The browser you are using is not supported by this website. All versions of Internet Explorer are no longer supported, either by us or Microsoft (read more here: https://www.microsoft.com/en-us/microsoft-365/windows/end-of-ie-support).

Please use a modern browser to fully experience our website, such as the newest versions of Edge, Chrome, Firefox or Safari etc.

A Vector-based, Multidimensional Scanpath Similarity Measure

Author

Summary, in English

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.

Publishing year

2010

Language

English

Pages

211-218

Publication/Series

[Host publication title missing]

Document type

Conference paper

Publisher

Association for Computing Machinery (ACM)

Topic

  • Human Aspects of ICT

Keywords

  • sequence analysis
  • scanpath
  • vector
  • string edit
  • Levenshtein distance

Conference name

Eye Tracking Research & Applications

Conference date

0001-01-02

Status

Published

Research group

  • Crypto and Security