In vision, it is very common to solve linear systems of the form A · X = 0, with A ∈ IRn×m  contains known values and X ∈ IRm is a vector of parameters, with n >> m. They are solved by minimizing ||A · X|| such that ||X|| = 1. Why not use a standard regression formula with the pseudo-inverse instead?

In this section, we are trying to estimate the illumination pattern of a narrow-beam led in an image. We consider an image as a 2D function I(x, y) ∈ IR, and we consider that the illumination pattern can be modelled as

Having extracted the inliers, explain how regression can be used to compute the least-square fit of (a, b, c, d) to the data. This question can be answered independently of the previous ones.

The translation of ” Marc a voyagé en France le weekend dernier” is “Marc traveled to France last weekend”

When doing a linear regression to fit a function y = ax2 + bx + c on n pairs of points (Xi,Yi), what is the cost function we are minimizing?

Aller is an ÊTRE verb

Name the organelle where ribosomal RNA synthesis takes place? (Note: This is a one-word answer, not an essay)

The translation of  “Il est resté avec sa copine hier” is ” He rested with his friend yesterday”

Manger is an ÊTRE verb

Which of the following is a polysaccharide used by animals for energy storage?