CAP 5415, fall 2016
Department of Computer Science, Florida State University
Monday
and Wednesday, 11:00AM – 12:15 PM, LOV 103
http://www.cs.fsu.edu/~liux/courses/cap5415-2016/index.html
This web site contains the up-to-date information related to this class such as
news, announcements, assignments, lecture notes, and useful links to resources
that are helpful to this class. Besides the web pages, Blackboard will be used
to communicate changes and updates and post grades for this class; in
particular, I will send emails using email addresses in the Blackboard system
and please make sure that your email address on record is current.
With the advances in software and hardware, intelligent components have become the most deciding factor in many applications and systems with intelligent components appear in daily news on a regular basis. Among different choices of sensors, visual sensors, i.e., cameras (and eyes in biological systems), are most efficient and effective in acquiring data of the environment and deriving information from the visual input should clearly be one of the important means and many applications such as automated target recognition have been long studied. Beyond visible spectra, advances in medical imaging and microscopic imaging have made computer vision and related techniques critical for many medical and biological applications. Additionally, with several decades of research, computer vision and related techniques are mature enough for solving problems in numerous applications.
This course provides introductory but
comprehensive coverage of principles, techniques, and algorithms to solve
problems in computer vision, including linear and nonlinear filtering, edge/corner
detection, stereopsis for 3D reconstruction, image segmentation and grouping,
motion estimation, texture modeling, appearance-based recognition, tracking,
and deformable template matching. It also offers opportunities to explore
applications of computer vision techniques in solving real world problems, such
as face detection and recognition.
COP 4530 – Data Structures, Algorithms, and
Generic Programming; basic knowledge and programming experience in any commonly
used programming language (for example, C, C++, Java, or Matlab); basic
knowledge and understanding of linear algebra algorithms and operations.
Upon successful
completion of this course of study, the student will:
Required
textbook: “Computer Vision: Algorithms and Applications,” Springer, 2010, by Richard Szeliski. An online
version available at http://www.szeliski.org/Book/drafts/SzeliskiBook_20100903_draft.pdf
(September 3, 2010 version).
Optional
reference book but not required:
“Computer Vision -- A Modern Approach”, Prentice Hall, 2003, by
David Forsyth and Jean Ponce; “Computer
Vision: Models, Learning, and Inference,”
Cambridge University Press, 2012, by Simon J.D. Prince (an online version is
available from http://www.computervisionmodels.com/);
“Image Processing, Analysis, and Machine
Vision,” Cengage Learning, 2014, by Milan Sonka, Vaclav Hlavac, and, Roger
Boyle.
In addition to the textbook, papers and notes
from the literature will be distributed along the lectures, including the
following journals and conference proceedings:
Attendance is required for this class. Unless
you obtain prior consent of the instructor, missing classes will be used as
bases for attendance grading. In case that it is necessary to skip a class, students
are responsible to make up missed materials. Participation of in-class
discussions and activities is also required. All submitted assignments and
projects must be done by the author(s). It is a violation of the Academic Honor
Code to submit other’s work and the instructor of this course takes the
violations very seriously.
About five homework assignments (including short programs in Matlab or other languages) will be given along the lectures and they need to be turned in. There will be two programming projects and a term project, which can be done in any programming language including Matlab, Java, and C/C++. Optionally, one can choose a grand project to substitute the two programming projects and the term project. There will be a midterm exam and no final exam.
Grades will be
determined as follows:
|
Assignment |
Points |
Assignment |
Points |
|
Class Attendance and Participation |
10 % |
Programming Project II |
10 % |
|
Homework Assignments |
25 % |
Term Project |
15 % |
|
Programming Project I |
10 % |
Midterm
Exam |
30 % |
Grading will be based on the weighted average as specified
above and the following scale will be used (suppose the weighted average is S
in 100 scale)
|
Score |
Grade |
Score |
Grade |
Score |
Grade |
|
93 £ S |
A |
80
£ S < 83 |
B- |
67 £
S < 70 |
D+ |
|
90
£ S < 93 |
A- |
77
£ S < 80 |
C+ |
63
£ S < 67 |
D |
|
87
£ S < 90 |
B+ |
73
£ S < 77 |
C |
60
£ S < 63 |
D- |
|
83
£ S < 87 |
B |
70
£ S < 73 |
C- |
S < 60 |
F |
Assignments are due at the beginning of the class on the due date. Assignments turned in late, but before the beginning of the next scheduled class will be penalized by 10 %. Assignments that are more than one class period late will NOT be accepted.
All tests/assignments/projects/homework will be returned as soon as possible after grading but no later than two weeks from the due date.
The
Florida State University Academic Honor Policy outlines the University’s
expectations for the integrity of students’ academic work, the procedures for
resolving alleged violations of those expectations, and the rights and
responsibilities of students and faculty members throughout the process. Students are responsible for reading the
Academic Honor Policy and for living up to their pledge to “. . . be honest and
truthful and . . . [to] strive for personal and institutional integrity at
Assignments/projects/exams are to be done individually, unless specified otherwise. It is a violation of the Academic Honor Code to take credit for the work done by other people. It is also a violation to assist another person in violating the Code (See the FSU Student Handbook for penalties for violations of the Honor Code). The judgment for the violation of the Academic Honor Code will be done by the instructor and a third party member (another faculty member in the Computer Science Department not involved in this course). Once the judgment is made, the case is closed and no arguments from the involved parties will be heard. Examples of cheating behaviors include:
v Discuss the solution for a homework question.
v Copy programs for programming assignments.
v Use and submit existing programs/reports on the World Wide Web as written assignments.
v Submit programs/reports/assignments done by a third party, including hired and contracted.
v Plagiarize sentences/paragraphs from others without giving the appropriate references. Plagiarism is a serious intellectual crime and the consequences can be very substantial.
Penalty for violating the Academic Honor Code: A 0 grade for the particular assignment/quiz/exam and a reduction of one letter grade in the final grade for all parties involved for each occurrence. A report will be sent to the department chairman for further administrative actions.
Students with disabilities needing academic accommodations should: 1) register with and provide documentation to the Student Disability Resource Center (SDRC), and 2) bring a letter to the instructor indicating the need for accommodation and what type. This should be done within the first week of class. This syllabus and other class materials are available in alternative format upon request.
For more information about services available to FSU
students with disabilities, contact the Assistant Dean of Students:
108 Student Services Building
(850) 644-9566 (voice)
(850) 644-8504 (TDD)
sdrc@admin.fsu.edu
http://www.disabilitycenter.fsu.edu/
© 2016, Florida State
University. Updated on August 27, 2016.