• Journal of the Ergonomics Society of Korea
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• v.34 no.1
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• pp.19-27
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• 2015

Objective: The aim of this study is to investigate how well eye movement times in visual target selection tasks by an eye input device follows the typical Fitts' Law and to compare vertical and horizontal eye movement times. Background: Typically manual pointing provides excellent fit to the Fitts' Law model. However, when an eye input device is used for the visual target selection tasks, there were some debates on whether the eye movement times in can be described by the Fitts' Law. More empirical studies should be added to resolve these debates. This study is an empirical study for resolving this debate. On the other hand, many researchers reported the direction of movement in typical manual pointing has some effects on the movement times. The other question in this study is whether the direction of eye movement also affects the eye movement times. Method: A cursor movement times in visual target selection tasks by both input devices were collected. The layout of visual targets was set up by two types. Cursor starting position for vertical movement times were in the top of the monitor and visual targets were located in the bottom, while cursor starting positions for horizontal movement times were in the right of the monitor and visual targets were located in the left. Results: Although eye movement time was described by the Fitts' Law, the error rate was high and correlation was relatively low ($R^2=0.80$ for horizontal movements and $R^2=0.66$ for vertical movements), compared to those of manual movement. According to the movement direction, manual movement times were not significantly different, but eye movement times were significantly different. Conclusion: Eye movement times in the selection of visual targets by an eye-gaze input device could be described and predicted by the Fitts' Law. Eye movement times were significantly different according to the direction of eye movement. Application: The results of this study might help to understand eye movement times in visual target selection tasks by the eye input devices.

• Journal of Multimedia Information System
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• v.7 no.1
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• pp.11-16
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• 2020

Deep Learning has become the most important technology in the field of artificial intelligence machine learning, with its high performance overwhelming existing methods in various applications. In this paper, an interactive window service based on object recognition technology is proposed. The main goal is to implement an object recognition technology using this deep learning technology to remove the existing eye tracking technology, which requires users to wear eye tracking devices themselves, and to implement an eye tracking technology that uses only usual cameras to track users' eye. We design an interactive system based on efficient eye detection and pupil tracking method that can verify the user's eye movement. To estimate the view-direction of user's eye, we initialize to make the reference (origin) coordinate. Then the view direction is estimated from the extracted eye pupils from the origin coordinate. Also, we propose a blink detection technique based on the eye apply ratio (EAR). With the extracted view direction and eye action, we provide some augmented information of interest without the existing complex and expensive eye-tracking systems with various service topics and situations. For verification, the user guiding service is implemented as a proto-type model with the school map to inform the location information of the desired location or building.

• Journal of Broadcast Engineering
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• v.26 no.6
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• pp.748-757
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• 2021

In this paper, we propose a gaze estimation network in which eye landmark position detection and gaze direction vector estimation are integrated into one deep learning network. The proposed network uses the Stacked Hourglass Network as a backbone structure and is largely composed of three parts: a landmark detector, a feature map extractor, and a gaze direction estimator. The landmark detector estimates the coordinates of 50 eye landmarks, and the feature map extractor generates a feature map of the eye image for estimating the gaze direction. And the gaze direction estimator estimates the final gaze direction vector by combining each output result. The proposed network was trained using virtual synthetic eye images and landmark coordinate data generated through the UnityEyes dataset, and the MPIIGaze dataset consisting of real human eye images was used for performance evaluation. Through the experiment, the gaze estimation error showed a performance of 3.9, and the estimation speed of the network was 42 FPS (Frames per second).

