[ Home ] [ Syllabus ] [ Lectures ] [project]
CS 181b/ECE 181b: Introduction to Computer Vision
B. S. Manjunath, manj at ece. Rm 3157, Engineering I. Tel: 805.893.7112
Office hours: T 1045-1145am, Th 1-2PM, or by appointment (or drop by and see if I'm available)
Teaching Assistants:
TA Office hours are held in Phelp 1435
Marco Zuliani, zuliani at ece.ucsb.edu (Thursday 1-3PM)
Laura Boucheron, lauraeb at ece.ucsb.edu (Monday 4-5PM and Fridfay 9-10AM)
Sharadh Ramaswamy, rsharadh at umail.ucsb.edu (Wednesday 1-2 PM, Friday 1-2PM)
Meeting Times and Locations
Lecture: Tues/Thurs 9:30-10:45am, Webb 1100
Discussion sessions: Mon 3:00-3:50pm (CS 181b students), Phelps 1425 or Fri 10:00-10:50am (ECE 181b students), Phelp 1425TA Office hours: Phelp 1435
Text Book: There is no required text book for this class. Lecture slides will be posted on the web. You may also want to browse through Professor Matthew Turk's S2003 class web site.
About the course:
An introduction to the field of Computer Vision (also known as Machine Vision or Image Understanding or Computational Vision). The aim of computer vision is to make computers "see" by processing images and/or video. By knowing such things as how images are formed, information about the sensors (cameras), and information about the physical world, it is possible (at least in some cases) to infer information about the world from an image or set of images. For example, one may wish to know the color of an apple, the width of a printed circuit trace, the size of an obstacle in front of a robot on Mars, the identity of a person's face in a surveillance system, the motion of an object, the vegetation type of the ground below, or the location of tumor in an MRI scan - automatically, from images. Computer vision studies how such tasks can be done, and how they can be done robustly and efficiently. Originally seen as a sub-area of artificial intelligence, computer vision has been an active area of research for almost 40 years.
People come to computer vision from of a variety of motivations. Some want to better understand biological vision - how people and animals see, how the eye and the brain work together to enable sight. Others want to build robots that can perceive and react to the environment around them. Others are interested in multimedia databases, image compression, human-computer interaction, security and surveillance, medical imaging, and other areas. Whatever the motivation or application, there are several topics that are fundamental to work in computer vision and are important to almost any application.
The tentative topics for S2004 are:
Application to image registration, content based retrieval and image databases, and face recognition.