A Vector-based, Multidimensional Scanpath Similarity Measure
(2010) Eye Tracking Research & Applications 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)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/1539209
- author
- Jarodzka, Halszka ; Holmqvist, Kenneth LU and Nyström, Marcus LU
- organization
- publishing date
- 2010
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- sequence analysis, scanpath, vector, string edit, Levenshtein distance
- host publication
- [Host publication title missing]
- pages
- 8 pages
- publisher
- Association for Computing Machinery (ACM)
- conference name
- Eye Tracking Research & Applications
- conference dates
- 0001-01-02
- external identifiers
-
- scopus:77952526277
- language
- English
- LU publication?
- yes
- id
- 7ccdec07-2dc9-45c4-a013-8a73aedd0132 (old id 1539209)
- date added to LUP
- 2016-04-04 10:43:47
- date last changed
- 2023-01-13 18:31:17
@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]}}, keywords = {{sequence analysis; scanpath; vector; string edit; Levenshtein distance}}, language = {{eng}}, pages = {{211--218}}, publisher = {{Association for Computing Machinery (ACM)}}, title = {{A Vector-based, Multidimensional Scanpath Similarity Measure}}, url = {{https://lup.lub.lu.se/search/files/5608175/1539210.PDF}}, year = {{2010}}, }