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Статті в журналах з теми "Eye tracking glasses"
OGASAWARA, Tomohito, Ryogo HORIUCHI, Yasuto TANAKA, and Norihisa MIKI. "Eye-tracking system for reverse glasses." Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec) 2017 (2017): 1A1—K12. http://dx.doi.org/10.1299/jsmermd.2017.1a1-k12.
Повний текст джерелаEhinger, Benedikt V., Katharina Groß, Inga Ibs, and Peter König. "A new comprehensive eye-tracking test battery concurrently evaluating the Pupil Labs glasses and the EyeLink 1000." PeerJ 7 (July 9, 2019): e7086. http://dx.doi.org/10.7717/peerj.7086.
Повний текст джерелаBehe, Bridget K., R. Thomas Fernandez, Patricia T. Huddleston, Stella Minahan, Kristin L. Getter, Lynnell Sage, and Allison M. Jones. "Practical Field Use of Eye-tracking Devices for Consumer Research in the Retail Environment." HortTechnology 23, no. 4 (August 2013): 517–24. http://dx.doi.org/10.21273/horttech.23.4.517.
Повний текст джерелаAl-Haddad, Sara, Matthew Sears, Omar Alruwaythi, and Paul M. Goodrum. "Complexity, Performance, and Search Efficiency: An Eye-Tracking Study on Assembly-Based Tasks among Construction Workers (Pipefitters)." Buildings 12, no. 12 (December 8, 2022): 2174. http://dx.doi.org/10.3390/buildings12122174.
Повний текст джерелаThibeault, Mark, Monica Jesteen, and Andrew Beitman. "Improved Accuracy Test Method for Mobile Eye Tracking in Usability Scenarios." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 63, no. 1 (November 2019): 2226–30. http://dx.doi.org/10.1177/1071181319631083.
Повний текст джерелаKatz, Trixie A., Danielle D. Weinberg, Claire E. Fishman, Vinay Nadkarni, Patrice Tremoulet, Arjan B. te Pas, Aleksandra Sarcevic, and Elizabeth E. Foglia. "Visual attention on a respiratory function monitor during simulated neonatal resuscitation: an eye-tracking study." Archives of Disease in Childhood - Fetal and Neonatal Edition 104, no. 3 (June 14, 2018): F259—F264. http://dx.doi.org/10.1136/archdischild-2017-314449.
Повний текст джерелаNiehorster, Diederick C., Thiago Santini, Roy S. Hessels, Ignace T. C. Hooge, Enkelejda Kasneci, and Marcus Nyström. "The impact of slippage on the data quality of head-worn eye trackers." Behavior Research Methods 52, no. 3 (January 2, 2020): 1140–60. http://dx.doi.org/10.3758/s13428-019-01307-0.
Повний текст джерелаGolard, Andre, and Sachin S. Talathi. "Ultrasound for Gaze Estimation—A Modeling and Empirical Study." Sensors 21, no. 13 (June 30, 2021): 4502. http://dx.doi.org/10.3390/s21134502.
Повний текст джерелаKortman, Brenton. "Assessing for Hemi-Spatial Neglect Using Eye Tracking Glasses." Archives of Physical Medicine and Rehabilitation 96, no. 10 (October 2015): e24. http://dx.doi.org/10.1016/j.apmr.2015.08.074.
Повний текст джерелаLaw, Brenda Hiu Yan, Po-Yin Cheung, Michael Wagner, Sylvia van Os, Bin Zheng, and Georg Schmölzer. "Analysis of neonatal resuscitation using eye tracking: a pilot study." Archives of Disease in Childhood - Fetal and Neonatal Edition 103, no. 1 (August 19, 2017): F82—F84. http://dx.doi.org/10.1136/archdischild-2017-313114.
Повний текст джерелаДисертації з теми "Eye tracking glasses"
Dahlberg, Joakim. "Eye Tracking with Eye Glasses." Thesis, Umeå University, Department of Physics, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-32868.
Повний текст джерелаThis study is concerned with the negative effects of wearing corrective lenses while using eye trackers, and the correction of those negative effects. The eye tracker technology studied is the video based real-time Pupil Center and Corneal Reflection method. With a user study, the wearing of eyeglasses is shown to cause 20 % greater errors in the accuracy of an eye tracker than when not wearing glasses. The error is shown to depend on where on the eye tracker viewing area the user is looking.
A model for ray refraction when wearing glasses was developed. Measurements on distortions on the image of the eye caused by eyeglass lenses were carried out. The distortions were analyzed with eye tracking software to determine their impact on the image-to-world coordinates mapping. A typical dependence of 1 mm relative distance change on cornea to 9 degrees of visual field was found.
