Computational Computer Vision
(3-0-0-3)
CMPE Degree: This course is Selected Elective for the CMPE degree.
EE Degree: This course is Selected Elective for the EE degree.
Lab Hours: 0 supervised lab hours and 0 unsupervised lab hours.
Technical Interest Groups / Course Categories: Threads / ECE Electives
Course Coordinator: Patricio Antonio Vela
Prerequisites: ECE 3084 [min D] or ECE 3550 [min D]
Catalog Description
Computational and theoretical aspects of computer vision. Application areas include robotics, autonomous vehicles, tracking, and image-guided surgery. Includes major project.Textbook(s)
Robot VisionCourse Outcomes
Derive and describe image formation with regards to world and camera relative geometry;
Describe the process of camera calibration and its related optimization formulations;
Apply stereo triangulation and epipolar constraints for solving vision related problems;
Describe the relationship between the heat equation, diffusion, and Gaussian smoothing;
Apply and implement differential and convolutional operators as discrete stencil operations;
Explain the role of optimization in solving vision-based problems or estimating visual properties;
Describe the purpose of adding prior constraints or regularization terms to computer vision derived optimization problems;
Describe fundamental approaches to segmentation and clustering;
Explain the equations underlying optical flow and their derivation from cost functionals;
Strategic Performance Indicators (SPIs)
N/A
Topic List
- Introduction
- Classic methods of linear filtering
- Sketch of wavelet techniques
- Edge detection
- Segmentation
- Optical flow and stereo disparity
- Shape recognition
- Color and texture processing
- Motion planning and tracking
- Applications: Robotics, Image-guided surgery, Controlled active vision