Some UCSB courses related to imaging, vision, perception, AI, HCI, etc.

(Please email if you'd like me to add anything)

[ CS - ECE - Psych - Comm - Int ]

Computer Science Department

165A. Introduction to Artificial Intelligence
(4) Turk
Prerequisites: Computer Science 130A or consent of instructor.
An introduction to the field of Artificial Intelligence, which attempts to understand and build intelligent systems.  Topics include AI programming languages, search, knowledge representation and reasoning, planning, perception, and intelligent agents..

165B. Machine Learning
(4) Smith
Prerequisites: Computer Science 165A or consent of instructor.
Machine intelligence is concerned with computational techniques for representing and reasoning about complex objects. Topics covered include some of the machine intelligence programming languages, data structures, control structures, and problem solving techniques used in both research and application.

180. Computer Graphics
(4) Wang
Prerequisite: Computer Science 130B.
X Window System; Xlib and widget programming; 2D drawing and painting algorithms; 2D transform and clipping; 3D transform, viewing, and clipping; overview of PHIGS graphics standard; graphics hardware; interactive devices and techniques; half-tone and dithering techniques; hidden surface removal algorithms.

181B. Introduction to Computer Vision
(4) Wang
Same course as ECE 181B.
Overview of image processing, pattern recognition; image formation, binary images; edge detection, image segmentation, introduction to textured image analysis, optical flow, depth from stereo, shape from shading, shape from motion, shape representation techniques, issues in object recognition, case study of some vision systems.

182. Multimedia Computing
(4) Almeroth
Prerequisites: Computer Science 176A and 176B.
Not open for credit to students who have completed ECE 160.
Introduction to multimedia and applications, including video conferencing, WWW, digital libraries, video on demand. Digital video and audio communication architectures, standards (including JPEG and MPEG2), multimedia storage and retrieval. Multimedia computing on the Internet and digital libraries. (first offered 2003-2004)

265. Advanced Topics in Machine Intelligence
(4) Smith
Prerequisite: Computer Science 165.
Course may be repeated for credit.
Topics covered include advanced programming techniques for representing and reasoning about complex objects, and various applications of such techniques including expert systems, natural language processors, image understanding systems, and machine learning.

280. Computer Graphics
(4) Wang
Prerequisite: Computer Science 180.
Special topics in computer graphics including: curves and curved surfaces, visual perception of colors and color models; shading models; shadow generation; texture mapping; solid textures; stereographics; helmet-mounted display; graphics hardware/architecture; solid modeling; physically-based modeling; fractals and graphtals; volume rendering; scientific visualization.

281B. Advanced Topics in Computer Vision
(4) Wang
Prerequisite: Computer Science 181B.
Same course as ECE 281B.
Advanced topics in computer vision: image sequence analysis, spatio-temporal filtering, camera calibration and hand-eye coordination, robot navigation, shape representation, physically-based modeling, multi-sensory fusion, biological models, expert vision systems, and other topics selected from recent research papers.

290A. Human Computer Interaction
(4) Turk

In this course, we will investigate next-generation user interfaces that use such technologies.  Topics include a review of HCI concepts and history, input devices and interaction techniques, information appliances, 3D user interfaces, adaptive interfaces, user modeling, speech recognition and conversational interfaces, wearable computers, multimodal interfaces, and perceptual interfaces.

290A. Computer Imaging
(4) Turk

The course will cover a broad range of subjects related to creating, processing, displaying, and interpreting digital images and video.  Topics include light, optics, cameras, color, image processing, image display, medical imaging, and computer vision.

Electrical and Computer Engineering Department

160. Multimedia Computing
(4) Chang
Prerequisites: ECE 155A, 158, and 178.
Not open for credit to students who have completed Computer Science 182. Lecture, 3 hours; laboratory, 3 hours.
Introduction to multimedia and applications, including video conferencing, WWW, digital libraries, video on demand. Digital video and audio communication architectures, standards (including JPEG and MPEG2), multimedia storage and retrieval. Multimedia computing on the Internet and digital libraries. (not offered 2000-2001)

177. Visual System Analysis
(4) Staff
Prerequisite: open to upper-division students only.
Same course as Psychology 130. Open to non-majors.
Recommended preparation: calculus, linear algebra and some computer programming experience. Lecture, 3 hours.
A systems approach to understanding vision. Topics will typically include transduction, signal detection, space and motion perception, color vision, and pattern classification. Special emphasis will be placed on comparing computational models with quantitative description of human visual performance.