• The Korean Journal of Physiology
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• v.22 no.1
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• pp.79-88
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• 1988

The effect of cervical proprioceptors on the control of eye movement and body posture was examined in unanesthetized labyrinthine intact and bilateral labyrinthectomized cats. Cervico-ocular reflex(COR) was elicited by stimulation of the cervical proprioceptors by means of sinusoidal rotation of head or body in the darkness. The following results were obtained: 1) In labyrinthine intact cats, sinusoidal rotation of the whole body elicited compensatory eye movement(vestibulo-ocular reflex: VOR); the direction of eye movement was opposite to the direction of head rotation. 2) Anticompensatory eye movement was observed by sinusoidal rotation of the body with head fixed in labyrinthine intact cats; the direction of eye movement was the same as the direction of head rotation. 3) Compensatory eye movement was observed by sinusoidal rotation of the head with body fixed or sinusoidal rotation of the body with head fixed in both acute and chronic bilateral labyrinthectomized cats. These results suggest that the cervical proprioceptors are important in the control of ocular movement and posture in the bilateral labyrintectomized cats, although they are questionable in labyrinthine intact cats.

• The Journal of Korean Physical Therapy
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• v.27 no.1
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• pp.50-54
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• 2015

Purpose: The purpose of this study is to investigate differences of cervical flexor muscle thickness (i.e., sternocleidomastoid muscle and deep cervical flexor muscles) depending on levels of pressure bio-feedback unit and eye directions during cranial-cervical flexor exercise in healthy subjects. Methods: A total of 30 subjects (12 males and 18 females) who had no medical history related to musculoskeletal and neurological disorders were enrolled in this study. They were instructed to perform cranial-cervical flexion exercise with adjustment of five different pressures (i.e., 22 mmHg, 24 mmHg, 26 mmHg, 28 mmHg, and 30 mmHg) using a pressure biofeedback unit, according to three different eye directions (i.e., $0^{\circ}$, $20^{\circ}C$, and $40^{\circ}C$). Muscle thickness of sternocleidomastoid muscle and deep cervical flexor muscles was measured according to pressure levels and eye directions using ultrasonography. Results: In results of muscle thickness in sternocleidomastoid muscle and deep cervical flexor muscles, the thickness of those muscles was gradually increased compared to the baseline pressure level (22 mmHg), as levels in the pressure biofeedback unit during cranial-cervical flexion exercise were increasing. In addition, at the same pressure levels, muscle thickness was increased depending on ascending eye direction. Conclusion: Our findings showed that muscle thickness of sternocleidomastoid muscle and deep cervical flexor muscles was generally increased during cranial-cervical flexion exercise, according to increase of eye directions and pressure levels. Therefore, we suggested that lower eye direction could induce more effective muscle activity than the upper eye direction in the same environment during cranial-cervical flexion exercise.

• Journal of Korean Ophthalmic Optics Society
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• v.17 no.2
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• pp.177-184
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• 2012

Purpose: In this study, the effect of the eye movement direction on visual function related to accommodation was investigated when playing computer games for a certain period of time. Methods: Total 60 subjects in 20s who had the visual acuity of 1.0 or higher without any ocular disease and accommodative dysfunction were asked to play computer games separately in horizontal and vertical directions for 40 and 90 minutes and then measured their accommodative amplitude, accommodative facility, accommodative lag and relative accommodations. Thevisual function when not doing the computer game was regarded as a control value, and further compared and analyzed. Results: The accommodative amplitude, accommodative facility, accommodative lag and relative accommodations showed the tendency of decrease after the computer game for 40 minutes, and more reduced values of the visual functions were shown when the computer game extended up to 90 minutes except positive relative accommodation. Positive relative accommodation had a tendency to increase slightly after the computer game for 90 minutes. Meanwhile, the change of the visual functions was primarily influenced by the eye movement in horizontal direction rather than by the eye movement in vertical direction during computer game when analyzed by the direction of eye movement. Conclusions: Over all accommodative functions tended to decrease with the extended VDT working time by computer game, and the frequent eye movement in horizontal direction during VDT tasks could be the main cause of eyestrain since the eye movement in horizontal direction rather than vertical direction significantly affected the change of accommodative function.

