Graphics and Vision
Computer graphics, classical computer vision, and human-computer interaction.
Graphics and Vision addresses computer graphics, classical computer vision, and human-computer interaction. It sits within Computer Science and inherits that area’s core questions about correctness, scale, and tractability. This page surveys the conceptual axes of the topic and points to the references that frame ongoing research and teaching. The intent is to be useful both as an entry point for newcomers and as an index for practitioners cross-checking their mental model against the field’s primary sources.
Work on graphics and vision can be organised around a few interlocking concerns: the formal objects under study, the algorithms or systems that compute over them, the resource trade-offs (time, memory, communication, statistical efficiency), and the empirical or theoretical guarantees that practitioners rely on. The sources cited below approach the topic from a mix of these angles.
Foundational references
Hughes, Computer Graphics: Principles and Practice (2013) is a standard reference for this material and is used both as a curriculum anchor and as a long-form survey of techniques. Szeliski, Computer Vision: Algorithms and Applications (2022) is a standard reference for this material and is used both as a curriculum anchor and as a long-form survey of techniques.
Open methodological questions in graphics and vision cluster around how to compose the techniques above under realistic constraints — scale, adversarial inputs, partial observability, and shifting workloads. The cited references give the precise statements, proofs, and empirical evaluations that this overview only sketches; downstream topic pages drill into specific subfields.
Prerequisites
Sources
- textbook · primary · 2013Computer Graphics: Principles and Practicehughes-2013
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In context
Where this topic sits in the prerequisite graph. Click any node to jump.
Explore
- 01
Computer Graphics
Rendering, modeling, and animation of digital images.
- 02
Classical Computer Vision
Non-deep-learning computer vision: geometry, image processing, and classical detection.
- 03
Global Illumination
Physically based simulation of how light propagates, scatters, and accumulates across a scene, including the indirect light that bounces between surfaces and through participating media.
- 04
Human-Computer Interaction
Design and study of how people use computer systems.
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