Mailing list link
Office Hours and Location: Monday 4:00 pm.
TA: Otavio Braga, e-mail: obraga at cs.nyu.edu
Office Hours: Tuesdays at 4:00 pm. 719 Broadway, Room 1219
Course Structure: theory and laboratory work. Groups of three students will work together in developing vision applications. We will use the microsoft Kinect as a plataform to acquire images, infrared depth maps, and skeletons.
See the following SDK
- Primesense SDK (windows, Linux, MacOs) http://www.openni.org/downloadfiles/openni-compliant-middleware-binaries/33-latest-unstable
HowTo install on Linux: http://www.keyboardmods.com/2010/12/howto-kinect-openninite-skeleton.html
- LibFreenect (no skeleton) for windows, Linux, MacOS http://openkinect.org/wiki/Getting_Started
Projects will be developped in class and as homeworks. Evaluation is based on participation and project results.
1. Introduction to Computer Vision.
A historical film about the beginning of computer vision MIT-1959
2. Format Images
There is a large library of computer vision algorithms including how to read and write image files at opencv
3. Camera Calibration.
3. Image Measurements and Feature Detection
(Image pixels, oriented filters, derivatives)
4. Image Segmentation and Graph Cut Method
(Lecture 4 is from Hiroshi Ishikawa, Ph.D. student at NYU and now professor in Japan, see his page http://www.f.waseda.jp/hfs/index.html)
This is a paper by Microsoft Cambridge Researchers with a more detailed development of Graph cut for Segmentation
5. The K-means and the Expectation Maximization methods.
6. Symmetry and Skeletons
A paper by Microsoft researchers on the kinect skeleton extraction
Condensation Algorithm home page
Homework 1: Due Thursday, October 13th
Homework 2: Due Tuesday, November 1st
Homework 3: Due Thursday, December 15th