Explore geometric measurement and reconstruction using a single-camera configuration and explicit assumptions.
Learners investigate how image information, calibration, and geometric constraints can support a scoped reconstruction problem. The project emphasizes what can and cannot be inferred from a chosen camera setup, how measurement error is evaluated, and how a reproducible workflow is documented.
Proposed learning outcomes for this program example:
The sequence below illustrates how this program’s content can be organized. Topics, pacing, and project depth are adapted for each offering. This is not an archived record of a specific cohort’s weekly syllabus.
Connect computer vision, machine learning, and physical modeling through a focused engineering research question.
Explore data-driven approaches to manufacturing defects, prediction, and process-quality questions.
Model hybrid energy systems and explore how data and optimization inform system design and operation.