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Yang, Chunhua; Xu, Canhui; Gui, Weihua; Zhou, Kaijun

doi:10.1002/ima.v19:4

Cited by 7 publications

(3 citation statements)

References 195 publications

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“…The detected X and Y positions and Z distance of the user's eye are transferred to the narrow-view camera. With the Z distance and face width measured by the wide-view camera, the optimal parameters of the modeled formula for estimating the Z distance are calculated using a least squares regression method based on the focus lens position, as shown in step (11) [see Sec. The focus score of the captured eye image is calculated in step (6).…”

Section: Proposed Gaze Tracking Systemmentioning

confidence: 99%

“…Equation (11) assumes that z x is the external division point of z m and z t with the ratio ðx − mÞ∶ðx − tÞ. The following method is used to overcome this problem.…”

Section: Updating Focus Data In Lookupmentioning

confidence: 99%

“…Numerous studies have examined characteristics of the human eye, such as research on gaze detection, 1-7 iris recognition, [8][9][10][11][12] and the measurement of eye fatigue. Numerous studies have examined characteristics of the human eye, such as research on gaze detection, 1-7 iris recognition, [8][9][10][11][12] and the measurement of eye fatigue.…”

Section: Introductionmentioning

confidence: 99%

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Auto-focusing method for remote gaze tracking camera

Lee

Cho

et al. 2012

Opt. Eng

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Gaze tracking determines what a user is looking at; the key challenge is to obtain well-focused eye images. This is not easy because the human eye is very small, whereas the required resolution of the image should be large enough for accurate detection of the pupil center. In addition, capturing a user's eye image by a remote gaze tracking system within a large working volume at a long Z distance requires a panning/tilting mechanism with a zoom lens, which makes it more difficult to acquire focused eye images. To solve this problem, a new auto-focusing method for remote gaze tracking is proposed. The proposed approach is novel in the following four ways: First, it is the first research on an auto-focusing method for a remote gaze tracking system. Second by using userdependent calibration at initial stage, the weakness of the previous methods that use facial width in captured image to estimate Z distance between a user and camera, wherein each person has the individual variation of facial width, is solved. Third, the parameters of the modeled formula for estimating the Z distance are adaptively updated using the least squares regression method. Therefore, the focus becomes more accurate over time. Fourth, the relationship between the parameters and the face width is fitted locally according to the Z distance instead of by global fitting, which can enhance the accuracy of Z distance estimation. The results of an experiment with 10,000 images of 10 persons showed that the mean absolute error between the ground-truth Z distance measured by a Polhemus Patriot device and that estimated by the proposed method was 4.84 cm. A total of 95.61% of the images obtained by the proposed method were focused and could be used for gaze detection.

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Section: Proposed Gaze Tracking Systemmentioning

confidence: 99%

“…Equation (11) assumes that z x is the external division point of z m and z t with the ratio ðx − mÞ∶ðx − tÞ. The following method is used to overcome this problem.…”

Section: Updating Focus Data In Lookupmentioning

confidence: 99%