CSE455: Computer Vision

4

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.

CSE 303; CSE 326; recommended: MATH 308.

Introduction to image analysis and interpreting the 3D world from image data. Topics may include segmentation, motion estimation, interest operators, image mosaics, 3D-shape reconstruction, object recognition, and image retrieval.

No required text. Recommended: Shapiro and Stockman, Computer Vision, Prentice Hall, 2001 or Sonka, Hlavac, and Boyle, Image Procesing, Analysis, and Machine Vision, ITP, 1999. Lecture notes and some technical paper are posted on the class web site.

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.

* feature detection, descriptors, and matching * image segmentation * motion * mosaics * 3D sensing and reconstruction * object recognition

2 lecture/discussion periods per week. 4 programming projects, each requiring a short report. 2 exams.

shapiro