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A Vector-based, Multidimensional Scanpath Similarity Measure

Jarodzka, Halszka; Holmqvist, Kenneth LU and Nyström, Marcus LU (2010) Eye Tracking Research & Applications In [Host publication title missing] p.211-218
Abstract
A great need exists in many fields of eye-tracking research for a robust and general method for scanpath comparisons. Current measures either quantize scanpaths in space (string editing measures like the Levenshtein distance) or in time (measures based on attention maps). This paper proposes a new pairwise scanpath similarity measure. Unlike previous measures that either use AOI sequences or forgo temporal order, the new measure defines scanpaths as a series of geometric vectors and compares temporally aligned scanpaths across several dimensions: shape, fixation position, length, direction, and fixation duration. This approach offers more multifaceted insights to how similar two scanpaths are.

Eight fictitious scanpath pairs are... (More)
A great need exists in many fields of eye-tracking research for a robust and general method for scanpath comparisons. Current measures either quantize scanpaths in space (string editing measures like the Levenshtein distance) or in time (measures based on attention maps). This paper proposes a new pairwise scanpath similarity measure. Unlike previous measures that either use AOI sequences or forgo temporal order, the new measure defines scanpaths as a series of geometric vectors and compares temporally aligned scanpaths across several dimensions: shape, fixation position, length, direction, and fixation duration. This approach offers more multifaceted insights to how similar two scanpaths are.

Eight fictitious scanpath pairs are tested to elucidate the strengths of the new measure, both in itself and compared to two of the currently most popular measures - the Levenshtein distance and attention map correlation. (Less)
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author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
sequence analysis, scanpath, vector, string edit, Levenshtein distance
in
[Host publication title missing]
pages
8 pages
publisher
ACM, New York, NY,
conference name
Eye Tracking Research & Applications
external identifiers
  • scopus:77952526277
language
English
LU publication?
yes
id
7ccdec07-2dc9-45c4-a013-8a73aedd0132 (old id 1539209)
date added to LUP
2010-02-05 21:13:47
date last changed
2017-04-16 04:28:45
@inproceedings{7ccdec07-2dc9-45c4-a013-8a73aedd0132,
  abstract     = {A great need exists in many fields of eye-tracking research for a robust and general method for scanpath comparisons. Current measures either quantize scanpaths in space (string editing measures like the Levenshtein distance) or in time (measures based on attention maps). This paper proposes a new pairwise scanpath similarity measure. Unlike previous measures that either use AOI sequences or forgo temporal order, the new measure defines scanpaths as a series of geometric vectors and compares temporally aligned scanpaths across several dimensions: shape, fixation position, length, direction, and fixation duration. This approach offers more multifaceted insights to how similar two scanpaths are.<br/><br>
Eight fictitious scanpath pairs are tested to elucidate the strengths of the new measure, both in itself and compared to two of the currently most popular measures - the Levenshtein distance and attention map correlation.},
  author       = {Jarodzka, Halszka and Holmqvist, Kenneth and Nyström, Marcus},
  booktitle    = {[Host publication title missing]},
  keyword      = {sequence analysis,scanpath,vector,string edit,Levenshtein distance},
  language     = {eng},
  pages        = {211--218},
  publisher    = {ACM, New York, NY,},
  title        = {A Vector-based, Multidimensional Scanpath Similarity Measure},
  year         = {2010},
}