Catalog Description: Paradigms for computational vision. Relation to human visual perception. Mathematical techniques for representing and reasoning, with curves, surfaces and volumes. Illumination and reflectance models. Color perception. Image segmentation and aggregation. Methods for bottom-up three dimensional shape recovery: Line drawing analysis, stereo, shading, motion, texture. Use of object models for prediction and recognition.

Units: 3

Also Offered As: VISSCI C280, COMPSCI C280

Related Areas:

• Artificial Intelligence (AI)
• Biosystems & Computational Biology (BIO)
• Graphics (GR)

Prerequisites: MATH 1A; MATH 1B; MATH 53; and MATH 54 (Knowledge of linear algebra and calculus).

Formats:
Spring: 3.0 hours of lecture per week
Fall: 3.0 hours of lecture per week

Grading Basis: Default Letter Grade; P/NP Option

Final Exam Status: Yes

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Class Schedule (Spring 2026):
CS C280 – TuTh 15:30-16:59, Hearst Mining 390 – Alexei Efros, Angjoo Kanazawa

Class Notes
- Time conflicts are not allowed

- Interested non-EECS/CS PhD students will be vetted by the instructors. Please attend the first class meeting for further instructions.

Links:

• EECS Course Archives (CalNet authentication required)
• CS enrollment policies
• EE enrollment policies
• HKN course maps