Special Topics in Data Science, DS-GA 3001.005/.006
DS-GA 3001.005 (Lecture)
Tuesdays 2pm-3:40pm 60FA room 110
DS-GA 3001.006 (Lab)
Tuesdays 3:50pm-4:40pm 60FA room 110
Office hours: Thursdays 2:00pm-4:00pm 60FA room 606
Jean Ponce (firstname.lastname@example.org)
Matthew Trager (email@example.com)
Jiachen Zhu (firstname.lastname@example.org)
Sahar Siddiqui (email@example.com)
Four/five programming assignments (60% of the grade) + final project (40% of the grade).
- Excercise 1 on camera calibration (zip file). Due on October 1st (on NYU class site).
Collaboration policy: You can discuss the assignments and final projects with other students in the class. Discussions are encouraged and are an essential component of the academic environment. However, each student has to work out their assignment alone (including any coding, experiments, and derivations) and submit their own report/notebook.
- Part I: Low level Computer Vision
- Filters, edge detection, visual features.
- Radiometry, shading and color.
- Part II: 3D reconstruction
- Camera models, one-view geometry.
- Multi-view geometry, stereo, SFM.
- Part III: Recognition
- CNNs for object detection and semantic segmentation.
- D.A. Forsyth and J. Ponce, “Computer Vision: A Modern Approach”, second edition, Pearson, 2011.
|1||9/3||Course overview, image formation||Slides|
|2||9/10||Camera geometry and calibration I||Slides|
|3||9/17||Camera geometry and calibration II||Slides|