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General Information:
| Lectures: | Tue/Thu, 12:30-1:45 | Hardman Hall # 101 1031-0101 |
| Presentations | Wed, 12:20-1:10 | Hardman Hall # 101 1031-0101 |
| Instructor: | Maria Hybinette | Boyd 219 C |
| TA | Michael Scott | mkdsctt AT gmail.com |
| Office hours: | Wed, 1:10-3:10 | |
| and by appointment | ||
| Mailing list: | ASA-Photography@listserv.uga.edu |
Short Description:
We will explore the scientific, artistic, and computational aspects of digital photography.
Learning Goals:
Upon completion of this course a student will understand how digital images are created and manipulated algorithmically for artistic objectives.
Longer Description:
This class explores the art, science and algorithms of photography with a focus on digital photography and digital image manipulation. We follow the photographic process from capture of the scene as light first enters the lens and strikes a sensor to manipulation of the data to the final image. The course will cover the quality of light, the rendering of texture, tone, shade and deep shadows both in practice and theory.
We will study algorithms for image manipulation that are often used to transform photographs, and use them in class projects. Finally we will look at compositional elements from the fine arts, including painting and architecture and study what makes an image pleasing and compelling.
Topics:
Lenses and optics, light and sensors, optical effects, perspective and depth of field, tilt-shift, sampling and noise, human visual system, color science, exposure control, camera as a computing platform, computational photography, history of photography, architecture and resolution.
Prerequisites & Expectations:
Java programming experience in Java, C++, MATLAB or Python and Calculus. Some projects will be coded in Python, but specific Python is not expected.
Students interested in this class should have access to and have some understanding on how to operate a digital camera with manual control of exposure and control of focus. You will need access to either a zoom lens or lenses with different focal lengths. You will also need to have a laptop with Photoshop installed on it, and bring that laptop to class.
Class Assignments:
Hands-on and based on the creation and manipulation of digital images and reading technical papers in image processing and the popular media literature.
Evaluation Policy:
You are evaluated via assignments (homework and 'image' projects), critique, presentations, summaries, quizzes, and exams. Grades will be based on whether you met the requirements of the assignment, and there may be a creative component as well.
Image (weekly), project (less frequent) and homework will be posted on the web from the scheduling page, and will be accessible from anywhere on the Internet. Image assignments will involve hands on experience in creating images and they may involve programming components. Homework is to gauge whether you understand concept covered in class or from the reading, it may contain technical questions solidifying the technical concepts that we are focusing on for the current week.
Critiques of 'image assignments are important to the creative and technical progress of each individual in the class, and to the success of the course itself. You will critique both your own work and other student's work. The critique fosters development of an ability to verbalize visual concepts, and it will help you learn to see actively.
You will present on one two topics throughout the semester, each presenter is expected to read additional technical papers (or essays), or tutorials to ensure breadth of the week's topic. Some suggestions to add "breath" to your theme topic are listed in the reading list, or you may choose your own. You will select the theme, but the specific paper will be assigned (however you may suggest or express interest in particular paper).
You will read/skim at least one technical paper, book chapter, tutorial, or essay every week. For each week each you will prepare a 1-page summary on one of the presented papers (you may chose any one of the two). This summary must be emailed to the grader account before midnight on the day the paper is due, typically a Wednesday. You also must turn in a hard copy of the summary the following day (typically a Thursday). The hardcopy will be used for grading and the email will check when you turned in the summary. The summary needs to reflect that you made an effort to read and understand the paper. The summary should address the questions listed on the reading list. You should also include a brief critique of the current week's presentation (both presentations). What else should have been included?/excluded? Suggested improvements? You may skip up to 2 summaries without a penalty (see reading page link above for specific questions that you need to address).
