The Viola-Jones face detection algorithm is based around the use of which type of features?

- SIFT features
- ORB features
- Edges detected using Canny's edge detector
Haar features

Which of the following techniques is "eigenfaces" built on?

- Convolutional Neural Network
- Linear Discriminant Analysis
Principal Component Analysis

- Support Vector Machine

What is covariance?

- A pair of images having dissimilar variances
- Another name for cross-correlation
A measure of the similarity of variations in the images

- A pair of images having similar variances

Faces are allegedly more attractive if:

The shape matches the golden ratio

- The lips are oval in shape
- The hair and skin are in the same region in HSV space
- Facial features are slightly asymmetrical

Why is the integral image representation used in Viola-Jones?

- It allows features to be concatenated into a feature vector
- It stores where faces lie in an image
It allows Haar features to be calculated in constant time

- It stores the sum of all the pixels in an image

What does Principal Component Analysis (PCA), as used in eigenfaces, do?

- Splits up features into components
- Finds the most important direction in an image
- Finds the most similar set of features in a database
Finds the directions in feature space with the largest variations

What is Affective Computing?

- A face recognition algorithm
- A way of performing computer vision that is more accurate
Taking into account the emotional state of the user

- A way of recognising facial expressions

What are Haar features?

- The sum of differences between a pair of images
- Measures of the number of edges in a region
- The number of corners in a region
Differences between the sums of pixels in rectangular regions

How is Principal Component Analysis performed?

- By Linear Discriminant Analysis of the variance of an image
- By Eigen decomposition of the variance of an image
- By Linear Discriminant Analysis of the covariance matrix
By Eigen decomposition of the covariance matrix

What is Adaptive Boosting?

- A method for improving the performance of a single weak classifier
- A way of improving the contrast of an image based on the local grey levels
A method for combining multiple weak classifiers into one strong classifier

- An adaptive way of choosing the best single classifier for a task