• Journal of Korean Ophthalmic Optics Society
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• v.14 no.2
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• pp.31-34
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• 2009

Purpose: We are to analyze optically how to affect the eye related with movement of the iris. Methods: Using the schematic eye to have the crystalline lens of the radial GRIN and the spherical GRIN forms that come to be planned in existing, the iris centre was moved 0.5 mm with nasal direction in order to be identical with the real eye. Also, considering that the iris centre move according to increase of the pupil size, the iris centre was moved 0.4 mm with temporal direction to analyze the optical performance change of the eye respectively. Results: Because of decrease in the spherical aberration, the schematic eye with nasal direction 0.5 mm eccentricity of the iris showed a different consequence plentifully compared with the performance of the real eye. Besides, the schematic eye with temporal direction 0.4 mm eccentricity of the iris showed that the spherical aberration somewhat increased. Conclusions: In case of design of the schematic eye with the similar real eye performance which the iris centre was moved 0.5 mm with nasal direction, we need to research about aspheric coefficient of optical constants of each refracting surface considering the performance change of a spherical aberration, a peripheral power error and astigmatism etc, owing to change of the real eye hence to be affected by the iris movement.

• IEMEK Journal of Embedded Systems and Applications
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• v.18 no.2
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• pp.81-87
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• 2023

With the development of BCI devices, it is now possible to use EEG control technology to move the robot's arms or legs to help with daily life. In this paper, we propose a customized vehicle control model based on BCI. This is a model that collects BCI-based driver EEG signals, determines information according to EEG signal analysis, and then controls the direction of the vehicle based on the determinated information through EEG signal analysis. In this case, in the process of analyzing noisy EEG signals, controlling direction is supplemented by using a camera-based eye tracking method to increase the accuracy of recognized direction . By synthesizing the EEG signal that recognized the direction to be controlled and the result of eye tracking, the vehicle was controlled in five directions: left turn, right turn, forward, backward, and stop. In experimental result, the accuracy of direction recognition of our proposed model is about 75% or higher.

• Korean Institute of Interior Design Journal
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• v.25 no.4
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• pp.80-89
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• 2016

The analysis of spatial search direction and its concentration through eye movement can produce some useful data in that it enables to know the features of space elements and their effects on one another. The results by analysing the search features and concentration of spatial sections through the eye-tracking in shops in a department store makes it possible to define the followings. First, the features of 'eye's in & out' could be estimated through the division of sections by the characteristics of those shops and the extraction of central point based on the decision of continuative observation. The decision of continuative observations enabled to analyse the frequency of observation data which can be considered to be 'things watched longtime' and the stared points that is equivalent to 'things seen very often', by which the searching characteristics of spatial sections could be estimated. Second, as with the eye's [in], the right shops had 0.6 times more (3.5%) than those left and as with the eye's [out] the left ones had 0.6 times more (3.5%). It indicates that [in, out] of the right and the left shops had the same difference, which lets us know that with starting point of the middle space, [in] and [out] were paid more attention to the right shops and the left shops respectively. Third, as with the searching directions by section, the searching times [2.9 times] from [B] to [A] were than that [2.6 times] from [A] to [B]. It was also found that the left shops had more searching direction toward [C, D] than the right ones and that those searching activities at the left shops were more active. Fourth, when the searching directions by section are reviewed, the frequency of searching from [B] to [A] was 2.9 and that of the other way 2.6. Also the left shops were found to have more searching direction toward [C, D] than the right ones and those searching activities at the left shops were estimated to be more active.

• Journal of information and communication convergence engineering
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• v.7 no.2
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• pp.131-134
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• 2009

The red-eye effect in photography occurs when using a photographic flash very close to the camera lens, in ambient low light due to in experience. Once occurred, the photographer needs to remove it with image tool that requires time consuming, skillful process. In this paper, we propose a new method to extract and remove such red-eye area automatically. Our method starts with transforming ROB space to YCbCr and HSI space and it extracts the face area by using skin color information. The target red-eye area is then extracted by applying 8-direction contour tracking algorithm and removed. The experiment shows our method's effectiveness.