3D Gaze Tracking and Analysis for Attentive Human Computer Interaction

Ki, Jeongseok; Kwon, Yong-Moo; Sohn, Kwanghoon

doi:10.1109/fbit.2007.15

Cited by 7 publications

(2 citation statements)

References 6 publications

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“…Based on their practical applications, these studies can be further divided into two groups: stereo displays and gazes in 3D. With regard to stereo displays, Ki et al [12], [13] proposed using a method of generating glints in pupil images using a pair of infrared LEDs and calculating the gaze from the observed glints in combination with the center positions of both pupils. Wang et al [14] proposed a method of estimating depth by mapping a stereoscopic screen based on triangulation.…”

Section: Introductionmentioning

confidence: 99%

An Eye-Tracker-Based 3D Point-of-Gaze Estimation Method Using Head Movement

Pichitwong

Chamnongthai

2019

IEEE Access

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Eye trackers are currently used to sense the positions of both the centers of the pupils and the point-of-gaze (POG) position on a screen, in keeping with the original objective for which they were designed; however, it remains difficult to measure the positions of three-dimensional (3D) POGs. This paper proposes a method for 3D gaze estimation by using head movement, pupil position data, and POGs on a screen. The method assumes that a person, usually unintentionally, moves his or her head a short distance such that multiple straight lines can be drawn from the center point between the two pupils to the POG. When the person is continuously focusing on a given 3D POG while moving, these lines represent the lines of sight that intersect at a 3D POG . That 3D POG can, therefore, be found from the intersection of several lines of sight formed by head movements. To evaluate the performance of the proposed method, experimental equipment was constructed, and experiments with five male and five female participants were performed in which the participants looked at nine test points in a 3D space for approximately 20 s each. The experimental results reveal that the proposed method can measure 3D POGs with average distance errors of 13.36 cm, 7.58 cm, 5.72 cm, 3.97 cm, and 3.52 cm for head movement distances of 1 cm, 2 cm, 3 cm, 4 cm, and 5 cm, respectively.INDEX TERMS 3D gaze estimation, gaze tracking, eye tracker.

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Section: Introductionmentioning

confidence: 99%

An Eye-Tracker-Based 3D Point-of-Gaze Estimation Method Using Head Movement

Pichitwong

Chamnongthai

2019

IEEE Access

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“…The combination of the 3D face tracking and the pose estimation is useful in various fields. For example, the gaze estimation, the Autostereoscopic based on viewer tracking [3], monitoring driver [4]. CLMs detect peak in patch.…”

Section: Introductionmentioning

confidence: 99%

Face Alignment for Robust to Background and Occlusion Using Variation of 3D Reference Shape

Kang

2013

AMR

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A Constrained Local Models is face tracking method based on variation of shape in the Allowable Shape Domain. The CLMs perform optimize strategy in patch. It has problem because occlusion and background. In this paper, variation of shape is constrained for solving this problem.The generating of shape allows only shape adjusted translation, rotation, scale. The proposed method prevent that the shape generate to abnormal forms. As a result, the alignment error is about 4.2 pixels in environment has complex background. Also, when part of the face occluded, the alignment error is about 18.1pixels.

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