The developed mathematical/physiological model for eyeglasses focuses on artifacts not possible to accommodate for with existing calibration methods, primarily varying combinations of viewing angles and head rotations. The main unknown in the presented model is the effective strength of the glasses. Automatic identification is discussed. The model presented here is general in nature and needs to be developed further in order to be a part of a specific application.
Fredriksson, Alfred, and Joakim Wallin. "Mapping an Auditory Scene Using Eye Tracking Glasses." Thesis, Linköpings universitet, Reglerteknik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-170849.
Повний текст джерелаAtan, Levent. "Multi-Person Infrared Pupil Tracking for 3D TV without Glasses." Thesis, Umeå universitet, Institutionen för informatik, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-62822.
Повний текст джерелаLarsson, Sofia, and Jimmy Åkesson. "Subtly Influencing Gaze Direction Using a Handheld Augmented Reality Device." Thesis, Malmö universitet, Fakulteten för teknik och samhälle (TS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-20760.
Повний текст джерелаSmart and helpful technologies are released every year and are quick to become partof our everyday lives. Technologies are becoming more aware of when and where weneed them and help us to achieve personal goals, such as taking the bike instead ofthe car to work. Still, many of these smart technologies have only limitedfunctionality without us interacting with them, resulting in us having to interactwith them and losing focus on other tasks.We believe that a decade from now, some future application interfaces will reside inaugmented reality smart glasses. While augmented reality can be a powerful toolwhen overlaying the real world, we also wish that the augmented reality interfacesdo not break the immersion of everyday life.In this study, we have explored the possibilities of sending visual cues to a user in asubtle or even a subliminal way in an augmented reality setting. In conclusion, thereis no obvious answer to whether a cue in the system that was implemented in thisstudy was subliminal. However, we found that the time it took to perceive a cue thatgradually intensifies with time differed between people and that people are moreinclined to focus on objects placed at an eye-level height which should be taken inconsideration when deciding on where to place visual cues.
LEE, TUNG-YING, and 李侗穎. "Gaze Tracking System for User Wearing Eye Glasses." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/nr8w5d.
Повний текст джерела國立暨南國際大學
資訊工程學系
105
Gaze tracking has become a popular human-computer interface which is widely adopted in various applications. However, most gaze tracking methods do not consider the influences of spectacle lens refraction and, therefore, can not be applied to users wearing eyeglasses. In this thesis, a new glint-feature-based (GFB) method (NGFB hereafter) is proposed which solves the spectacle lens refraction problem in gaze tracking. In the NGFB method, the ray tracking technique is employed to tackle the spectacle lens refraction. Thus, the NGFB method is compatible with either spherical for aspheric spectacle lenses. With the aid of ray tracing, the curvature center of the cornea and the refracted line of sight can be evaluated accurately. In this thesis, four experiments are conducted to test the proposed method via computer simulations. First, robustness of the NGFB method against the image noises is tested with spectacle lenes of diopters -5, -3, -1, 1, 3, and 5, respectively. Second, the influences of the position of virtual reflection plane used in the NGFB method to gaze tracking accuracy are examined. Third, the influences of the pose error of the spectacle lens to gaze tracking accuracy are evaluated. Experimental results show that the proposed NGFB method is robust against image noises and is insensitive to the spectacle lens pose estimation error.
CHEN, PIN-CHIH, and 陳品志. "Attention estimation from the integrated IMU and eye-tracking perception of smart glasses." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/50219533067558386819.
Повний текст джерела國立中正大學
電機工程研究所
104
Wearable mobile learning becomes an inevitable trend in the future. With the matured wearable technologies, related applications have boosted in the market, but lacked for a killer application that can lead and spread wearable technologies. In another way, attention ability is essential to effective learning. By estimating and recording attention capability help learners to improve and review their learning process. In the light of this, attention-estimating system is constructed form IMU information, and eye-tracking perception in our study. In this study, we combine eye-tracking perception with IMU information to realize the Attention-estimating system based on Android smart glasses. First, we divided the eye-tracking into eyeball detection and eye corner detection. Minimum Average Gray Value was used to find the general eyeball contour. Moreover, considered all kinds of light changes, Otsu algorithm also was used to detect the contour of eye corners. Then, we can master the eye movement by determining the sight and projection point. The result of the average error angle of view is 1.82 degree. In the attention recognition, the system divided steps into five part: data acquisition, feature extraction, feature selection, classify and voting mechanism in this study. In order to extract the eye movement and IMU information by recording experiment of attention and non-attention in seven different scenarios; In the feature extraction, we extracted forty one kinds of features based on feature characteristics, and selected the suitable feature by four different kinds of feature selections; Finally, we optimized the parameter of SVM by Genetic algorithm, and validated the reliability by K-fold algorithm, however, we also adapted the voting mechanism to estimate the result of attention level. The classified accuracy of attention and non-attention are reach up to 86.10% under seven scenarios. The three and two categories of Continuous Performance Test experiment result are 81.12% and 83.44%, respectively. Eventually our result as compared with reference papers that indicated feasibility and reliability.
