Learning from Design Heritage
Research Workshop on Data-driven Methods
| A research project on Machu Picchu, an example using various technology methods |
* The first class: 11am, Monday, February 6
* Undergrad students should sign up 4.550 and grad students should do 4.570.
* Limited enrollment: 9-12 students
* Spring 2023 class includes NO field trip component
* This class is a sequel following the same subject number in spring 2013-20, and may be taken repeatedly with permission of the instructor.
* Homepage: https://cat2.mit.edu/4.570
Spring 2023 - Class Information
This class investigates recent information and visualization technologies that helps studying "design heritage", spatial designs that surround our lives. Design heritage broadly includes architecture, city and landscape; the built, demolished, and planned; and culturally important as well as the banal ones. We will look at various data-driven methods relevant to learn them, such as image/video feature detection, machine learning, physiological sensors, natural language processing, photogrammetric capture, augmented/virtual reality, and gamification. By examining how to collect data, how to process the raw data into forms useful for evaluation, and how to interpret and apply the findings, the students build a foundation for research projects bettering our understanding of the design heritage around us.
Each week during the first half of the class, the class will invite a guest speaker, conduct a short hands-on exercise on a selected data processing tool, and read relevant literature from previous research projects in design heritage. The second half is run in a workshop format with desk critiques, where students are expected to design and develop a small research project individually or in a group. There is no requirement for computational skills for this class, although familiarity with some scripting language is an advantage.
Instructors:
Takehiko Nagakura (takehiko@mit.edu), Daniel Tsai and weekly guest speakers
TA: Han Tu (hantu@mit.edu)
Regular Class Hours: Monday 11:00 AM - 2:00 PM
Lab (subject to change): Tuesday, 7:00 PM - 8:30 PM
* Lab hours are used for demos during the first half of the semester, and for project development by student teams during the second half.
* The final presentation of this class takes place during the last class just before the MIT exam week in May 2023.
2023 Class information
- Flyer (Summery)
- Schedule (subject to change)
- Reference: Relevant projects from recent MIT theses (Research prjoects)
- Examples of student final project from 2022 class (Research prototypes)
- Examples of class projects from the past fieldworks (Representation prototypes)
- Exercise 1: image feature analysis
- Exercise 2: image-to-image generative machine learning
- In-class exercise: Photogrammetric modeling and AR
- Exercise 4: video semantics analysis
- Exercise 5: VR and measurement
- Exercise 6: Exploaring Language and Design via NLP
- Final Project Ideas
- Final Presentation and Submission (TBA)
- MET warehouse (no AR)
- MET warehouse (with AR)