178. Fundamentals of Computer Image Processing
(4) Manjunath
Prerequisites: ECE 15 or ECE 15A-B or Computer Science 30; and, ECE 130A-B; open to ECE and CE majors only. Lecture, 3 hours; discussion, 1 hour.
Basic concepts in image processing. Techniques, capabilities, and limitations with emphasis on use of digital computer but also of optical and analog systems. Image sampling, reconstruction, enhancement, restoration, data extraction, and coding. Some hands-on laboratory experience is offered. (W)

181B. Introduction to Computer Vision
(4) Manjunath
Prerequisites: upper-division standing.
Same course as Computer Science 181B. Lecture, 3 hours; discussion, 1 hour.
Overview of image processing, pattern recognition; image formation, binary images; edge detection, image segmentation, introduction to textured image analysis, optical flow, depth from stereo, shape from shading, shape from motion, shape representation techniques, issues in object recognition, case study of some vision systems. (S)

277B. Pattern Recognition
(4) Rose
Prerequisites: ECE 130C and 140. Lecture, 4 hours.
Principles and design of pattern recognition systems. Statistical classifiers: discriminant functions; Bayes, minimum-risk, k-nearest neighbors, perceptrons. Clustering and estimation; criteria; k-means, fuzzy, hierarchical, graph-theoretic, simulated and deterministic annealing; maximum likelihood and Bayesian methods; nonparametric methods. Overview of applications. (W)

278A. Digital Image Processing
(4) Mitra, Manjunath
Prerequisite: ECE 158 or ECE 178. Lecture, 3 hours; laboratory, 3 hours.
Two-dimensional signals and systems. Two-dimensional Fourier and z-transforms. Discrete Fourier transform, two-dimensional digital filters. Image processing basics, image enhancement and restoration. Special image processing software available for laboratory experimentation. (S)

278B. Selected Topics in Image Processing
(4) Manjunath
Prerequisite: ECE 278A. Lecture, 4 hours.
An advanced course in DIP: topics to be covered include edge detection, random fields and application to image analysis including textures, image reconstruction. (may not be offered every year)

278C. Imaging Systems
(4) Lee
Prerequisites: ECE 158 and 178. Lecture, 4 hours.
Generalized holography, backward techniques, resolution limit, X-ray tomography, diffraction tomography, NMR imaging, synthetic-aperture radar, active sonar imaging, acoustic microscopy, imaging algorithms, motion estimation and tracking. (S)

281B. Advanced Topics in Computer Vision
(4) Manjunath
Prerequisite: ECE 181B. Lecture, 3 hours.
Same course as Computer Science 281B.
Advanced topics in computer vision: image sequence analysis, spatiotemporal filtering, camera calibration and hand-eye coordination, robot navigation, shape representation, physically-based modeling, multi-sensory fusion, biological models, expert vision systems, and other topics selected from recent research papers. (F; offered alternate years)

Psychology Department

107. Introduction to Perception
(4) Loomis
Prerequisite: a prior lower-division course in psychology, or upper-division standing.
May not be taken after or concurrently with Psychology 110A or 110B or 110C or 110L or 118A.
An introductory course in perception open to students in all majors. A variety of demonstrations are used to allow the student to experience the phenomena of perception. Current hypotheses and theories concerning the underlying psychological and biological processes are described.

110A. Perception: Vision
(4) Brainard
Prerequisites: Psychology 1, 5, and 7; open to psychology and biopsychology majors only.
May not be taken concurrently with Psychology 107.
This course is an overview of visual perception. It covers a wide range of phenomena from the detection of simple stimuli to the identification of objects and events. Human performance, psychological theories, and biology will be considered.

110B. Perception: Audition
(4) Ashby, Loomis
Prerequisites: Psychology 1, 5, and 7; open to psychology and biopsychology majors only.
May not be taken concurrently with Psychology 107.
An overview of auditory perception covering topics such as the physics of sound, psycho-physical methods, the structure and function of the ear and auditory pathway, detection and discrimination, masking, pitch perception, musical scales, 3-D localization, and speech perception.

110L. Laboratory in Perception
(5) Brainard
Prerequisites: Psychology 1, 5, 7; and, Psychology 110A or 110B or 110C or 132; open to psychology and biopsychology majors only.
A laboratory course that emphasizes experimental methods and data analysis techniques relevant to the study of sensation and perception.

130. Visual System Analysis
(4) Staff
Prerequisite: upper-division standing.
Same course as ECE 177.
Recommended preparation: calculus, linear algebra and some computer programming experience.
A systems approach to understanding vision. Topics will typically include transduction, signal detection, space and motion perception, color vision, and pattern classification. Special emphasis will be placed on comparing computational models with quantitative descriptions of human visual performance.

132. Visual Neuroscience
(4) Jacobs
Prerequisites: Psychology 1, 5, and 7; and, Psychology 106 or 111; and MCDB 1A-AL; and, MCDB 1B-BL or EEMB 2-2L; open to psychology and biopsychology majors only.
An examination of the neural basis of vision. The course focuses on mammalian vision and considers evidence from behavioral and biological approaches.

228. Perception
(4) Brainard
Analysis of psychophysical relations in sensory processes with stress on detection, scaling, discrimination, spatial and temporal resolution, and the interaction of cue systems in perceptual behavior.

230. Psychophysiology of Vision
(4) Jacobs
Consideration of the physiological and psychophysical data bearing on the major features of vision in vertebrates.

Communication Department

161. Interactive Media Theory and Design
(4) Lieberman
Interactive Media Theory and Design is an introduction to the human side of human-computer interaction.  Drawing on the material covered in the course, how should we design interactive applications to meet each group’s special needs and interests? 

Interdisciplinary Studies

200. Seminar in Cognitive Science
(2) Staff
Prerequisite: graduate standing.
Research seminar on topics in cognitive science.