HCL_AOIs

This dataframe contains three rectangular areas of interest (AOIs), set out for use with the HCL dataset.
Values are in pixels.

datasets

Enables the automation of actions across the pipeline, including
initial steps of transforming binocular data and gap repair to event-based
processing such as fixations, saccades, and entry/duration in Areas of
Interest (AOIs). It also offers visualisation of eye movement and AOI
entries. These tools take relatively raw (trial, time, x, and y form) data
and can be used to return fixations, saccades, and AOI entries and time spent
in AOIs. As the tools rely on this basic data format, the functions can work
with data from any eye tracking device. Implements fixation and saccade
detection using methods proposed by Salvucci and Goldberg (2000)
<doi:10.1145/355017.355028>.

Tom Beesley

eyetools

Analyse Eye Data

Matthew Ivory

HCL_AOIs function

A data frame with 3 rows and 4 variables:<dl>
<dt>x</dt>
<dd>centred x coordinate of the AOI</dd><dt>y</dt>
<dd>centred y coordinate of the AOI</dd><dt>width_radius</dt>
<dd>either the width of the AOI, or the radius for circular AOIs</dd><dt>height</dt>
<dd>the height of the AOI; should be NA for circular AOIs</dd>...</dl>

Format

Example AOIs for use with HCL — HCL_AOIs

A data frame with 3 rows and 4 variables:<dl>
<dt>x</dt>
<dd>centred x coordinate of the AOI</dd>

<dt>y</dt>
<dd>centred y coordinate of the AOI</dd>

<dt>width_radius</dt>
<dd>either the width of the AOI, or the radius for circular AOIs</dd>

<dt>height</dt>
<dd>the height of the AOI; should be NA for circular AOIs</dd>

...

</dl>

HCL_AOIs: Example AOIs for use with HCL

Description

Usage

Arguments

Format