ASTEF: A simple tool for examining fixations

Fixation identification: The optimum threshold for a dispersion algorithm

“…Figure 1B shows the same board with the pieces removed in order to reduce cluttering and improve visibility of the PORs. It is clear that the PORs are grouped together and that these clusters could possibly be identified by a human observer tations thereof are discussed in Camilli et al (2008), Salvucci and Goldberg (2000), Shic et al (2008), and Urruty et al (2007). The algorithm utilizes the fact that fixation points, because of their low velocity, tend to cluster close together.…”

“…This algorithm is quite robust with regard to identified fixation sequences, as opposed to other algorithms; for example, velocity-based algorithms may produce inconsistent results at or near threshold values (Salvucci & Goldberg, 2000) or at slow eye movements gested in the past (Kumar, Klingner, Puranik, Winograd, & Paepcke, 2008;Santella & DeCarlo, 2004;Urruty, Lew, Ihadaddene, & Simovici, 2007). Also, several tools exist that employ these algorithms (Camilli, Nacchia, Terenzi, & Di Nocera, 2008;Eyenal, 2001;Gitelman, 2002;Heminghous & Duchowski, 2006;Salvucci, 2000;Spakov & Miniotas, 2007;Tobii Technology AB, 2008).…”

“…Fixations are identified as groups of consecutive PORs within a particular dispersion or maximum separation. The dispersion can be measured in terms of the distance between points in the fixation that are the farthest apart (Salvucci & Goldberg, 2000), the distance between any two points (Shic et al, 2008;Spakov & Miniotas, 2007), the distance between points and the center of the fixation (Camilli et al, 2008;Shic et al, 2008), the standard deviation of the x-and y-coordinates (Anliker, 1976;Eyenal, 2001), or a minimum spanning tree of the points in a fixation (Salvucci & Goldberg, 2000;Urruty et al, 2007).…”

“…The dispersion threshold algorithm was originally proposed by Widdel (1984), and adaptations and implemen- Gordon, 2003), and the dispersion threshold should include 0.5º-1º of visual angle (Camilli et al, 2008;Eyenal, 2001;Jacob & Karn, 2003;Salvucci & Goldberg, 2000).…”

GazeAlyze: a MATLAB toolbox for the analysis of eye movement data

“…A very well-designed application is OGAMA (Vosskuhler, Nordmeier, Kuchinke, & Jacobs, 2008), which allows the analysis of gaze and mouse movement data together and the recording and storage of data in a Structured Query Language (SQL) database. The other C#-based software is ASTEF (Camilli, Nacchia, Terenzi, & Di Nocera, 2008), an easy-to-use tool for the investigation of fixations that implements the nearest neighbor Index as a measure of the spatial dispersion of the fixation distribution.…”