Grade Distribution and Grade Philosophy:
The grade distribution is as follows:
| Participation | 05% |
| Quizzes (fun) | 05% |
| Workshops | 15% |
| Exam 1 | 10% |
| Exam 2 | 10% |
| Final | 15% |
| Photo Assignments | 15% |
| Projects | 15% |
| Critique | 5% |
| Homework | 5% |
(subject to change)
Note that our course syllabus is a general plan for the course; deviations announced to the class by the instructor (either in class or online) may be necessary
A+ (95-100) Extraordinary, goes beyond minimum criteria both in depth and breath. Design is thourough and well thought out, code base and implementation is beautiful- modularized, complete, clear and concise. A well thought out debugging strategy is appearant. Well documented code. The evaluation plan is welll executed and well thought out, goes beyond the simple cases and illustrates strong problem solving skills.
A (90-94) Superior (somewhat less than an A+, almost perfect code, beautiful, concise, minimum criteria met, not as much depth and forethought as an A+ but it is superb), goes beyound meeting the minimum critera demonstrates depth, can apply solution to a variation of similar problems.
B (80-89) Good, minimum criteria well executed and well done, shows some depth and understanding, meets most testcases but not as much forethought as an A;
C (70-79) Fair, minimum criteria met, but could have been executed with more depth and forethought.
Assignment Posting Policy:
Assignments may be posted before they are officially assigned; however, you should not assume that an assignment on the web is in final form until the date it is assigned. In other words, assignments are subject to change before the date that they are officially assigned.
Participation, Attendance & Other Policies:
Class attendance is mandatory; we typically do not take attendance - but it happens, and class participation is 5% of your grade. So how do we know? Don't worry, we know.
Homework, assignments, and important dates will be posted on the scheduling page and is provided as a courtesy and is not always complete. It's your responsibility to find out what you missed if you don't attend class. You are also required to subscribe to the class email list or forum - and be aware that sometimes homework is assigned via the forum - or there are some hints posted in the forum - you probably do not want to miss that.
Office hours are of-course optional. They're your chance to ask the instructor about the material being covered, assignments, or anything else about themes related to computational photography.
Honor Code:
As a University of Georgia student, you have agreed to abide by the University's academic honesty policy, "A Culture of Honesty," and the Student Honor Code. All academic work must meet the standards described in "A Culture of Honesty" found at: www.uga.edu/honesty. Lack of knowledge of the academic honesty policy is not a reasonable explanation for a violation. Questions related to course assignments and the academic honesty policy should be directed to the instructor. The link to more detailed information about academic honesty can be found at: http://www.uga.edu/ovpi/honesty/acadhon.htm
Late Policy:
Homework assignments and summaries are due on the date and time specified in the assignment or the day of the presentation (email as a time stamp and hand-in hardcopy the next day). Late homework will not be accepted.
For the programming assignments (and for final project milestones) you will have 3 grace days to extend the due date of a programming assignment (for you only, not the whole class). Programming assignments turned in after the due date lose 10% per day, including weekends and holidays. Grade days will be automatically applied at the end of the Semester. There will be opportunities throughout the semester to earn additional grace days.
There may be a time where you submit a project but it doesn't work for the TA (the TA will not fix your programs for you). If this happens, your project will be returned to you and you will be given the opportunity to fix and resubmit the project (after this point you may have to meet with the TA to demonstrate it). After the project is returned to you, every 24 hour period used to fix the project will use up a grace day. If you no longer have any grace days left, 10% will be docked off of the project for every day late. If you feel that the project should have worked, and you are not at fault, please contact the TA immediately in order to schedule an appointment to resolve the issue.
Make-up exams will only be administered under extreme circumstances and will be determined on an individual basis.
Inspiration/Acknowledgments:
Some representative components of this course are taught at Berkeley, Stanford and Georgia Tech and are used by permission, e.g., Professor Marc Levoy's Digital Photography Course @ Stanford University (emphasis, we will follow Prof. Levoy's scheme pretty closely, but we will add programming projects) and Professor Brian Barsky @ University of California at Berkeley and Professor Irfan Essa @ Georgia Tech and Professor Dellaerts Computional Photography Course (links provided in page below).
Class Resources & Other Digital Photography Courses
Class Photo:
+ ~~ Spring 2011 Class ~~ +