Rapid detection of targets from complex backgrounds based on eye-tracking data

Yichuan Jiang; Xinyu Chen; Hui Liu; Yue Leng; Yuankui Yang; Pan Lin; Junfeng Gao; Ruiming Wang; Keiji Iramina; Sheng Ge

doi:10.1145/3207677.3278051

Rapid detection of targets from complex backgrounds based on eye-tracking data

Yichuan Jiang, Xinyu Chen, Hui Liu, Yue Leng, Yuankui Yang, Pan Lin, Junfeng Gao, Ruiming Wang, Keiji Iramina, Sheng Ge

Intelligence Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

In this study¹, we used a remote eye-tracker in a head-free setting to measure target detection in visual scenes. Participants underwent two kinds of tasks that were designed to simulate different situations and to study the validity and accuracy of the remote eye-tracking system. We found that the average target detection rate in the simulation task reached 88.95%, whereas in the real scene task the average accuracy was 83.20%. Our results show that the remote eye-tracker possesses enough precision to be used for the measurement of target detection in complex visual scenes.

Original language	English
Title of host publication	Proceedings of 2nd International Conference on Computer Science and Application Engineering, CSAE 2018
Editors	Ali Emrouznejad
Publisher	Association for Computing Machinery
ISBN (Electronic)	9781450365123
DOIs	https://doi.org/10.1145/3207677.3278051
Publication status	Published - Oct 22 2018
Event	2nd International Conference on Computer Science and Application Engineering, CSAE 2018 - Hohhot, China Duration: Oct 22 2018 → Oct 24 2018

Publication series

Name	ACM International Conference Proceeding Series

Other

Other	2nd International Conference on Computer Science and Application Engineering, CSAE 2018
Country/Territory	China
City	Hohhot
Period	10/22/18 → 10/24/18

All Science Journal Classification (ASJC) codes

Software
Human-Computer Interaction
Computer Vision and Pattern Recognition
Computer Networks and Communications

Access to Document

10.1145/3207677.3278051

Cite this

Jiang, Y., Chen, X., Liu, H., Leng, Y., Yang, Y., Lin, P., Gao, J., Wang, R., Iramina, K., & Ge, S. (2018). Rapid detection of targets from complex backgrounds based on eye-tracking data. In A. Emrouznejad (Ed.), Proceedings of 2nd International Conference on Computer Science and Application Engineering, CSAE 2018 Article a116 (ACM International Conference Proceeding Series). Association for Computing Machinery. https://doi.org/10.1145/3207677.3278051

Rapid detection of targets from complex backgrounds based on eye-tracking data. / Jiang, Yichuan; Chen, Xinyu; Liu, Hui et al.
Proceedings of 2nd International Conference on Computer Science and Application Engineering, CSAE 2018. ed. / Ali Emrouznejad. Association for Computing Machinery, 2018. a116 (ACM International Conference Proceeding Series).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Jiang, Y, Chen, X, Liu, H, Leng, Y, Yang, Y, Lin, P, Gao, J, Wang, R, Iramina, K & Ge, S 2018, Rapid detection of targets from complex backgrounds based on eye-tracking data. in A Emrouznejad (ed.), Proceedings of 2nd International Conference on Computer Science and Application Engineering, CSAE 2018., a116, ACM International Conference Proceeding Series, Association for Computing Machinery, 2nd International Conference on Computer Science and Application Engineering, CSAE 2018, Hohhot, China, 10/22/18. https://doi.org/10.1145/3207677.3278051

Jiang Y, Chen X, Liu H, Leng Y, Yang Y, Lin P et al. Rapid detection of targets from complex backgrounds based on eye-tracking data. In Emrouznejad A, editor, Proceedings of 2nd International Conference on Computer Science and Application Engineering, CSAE 2018. Association for Computing Machinery. 2018. a116. (ACM International Conference Proceeding Series). doi: 10.1145/3207677.3278051

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abstract = "In this study1, we used a remote eye-tracker in a head-free setting to measure target detection in visual scenes. Participants underwent two kinds of tasks that were designed to simulate different situations and to study the validity and accuracy of the remote eye-tracking system. We found that the average target detection rate in the simulation task reached 88.95%, whereas in the real scene task the average accuracy was 83.20%. Our results show that the remote eye-tracker possesses enough precision to be used for the measurement of target detection in complex visual scenes.",

author = "Yichuan Jiang and Xinyu Chen and Hui Liu and Yue Leng and Yuankui Yang and Pan Lin and Junfeng Gao and Ruiming Wang and Keiji Iramina and Sheng Ge",

note = "Funding Information: This work was supported by the National Basic Research Program of China (2015CB351704), the National Nature Science Foundation of China (61473221, 31500881, 61773408, 81271659), and the Fundamental Research Funds for the Southeast University.; 2nd International Conference on Computer Science and Application Engineering, CSAE 2018 ; Conference date: 22-10-2018 Through 24-10-2018",

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doi = "10.1145/3207677.3278051",

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AU - Gao, Junfeng

AU - Wang, Ruiming

AU - Iramina, Keiji

AU - Ge, Sheng

N1 - Funding Information: This work was supported by the National Basic Research Program of China (2015CB351704), the National Nature Science Foundation of China (61473221, 31500881, 61773408, 81271659), and the Fundamental Research Funds for the Southeast University.

PY - 2018/10/22

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N2 - In this study1, we used a remote eye-tracker in a head-free setting to measure target detection in visual scenes. Participants underwent two kinds of tasks that were designed to simulate different situations and to study the validity and accuracy of the remote eye-tracking system. We found that the average target detection rate in the simulation task reached 88.95%, whereas in the real scene task the average accuracy was 83.20%. Our results show that the remote eye-tracker possesses enough precision to be used for the measurement of target detection in complex visual scenes.

AB - In this study1, we used a remote eye-tracker in a head-free setting to measure target detection in visual scenes. Participants underwent two kinds of tasks that were designed to simulate different situations and to study the validity and accuracy of the remote eye-tracking system. We found that the average target detection rate in the simulation task reached 88.95%, whereas in the real scene task the average accuracy was 83.20%. Our results show that the remote eye-tracker possesses enough precision to be used for the measurement of target detection in complex visual scenes.

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Rapid detection of targets from complex backgrounds based on eye-tracking data

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