CSE 455
Computer Vision
Credits
4.0
Lead Instructor
Steven Seitz
Textbook
None
Course Description
Introduction to image analysis and interpreting the 3D world from image data. Topics may include segmentation, motion estimation, image mosaics, 3D-shape reconstruction, object recognition, and image retrieval.
Prerequisites
CSE 303 or CSE 333; CSE 326 or CSE 332; recommended: MATH 308; STAT 391.
CE Major Status
Selected Elective
Course Objectives
Students learn the basics of computer vision and some of the state-of-the-art techniques. They will
be able to write programs that can perform image segmentation, image matching, object detection or
recognition, and applications such as content-based image retrieval or construction of panoramas.
Upon completion of the course they should be able to take an internship or job with a vision
company or research lab doing vision or to participate in undergraduate research leading to
potential graduate level research.
ABET Outcomes
No outcomes registered
Course Topics
- * feature detection, descriptors, and matching
- * image segmentation
- * motion
- * mosaics
- * 3D sensing and reconstruction
- * object recognition