Skip to main content

Lund University Publications


A new method for comparing scanpaths based on vectors and dimensions

Dewhurst, Richard LU ; Jarodzka, Halszka ; Holmqvist, Kenneth LU ; Foulsham, Tom and Nyström, Marcus LU (2011) Vision Sceinces Society
Please use this url to cite or link to this publication:
; ; ; and
publishing date
Contribution to conference
publication status
Eye movements, Cognition, Scanpaths
conference name
Vision Sceinces Society
conference dates
LU publication?
additional info
We make different sequences of eye movements—or scanpaths—depending on what we are viewing and the current task we are carrying out (e.g. Land, Mennie & Rusted, 1999). In recent years, research efforts have been very informative in identifying commonalities between scanpath pairs, allowing us to quantify, for example, the similarity in eye movement behaviour between experts and novices (Underwood, Humphrey & Foulsham, 2008), or between encoding and recognition of the same image (Foulsham & Underwood, 2008). However, common methods for comparing scanpaths (e.g. ‘string-edit’, based on Levenshtein, 1966, or ‘positon measures’, see Mannan, Ruddock & Wooding, 1995) fail to capture both the spatial and temporal aspects of scanpaths. Even the newest techniques (e.g. ‘Scanmatch’, Cristino, Mathôt, Theeuwes & Gilchrist, 2010) are restricted by the fact that they rely on the division of space into Areas of Interest (AOIs), thus limiting the spatial resolution of the similarity metric produced. Here we validate a new algorithm for comparing scanpaths (Jarodzka, Holmqvist & Nyström, 2010) with eye movement data from human observers. Instead of relying on the quantization of space into AOIs, our method represents scanpaths as geometrical vectors, which retain temporal order and spatial position. Scanpaths are then compared across several dimensions—shape, position, length, direction, and duration—and a similarity value is returned for each. Using this new multidimensional approach, our data from two experiments highlights aspects of scanpath similarity which cannot otherwise be quantified: when scanpaths are clearly similar, but are spatially downscaled, for instance. Moreover, we show how scanpath similarity changes depending on task, using our algorithm in comparison to the most popular alternatives. This data demonstrates that our vector-based multi-dimensional approach to scanpath comparison is favorable to others, and should encourage a shift away from methods which are rooted in the Levenstein principle or spatial position alone.
e3b0f520-4ab3-481a-86ed-3824cd93b96d (old id 1971178)
date added to LUP
2016-04-04 14:41:27
date last changed
2018-11-21 21:21:44
  author       = {Dewhurst, Richard and Jarodzka, Halszka and Holmqvist, Kenneth and Foulsham, Tom and Nyström, Marcus},
  language     = {eng},
  title        = {A new method for comparing scanpaths based on vectors and dimensions},
  year         = {2011},