{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,6]],"date-time":"2025-10-06T18:53:06Z","timestamp":1759776786273,"version":"3.37.3"},"reference-count":15,"publisher":"World Scientific Pub Co Pte Ltd","issue":"09","funder":[{"name":"the Shaanxi Provincial Department of Education Industrialization Cultivation Project","award":["No. 16JF012"],"award-info":[{"award-number":["No. 16JF012"]}]},{"name":"the National Defense Science and Technology Innovation Zone","award":["No. ZT00100728"],"award-info":[{"award-number":["No. ZT00100728"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Patt. Recogn. Artif. Intell."],"published-print":{"date-parts":[[2020,8]]},"abstract":"<jats:p> The traditional information extraction technology of dashboard is easily affected by external factors, and the robustness is poor. To improve the safety of the pilot\u2019s performance on the dashboard, this paper proposes a way for extracting the dashboard feature information in eye tracking, which acquires the line of sight point in simulated dashboard. It then uses the Mask R-CNN method to detect the gaze area and then extracts the target feature information. Finally, it fuses two sets of data to get the result of the pilot who extracts the target gaze area in the scene. Experiment results show that the method of new dashboard information extraction proposed in this paper has a better accuracy. <\/jats:p>","DOI":"10.1142\/s0218001420550174","type":"journal-article","created":{"date-parts":[[2019,9,25]],"date-time":"2019-09-25T10:45:09Z","timestamp":1569408309000},"page":"2055017","source":"Crossref","is-referenced-by-count":4,"title":["Mask R-CNN Method for Dashboard Feature Extraction in Eye Tracking"],"prefix":"10.1142","volume":"34","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4468-3539","authenticated-orcid":false,"given":"Pei","family":"Zhang","sequence":"first","affiliation":[{"name":"Xi\u2019an Technological University, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Changyuan","family":"Wang","sequence":"additional","affiliation":[{"name":"Xi\u2019an Technological University, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hongbo","family":"Jia","sequence":"additional","affiliation":[{"name":"Air Force Medical Center of PLA, Air Force Military Medical University, PLA, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"219","published-online":{"date-parts":[[2020,1,21]]},"reference":[{"first-page":"2858","volume-title":"CVPR","author":"Bai M.","key":"S0218001420550174BIB001"},{"key":"S0218001420550174BIB003","doi-asserted-by":"publisher","DOI":"10.1109\/19.836317"},{"issue":"5","key":"S0218001420550174BIB004","first-page":"50","volume":"2018","author":"Feng W.","year":"2018","journal-title":"Mech. 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