Data Privacy via Machine Learning, and Back

Focuses on discussion of recent advances in the area of visual storytelling in graphical environments. Major topics covered in this course are: intelligent camera control, shot-composition, lighting design, interactive storytelling, and computational techniques associated with these applications. Class will consist of in-class discussions and student presentations of research papers and a final student project. 

Course structure and class format


Class will meet twice a week in Baskin Engineering 156 at 6 PM on Tuesdays and Thursdays. During our class meetings we will discuss texts and papers related to computational cinematography from the reading list available from the class website. Discussion will take place in debate format where students, who are assigned to defend arguments and claims made in respective papers, will lead the discussion against students assigned to be opponents. Each student will be expected to lead two classes as proponent and two as opponent.




Assignments will consist of three types of activities:

  • Class discussions : 2 as proponents and 2 as opponents
  • Essays               : 3 essays on class topics. These will be due in weeks 5, 7, and 9 at the end of Thursday's class. They should be formatted using AAAI format and should fit in 6 pages with references. Examples of essay formats : 
        1. Summarize related work in one of the interest areas
        2. Proposal for extension of one of the computational models discussed in class
        3. Detailed analysis of one of the models in terms of factors like expressive power, authorial burden, etc.
        4. Some other format that is pre-approved by the instructor
  • Group project : Students will work on a group project during the quarter. Teams should contain 2 or more students. Interdisciplinary teams are encouraged. Project could be implementation and extension of an existing system, demonstration of a concept from film theory implemented as a computational prototype, user study validating claims of an existing system, user study to understand some aspect of the visual system (eg. pre-attentive processing). Specific project definitions for sample projects will also be provided in class. Each project group will be expected to present results of their project in a final class presentation and submit a paper (also in AAAI format) of up to 4 pages summarizing the main results of their work.

Instructors and Assistants