This course provides an introduction to computer vision, an area that lies in the heart of many modern AI applications: robotics navigation, searching through billions of images, autonomous vehicles and social networking. Computer vision technologies can understand and reconstruct the visual world. The course covers a range of topics, including feature detection, motion estimation, panoramas, 3D shape reconstruction, and object detection and recognition.
This course emphasizes hands-on experience with computer vision, with several large programming projects.
Knowledge of the following is required:
- Image Processing and Analysis 046200
- Working knowledge of MATLAB or Python and preferably also C/C++
- Linear algebra
- Basic probability theory and statistics
- Recommended: Vector calculus, Data structures
The course grade will be determined as follows:
- HW1: 15%
- HW2: 15%
- HW3: 15%
- HW4: 10%
- Active participation in class: 5%
- Final exam: 40%