• Title/Summary/Keyword: Eye Localization

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Eye Localization based on Multi-Scale Gabor Feature Vector Model (다중 스케일 가버 특징 벡터 모델 기반 눈좌표 검출)

  • Kim, Sang-Hoon;Jung, Sou-Hwan;Oh, Du-Sik;Kim, Jae-Min;Cho, Seong-Won;Chung, Sun-Tae
    • The Journal of the Korea Contents Association
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    • v.7 no.1
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    • pp.48-57
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    • 2007
  • Eye localization is necessary for face recognition and related application areas. Most of eye localization algorithms reported thus far still need to be improved about precision and computational time for successful applications. In this paper, we propose an improved eye localization method based on multi-scale Gator feature vector models. The proposed method first tries to locate eyes in the downscaled face image by utilizing Gabor Jet similarity between Gabor feature vector at an initial eye coordinates and the eye model bunch of the corresponding scale. The proposed method finally locates eyes in the original input face image after it processes in the same way recursively in each scaled face image by using the eye coordinates localized in the downscaled image as initial eye coordinates. Experiments verify that our proposed method improves the precision rate without causing much computational overhead compared with other eye localization methods reported in the previous researches.

Relative localization errors: The effect of reference location on the errors (상대적인 위치지각의 왜곡: 참조자극의 위치가 왜곡에 미치는 영향)

  • Li, Hyung-Chul
    • Korean Journal of Cognitive Science
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    • v.15 no.3
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    • pp.15-24
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    • 2004
  • The perceived position of a flashing target object is generally biased towards the direction of eye movement when there is no reference around the target. Current research examined the localization accuracy of a flashing target relative to a static reference. The perceived location of the target relative to the reference was distorted and the pattern of perceptual distortion systematically depended on the position of the reference relative to the target. This kind of result was consistently observed regardless of the distance between the reference and the target and direction of pursuit eye movement. We have discussed how these results could he explained by the theories previously suggested to explain the localization of objects.

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Robust Eye Localization using Multi-Scale Gabor Feature Vectors (다중 해상도 가버 특징 벡터를 이용한 강인한 눈 검출)

  • Kim, Sang-Hoon;Jung, Sou-Hwan;Cho, Seong-Won;Chung, Sun-Tae
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.45 no.1
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    • pp.25-36
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    • 2008
  • Eye localization means localization of the center of the pupils, and is necessary for face recognition and related applications. Most of eye localization methods reported so far still need to be improved about robustness as well as precision for successful applications. In this paper, we propose a robust eye localization method using multi-scale Gabor feature vectors without big computational burden. The eye localization method using Gabor feature vectors is already employed in fuck as EBGM, but the method employed in EBGM is known not to be robust with respect to initial values, illumination, and pose, and may need extensive search range for achieving the required performance, which may cause big computational burden. The proposed method utilizes multi-scale approach. The proposed method first tries to localize eyes in the lower resolution face image by utilizing Gabor Jet similarity between Gabor feature vector at an estimated initial eye coordinates and the Gabor feature vectors in the eye model of the corresponding scale. Then the method localizes eyes in the next scale resolution face image in the same way but with initial eye points estimated from the eye coordinates localized in the lower resolution images. After repeating this process in the same way recursively, the proposed method funally localizes eyes in the original resolution face image. Also, the proposed method provides an effective illumination normalization to make the proposed multi-scale approach more robust to illumination, and additionally applies the illumination normalization technique in the preprocessing stage of the multi-scale approach so that the proposed method enhances the eye detection success rate. Experiment results verify that the proposed eye localization method improves the precision rate without causing big computational overhead compared to other eye localization methods reported in the previous researches and is robust to the variation of post: and illumination.

Deep Learning-based Gaze Direction Vector Estimation Network Integrated with Eye Landmark Localization (딥 러닝 기반의 눈 랜드마크 위치 검출이 통합된 시선 방향 벡터 추정 네트워크)

  • Joo, Heeyoung;Ko, Min-Soo;Song, Hyok
    • 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).

Localization using Ego Motion based on Fisheye Warping Image (어안 워핑 이미지 기반의 Ego motion을 이용한 위치 인식 알고리즘)

  • Choi, Yun Won;Choi, Kyung Sik;Choi, Jeong Won;Lee, Suk Gyu
    • Journal of Institute of Control, Robotics and Systems
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    • v.20 no.1
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    • pp.70-77
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    • 2014
  • This paper proposes a novel localization algorithm based on ego-motion which used Lucas-Kanade Optical Flow and warping image obtained through fish-eye lenses mounted on the robots. The omnidirectional image sensor is a desirable sensor for real-time view-based recognition of a robot because the all information around the robot can be obtained simultaneously. The preprocessing (distortion correction, image merge, etc.) of the omnidirectional image which obtained by camera using reflect in mirror or by connection of multiple camera images is essential because it is difficult to obtain information from the original image. The core of the proposed algorithm may be summarized as follows: First, we capture instantaneous $360^{\circ}$ panoramic images around a robot through fish-eye lenses which are mounted in the bottom direction. Second, we extract motion vectors using Lucas-Kanade Optical Flow in preprocessed image. Third, we estimate the robot position and angle using ego-motion method which used direction of vector and vanishing point obtained by RANSAC. We confirmed the reliability of localization algorithm using ego-motion based on fisheye warping image through comparison between results (position and angle) of the experiment obtained using the proposed algorithm and results of the experiment measured from Global Vision Localization System.

