C Languages.

Grading Policy:
Written & computer assignments: 4.5 Points
Quiz: 2 Points (1 Point Each)
Midterm exam: 4 Points
Final exam: 10 Points
Class activities: 1.5 Points

Course Description:
40-221 provides an introduction to scientific & technical presentation. Topics include: Guidelines on good technical presentations (written and oral), elimination of sporadic noise in technical presentations, writing technical documents with emphasis on content and style, accessing technical information, engineering a presentation, and writing other common technical documents.

Prerequisites:
40-211 (Computer Engineering English)

Credit:
2 units.

Website:
The course website can be found at CW.
Please check this site often for important announcements, files needed for computer exercises, and the PDF versions of handouts & homework.

Main Text Book:
Scientific & Technical Presentation, by S.M.T. Rouhani Rankouhi, 2 edition, Jelveh Publisher, 1380. (Additional topics will be included.)

Homework Policy:
Homework problems will be assigned during the course. Name your presentation and report files as: Tech_Pres_7_1_group number.ppt, Tech_Pres_7_2_group number.ppt, & Tech_Pres_7_r_ type_group number.doc, respectively.

Course Project:
There will be some course projects.

• Student groups are supposed to present the assigned subjects and prepare some technical reports.
• Project topics should be different from the thesis, other course projects, & also other students' presentations.
• All groups should also use other references, specially [1, 2], to enrich the content.

Grading Policy:
Final exam: 4 pts.
Midterm exam: 1.5 pts.
Oral presentation: 4 pts.
Presentation report: 2 pts.
Final 4-page two-column report: 2.5 pts.
Professional organization memo (Persian and English): 0.5 pts.
User Manual: 2 pts.
Infographic presentation: 2 pts.
Participation: 1.5 pts.
Best presentation group: 0.5 pts.
Best infographic group: 0.5 pts.

Absence:
A substantial portion of this class revolves around in-class collaborative work. As emergencies do arise, you will be allowed one unexcused absence, but you will still be responsible for getting in contact with your peer group and/or completing the work for that day. Each absence after that can bring your grade down 0.25 level.
Excused absences are allowed in cases of serious problems. In order to receive an excused absence for an illness, you must notify me before class time or bring official notification.

Complete Work:
In order to receive a passing grade in this course, you must complete all of the work assigned during the semester. Late work will not be accepted.

Main Reference Books:

1. A Guide to Writing as an Engineer, by D. Beer and D. McMurrey, John Wiley & Sons Inc., 1997 (SUT Call No.: T11 .B396 1997 C.3).
2. The Student Skills Guide, by S. Drew and R. Bingham, Sampad Publisher, 1997.
3. The Craft of Scientific Writing, by Michael Alley, 3rd edition, Springle-Verlag, 1996.
4. From Research to Printout: Creating Effective Technical Documents, by J.H. White, The American Society of Mechanical Engineers ASME Press,1997 (SUT Call No.: T11 .W448 1997 C.6).
5. Dictionary of Problem Words and Expresions, by H. Shaw, McGraw-Hill, 1987.
6. Handbook of Technical Writing, by C.T. Brusaw, G.J. Alred, & W.E. Oliu, 6th edition, St. Martin's Press, New York, 117.
7. The non-desiners Design Book, by R. Williams, Peachpit Press, Berkley, CA, 1994.
8. Writing in the Technical Fields: A Step-by-Step Guide for Engineers, Scientists, and Technicians, by M.H. Markel, IEEE Press, 1994 (SUT Call No.: T11 .M3465 1994).