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Cited by 371

The DOI matches its Crossref record; 17 of the 17 references it cites were found in a registry or an index.

Starburst: A hybrid algorithm for video-based eye tracking combining feature-based and model-based approaches

Dongheng Li, Winfield, D., Parkhurst, D.J.·2006·2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops
DOI 10.1109/cvpr.2005.531
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Abstract

Knowing the user’s point of gaze has significant potential to enhance current human-computer interfaces, given that eye movements can be used as an indicator of the attentional state of a user. The primary obstacle of integrating eye movements into today’s interfaces is the availability of a reliable, low-cost open-source eye-tracking system. Towards making such a system available to interface designers, we have developed a hybrid eye-tracking algorithm that integrates feature-based and model-based approaches and made it available in an open-source package. We refer to this algorithm as "starburst" because of the novel way in which pupil features are detected. This starburst algorithm is more accurate than pure feature-based approaches yet is signi?cantly less time consuming than pure modelbased approaches. The current implementation is tailored to tracking eye movements in infrared video obtained from an inexpensive head-mounted eye-tracking system. A validation study was conducted and showed that the technique can reliably estimate eye position with an accuracy of approximately one degree of visual angle.

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Metadata

Authors
Li, D., Winfield, D., & Parkhurst, D. J.
Venue
2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops
Publisher
IEEE
Published
2006-01-05
Volume
3
Pages
79-79
ISSN
2160-7508 (ISSN-L)
DOI
10.1109/cvpr.2005.531
OpenAlex
W2107956149
Cited by
371
References
17
FWCI
8.39
Type
conference paper
Language
en
Open access
closed

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CoChat. (2026). Citation check: Starburst: A hybrid algorithm for video-based eye tracking combining feature-based and model-based approaches. https://app.cochat.ai/papers/10.1109/cvpr.2005.531
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Li, D., Winfield, D., & Parkhurst, D. J. (2006). Starburst: A hybrid algorithm for video-based eye tracking combining feature-based and model-based approaches. 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops. https://doi.org/10.1109/cvpr.2005.531

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