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Assessment Guide

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title: Assessment Guide (Machine Vision)


A final version of this exam will be published before the teaching
term ends.

# Overview

1. The exam is viva voce.
2. **Duration** Normally 20 min. May extend up to a maximum of 30 min.
3. The student manages the first seven minutes of the exam to make their
case to demonstrate that the learning outcomes have been achieved.
4.  The student is free to bring any material desired to serve as a
demonstration.  However,
    + having developed a product is not sufficient.
    + The candidate has to demonstrate that they understand how to
      develop the product.  See below for elaboration.
    + This is both because depth understanding is a learning objective
      in itself, and because we cannot otherwise know if the student
      has developed the demo themselves.
5. The remaining 2/3 of the exam is for further questions from the
examiners to make sure that all the learning outcomes are covered.

# Learning outcomes

The assessment is made with respect to the learning outcomes from the
[Module Description](, as follows (with numbering added).

The candidate can explain fundamental mathematical models for digital imaging, 3D models, and machine vision

The candidate are aware of the principles of digital cameras and image capture

The candidate can implemented selected techniques for object recognition and tracking

The candidate can calibrate cameras for use in machine vision systems

The candidate has a good analytic understadning of machine vision and of the collaboration between machine vision and other systems in robotics

The candidate can exploit the connection between theory and application for presenting and discussing engineering problems and solutions

# Interpretation of Grades and Learning Outcomes

## The Grade C

The Grade **C** represents 
solid working knowledge of the most important techniques in the syllabus.
This includes

1.  Sufficient knowledge to be able to implement and use the technique.
2.  Sufficient theoretical understanding to vary the techniques and 
    adapt them to different use cases, including but not limited to
    parameter tuning. (C2)
3.  Sufficient theoretical understanding to explain when and why the
    technique is appropriate. (K1, C1)

Which techniques are most important may be subject to opinion, but the
following has a good case,

1.  Feature tracking - i.e. identification of objects in a video, and
    tracking of these objects across several frames. 
2.  Calculation of relative pose, triangulation, and 3D reconstruction.
    **TODO** The wording needs review.

A student who merits a C can be trusted to implement these techniques
correctly in a project without close supervision.

Students who have focused on other techniques which are important for
their own education, may choose to focus on them, as long as

+ they are taken from the syllabus, possibly extended with other sources.
+ they constitute a similar volume and challenge as the above.
+ they address the learning outcomes (S1, C2, K1, C2) as mentioned above.

The student also needs a cursory understanding of the remaining
learning outcomes (K2, S2).

We respect that some students may have a more practical, and others
a more theoretical understanding of the technology, and that both may
merit the same grade.  The **C** Grade is a broad category. 

## The Grade A (and B)

The Grade **A** represent broad and deep understanding
of all the material discussed in the module.
This includes the requirements for a **C**, and additionally the
**A** student has

1.  working knowledge of additional techniques from the syllabus.
2.  solid understanding of learning outcome K2 and S2.
3.  deeper and more complete understanding of the underlying theory
    than we expect for a **C**

To merit an **A** the candidate has to impress and surprise.
The performance has to *clearly outstanding*, as it says in the
nationaly guidelines:

> An excellent performance, clearly outstanding.
The candidate demonstrates excellent
judgement and a very high degree of independent thinking. 

The Grade **B** is an intermediate grade.  The candidate demonstrates
some features of an **A** and thus exceed the expectations for a **C**,
but they do not have to be `clearly outstanding'.

## The Grade E (and D)

Grades below **C** represents working knowledge which can possibly
be of value in a development team, but not sufficient for the candidate
to be trusted to carry out independent work.  

As for the **C**, the candidate has to

+ demonstrate working knowledge of the most important techniques
  in the syllabus, 
+ be aware of most of features that require tuning and adaptation
  in practical situation.

Unlike the **C**, a certain awareness of the underlying theory 
suffices.  This is not expected to suffice to adapt and justify
solutions to practical uses beyond routine problems.