Mathematics Bridge
The linear algebra, calculus, and probability used throughout the course, with attention to units and conditioning.
Key Terms
Vectors & MatricesSVDLeast SquaresTaylor ExpansionProbabilityUnits & Normalization
Python Tools
NumPySciPyMatplotlib
Textbook Reference
Szeliski App.AHartley & Zisserman App.A
Topics Covered
- 1Vector and matrix operations, rank, null space, and orthogonality
- 2Singular value decomposition and its geometric interpretation
- 3Linear and homogeneous least squares, normal equations, and conditioning
- 4First- and second-order Taylor expansion for local approximation
- 5Probability essentials, Gaussians, covariance, and the role of units and normalization
Learning Outcomes
- Use SVD to solve least-squares and homogeneous systems that arise in vision
- Apply Taylor expansion to derive local models of image and geometric functions
- Track units and apply normalization to keep estimation problems well-conditioned
Lecture PDFs
Mathematics Bridge
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