Texts:

1. Required: Introductory Techniques for 3D Computer Vision, E. Trucco and A. Verri, Publisher: Prentice-Hall.
2. Other Material: Class notes and papers from the following: IEEE Trans. Patt. Anal. Mach. Intell. and other journals

Office hours: TR 1:30PM-3PM or by appointment.

Grading:

1. Homeworks: 25%.
2. Two Midterms: 25% each.
3. Computational Exercises: 25%

1. Prerequisites: A familiarity with basic concepts in calculus and linear algebra. A partial list of basic requirements follows. Calculus: Differentiation, chain rule, integration. Linear algebra: Matrix multiplication, inverse, pseudo-inverse.
2. Homeworks/programs will be assigned bi-weekly. If you do not have any prior numerical computing experience, I suggest you use MATLAB for the programs.
3. First Midterm will be given approximately at the middle of the semester and the second will be in the last week of classes.
4. A set of notes which will evolve with the course can be found here.
5. Here is the link to the homework and computational exercises announcements.

 

 
 
 

Image features: Image acquisition, edge detection, surface extraction, Hough transform, deformable contours.

Stereopsis: Correspondence, epipolar geometry, reconstruction.

Motion: Motion fields, optical flow, structure from motion.

Recognition: Interpretation trees, invariants, Appearance-based identification, pose estimation.