Detection of eye using optimal edge technique and intensity information (눈 영역에 적합한 에지 추출과 밝기값 정보를 이용한 눈 검출)

  • Mun, Won-Ho;Choi, Yeon-Seok;Kim, Cheol-Ki;Cha, Eui-Young
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2010.10a
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    • pp.196-199
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    • 2010
  • The human eyes are important facial landmarks for image normalization due to their relatively constant interocular distance. This paper introduces a novel approach for the eye detection task using optimal segmentation method for eye representation. The method consists of three steps: (1)edge extraction method that can be used to accurately extract eye region from the gray-scale face image, (2)extraction of eye region using labeling method, (3)eye localization based on intensity information. Experimental results show that a correct eye detection rate of 98.9% can be achieved on 2408 FERET images with variations in lighting condition and facial expressions.

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Human Spatial Cognition Using Visual and Auditory Stimulation

  • Yu, Mi;Piao, Yong-Jun;Kim, Yong-Yook;Kwon, Tae-Kyu;Hong, Chul-Un;Kim, Nam-Gyun
    • International Journal of Precision Engineering and Manufacturing
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    • v.7 no.2
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    • pp.41-45
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    • 2006
  • This paper deals with human spatial cognition using visual and auditory stimulation. More specially, this investigation is to observe the relationship between the head and the eye motor system for the localization of visual target direction in space and to try to describe what is the role of right-side versus left-side pinna. In the experiment of visual stimulation, nineteen red LEDs (Luminescent Diodes, Brightness: $210\;cd/^2$) arrayed in the horizontal plane of the surrounding panel are used. Here the LEDs are located 10 degrees apart from each other. Physiological parameters such as EOG (Electro-Oculography), head movement, and their synergic control are measured by BIOPAC system and 3SPACE FASTRAK. In the experiment of auditory stimulation, one side of the pinna function was distorted intentionally by inserting a short tube in the ear canal. The localization error caused by right and left side pinna distortion was investigated as well. Since a laser pointer showed much less error (0.5%) in localizing target position than FASTRAK (30%) that has been generally used, a laser pointer was used for the pointing task. It was found that harmonic components were not essential for auditory target localization. However, non-harmonic nearby frequency components was found to be more important in localizing the target direction of sound. We have found that the right pinna carries out one of the most important functions in localizing target direction and pure tone with only one frequency component is confusing to be localized. It was also found that the latency time is shorter in self moved tracking (SMT) than eye alone tracking (EAT) and eye hand tracking (EHT). These results can be used in further study on the characterization of human spatial cognition.

Vision-based Self Localization Using Ceiling Artificial Landmark for Ubiquitous Mobile Robot (유비쿼터스 이동로봇용 천장 인공표식을 이용한 비젼기반 자기위치인식법)

  • Lee Ju-Sang;Lim Young-Cheol;Ryoo Young-Jae
    • Journal of the Korean Institute of Intelligent Systems
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    • v.15 no.5
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    • pp.560-566
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    • 2005
  • In this paper, a practical technique for correction of a distorted image for vision-based localization of ubiquitous mobile robot. The localization of mobile robot is essential and is realized by using camera vision system. In order to wide the view angle of camera, the vision system includes a fish-eye lens, which distorts the image. Because a mobile robot moves rapidly, the image processing should he fast to recognize the localization. Thus, we propose the practical correction technique for a distorted image, verify the Performance by experimental test.

Indoor Positioning System Based on Camera Sensor Network for Mobile Robot Localization in Indoor Environments (실내 환경에서의 이동로봇의 위치추정을 위한 카메라 센서 네트워크 기반의 실내 위치 확인 시스템)

  • Ji, Yonghoon;Yamashita, Atsushi;Asama, Hajime
    • Journal of Institute of Control, Robotics and Systems
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    • v.22 no.11
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    • pp.952-959
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    • 2016
  • This paper proposes a novel indoor positioning system (IPS) that uses a calibrated camera sensor network and dense 3D map information. The proposed IPS information is obtained by generating a bird's-eye image from multiple camera images; thus, our proposed IPS can provide accurate position information when objects (e.g., the mobile robot or pedestrians) are detected from multiple camera views. We evaluate the proposed IPS in a real environment with moving objects in a wireless camera sensor network. The results demonstrate that the proposed IPS can provide accurate position information for moving objects. This can improve the localization performance for mobile robot operation.

Study on the Characteristic of Eye Movement for Visual Improvement of the Elderly

  • Yu, Mi;Piao, Yong-Jun;Kim, Yong-Yook;Kwon, Tae-Kyu;Hong, Chul-Un;Kim, Nam-Gyun
    • 제어로봇시스템학회:학술대회논문집
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    • 2005.06a
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    • pp.202-205
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    • 2005
  • The purpose of this work is to identify the characteristic of eye movement for visual training of the elderly. This investigation is to examine the relationship between the head and the eye motor system for the localization of visual target direction in three-dimensional space. All experiments were performed in a soundproof chamber. Twenty-one red LEDs (Light-Emitting Diode, Brightness: 20cd/$m^2$) arrayed in three lines on a half circle-surrounding panel are used. LEDs are horizontally 30 degree apart and vertically 20 degree apart from each other. The condition of stimulation is random and anti-saccade. Physiological parameter such as EOG (Electro-Oculography) was measured by BIOPAC system. We measure the mean latency time, which is the time from the start of visual stimulation to the response of the human body. The result shows that the mean latency time is short in the case of the condition of anti-saccade, the fixed head and a quarter visual stimulation. This finding can be used in developing programs for various visual improvements for the elderly by analyzing the characteristic of eye movement.

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