| Budget Amount *help |
¥4,810,000 (Direct Cost: ¥3,700,000、Indirect Cost: ¥1,110,000)
Fiscal Year 2015: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2014: ¥1,950,000 (Direct Cost: ¥1,500,000、Indirect Cost: ¥450,000)
Fiscal Year 2013: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
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| Outline of Final Research Achievements |
This research develops a Gaze Interface for Mobile Devices Operation. (1) Eye gaze vectors are acquired with a single camera attached on a table PC. Although eye gaze vectors in the vertical direction sometimes include errors caused by an eyebrow or an eyelid, those in the horizontal direction are relatively measured correctly. (2) A gaze point is regarded to spread spatially and temporally. An icon selection method based on the distributions of gaze points in spatially and temporally is proposed. Target selections are succeeded extremely about 45% to 85%. (3) A gaze gesture classification method using HMM(Hidden Markov Model) that is capable to be used in low-end gaze tracking devices. Although the gesture classification performance strongly depends on users, it improves performance comparing with a rule-base classification method.
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