Fixation identification in centroid versus start-point modes using eye-tracking data
Fixation-identification algorithms, needed for analyses of eye movements, may typically be separated into three categories, viz. (i) velocity-based algorithms, (ii) area-based algorithms, and (iii) dispersion-based algorithms. Dispersion-based algorithms are commonly used but this application introd...
| Main Authors: | , , , , |
|---|---|
| Format: | Journal Article |
| Published: |
Ammons Scientific Ltd.
2008
|
| Online Access: | http://hdl.handle.net/20.500.11937/30165 |
| _version_ | 1848753010310643712 |
|---|---|
| author | Falkmer, Torbjorn Dahlman, J. Dukic, T. Bjällmark, A. Larsson, M. |
| author_facet | Falkmer, Torbjorn Dahlman, J. Dukic, T. Bjällmark, A. Larsson, M. |
| author_sort | Falkmer, Torbjorn |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Fixation-identification algorithms, needed for analyses of eye movements, may typically be separated into three categories, viz. (i) velocity-based algorithms, (ii) area-based algorithms, and (iii) dispersion-based algorithms. Dispersion-based algorithms are commonly used but this application introduces some difficulties, one being optimization. Basically, there are two modes to reach this goal of optimization, viz., the start-point mode and the centroid mode. The aim of the present study was to compare and evaluate these two dispersion-based algorithms. Manual inspections were made of 1,400 fixations in each mode. Odds ratios showed that by using the centroid mode for fixation detection, a valid fixation is 2.86 times more likely to be identified than by using the start-point mode. Moreover, the algorithm based on centroid mode dispersion showed a good interpretation speed, accuracy, robustness, and ease of implementation, as well as adequate parameter settings. © Perceptual and Motor Skills 2008. |
| first_indexed | 2025-11-14T08:17:43Z |
| format | Journal Article |
| id | curtin-20.500.11937-30165 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T08:17:43Z |
| publishDate | 2008 |
| publisher | Ammons Scientific Ltd. |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-301652017-09-13T15:31:39Z Fixation identification in centroid versus start-point modes using eye-tracking data Falkmer, Torbjorn Dahlman, J. Dukic, T. Bjällmark, A. Larsson, M. Fixation-identification algorithms, needed for analyses of eye movements, may typically be separated into three categories, viz. (i) velocity-based algorithms, (ii) area-based algorithms, and (iii) dispersion-based algorithms. Dispersion-based algorithms are commonly used but this application introduces some difficulties, one being optimization. Basically, there are two modes to reach this goal of optimization, viz., the start-point mode and the centroid mode. The aim of the present study was to compare and evaluate these two dispersion-based algorithms. Manual inspections were made of 1,400 fixations in each mode. Odds ratios showed that by using the centroid mode for fixation detection, a valid fixation is 2.86 times more likely to be identified than by using the start-point mode. Moreover, the algorithm based on centroid mode dispersion showed a good interpretation speed, accuracy, robustness, and ease of implementation, as well as adequate parameter settings. © Perceptual and Motor Skills 2008. 2008 Journal Article http://hdl.handle.net/20.500.11937/30165 10.2466/PMS.106.3.710-724 Ammons Scientific Ltd. restricted |
| spellingShingle | Falkmer, Torbjorn Dahlman, J. Dukic, T. Bjällmark, A. Larsson, M. Fixation identification in centroid versus start-point modes using eye-tracking data |
| title | Fixation identification in centroid versus start-point modes using eye-tracking data |
| title_full | Fixation identification in centroid versus start-point modes using eye-tracking data |
| title_fullStr | Fixation identification in centroid versus start-point modes using eye-tracking data |
| title_full_unstemmed | Fixation identification in centroid versus start-point modes using eye-tracking data |
| title_short | Fixation identification in centroid versus start-point modes using eye-tracking data |
| title_sort | fixation identification in centroid versus start-point modes using eye-tracking data |
| url | http://hdl.handle.net/20.500.11937/30165 |