Частини книг з теми "Eye tracking glasses"
Hsieh, Yi-Yu, Chia-Chen Liu, Wei-Lin Wang, and Jen-Hui Chuang. "Investigating Size Personalization for More Accurate Eye Tracking Glasses." In Computer Vision – ACCV 2016 Workshops, 239–48. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-54526-4_18.
Повний текст джерелаBao, Haifeng, Weining Fang, Beiyuan Guo, and Peng Wang. "Real-Time Eye-Interaction System Developed with Eye Tracking Glasses and Motion Capture." In Advances in Human Factors in Wearable Technologies and Game Design, 72–81. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-60639-2_8.
Повний текст джерелаKing, Meggan, Feiyan Hu, Joanna McHugh, Emma Murphy, Eamonn Newman, Kate Irving, and Alan F. Smeaton. "Visibility of Wearable Sensors as Measured Using Eye Tracking Glasses." In Communications in Computer and Information Science, 23–32. Cham: Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-04406-4_4.
Повний текст джерелаChaloupka, Christine, Ralf Risser, and Elisabeth Füssl. "Evaluation of Technologies That Help to Identify Hazards for Cyclists in Cities." In Advances in Civil and Industrial Engineering, 155–71. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-5225-9932-6.ch008.
Повний текст джерелаТези доповідей конференцій з теми "Eye tracking glasses"
Ye, Zhefan, Yin Li, Alireza Fathi, Yi Han, Agata Rozga, Gregory D. Abowd, and James M. Rehg. "Detecting eye contact using wearable eye-tracking glasses." In the 2012 ACM Conference. New York, New York, USA: ACM Press, 2012. http://dx.doi.org/10.1145/2370216.2370368.
Повний текст джерелаTopal, Cihan, Atakan Dogan, and Omer Nezih Gerek. "An eye-glasses-like wearable eye gaze tracking system." In 2008 IEEE 16th Signal Processing, Communication and Applications Conference (SIU). IEEE, 2008. http://dx.doi.org/10.1109/siu.2008.4632568.
Повний текст джерелаOskina, Maria, Zoltan Rusak, and Peter Boom. "Eye on HMI - Assessment of Human-Machine Interface with wearable eye-tracking glasses." In Design Computation Input/Output 2022. Design Computation, 2022. http://dx.doi.org/10.47330/dcio.2022.gpqp2161.
Повний текст джерелаMeyer, Johannes, Thomas Schlebusch, Thomas Kuebler, and Enkelejda Kasneci. "Low Power Scanned Laser Eye Tracking for Retinal Projection AR Glasses." In ETRA '20: 2020 Symposium on Eye Tracking Research and Applications. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3379157.3391995.
Повний текст джерелаHong, Injoon, Hoi-Jun Yoo, and Kyeongryeol Bong. "Challenges of eye tracking systems for mobile XR glasses." In Applications of Digital Image Processing XLI, edited by Andrew G. Tescher. SPIE, 2018. http://dx.doi.org/10.1117/12.2322657.
Повний текст джерелаGao, Xiang-Yu, Yu-Fei Zhang, Wei-Long Zheng, and Bao-Liang Lu. "Evaluating driving fatigue detection algorithms using eye tracking glasses." In 2015 7th International IEEE/EMBS Conference on Neural Engineering (NER). IEEE, 2015. http://dx.doi.org/10.1109/ner.2015.7146736.
Повний текст джерелаMulvey, Fiona Bríd, Marek Mikitovic, Mateusz Sadowski, Baosheng Hou, Nils David Rasamoel, John Paulin Paulin Hansen, and Per Bækgaard. "Gaze Interactive and Attention Aware Low Vision Aids as Future Smart Glasses." In ETRA '21: 2021 Symposium on Eye Tracking Research and Applications. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3450341.3460769.
Повний текст джерелаYip, Hiu Man, David Navarro-Alarcon, and Yun-hui Liu. "Development of an eye-gaze controlled interface for surgical manipulators using eye-tracking glasses." In 2016 IEEE International Conference on Robotics and Biomimetics (ROBIO). IEEE, 2016. http://dx.doi.org/10.1109/robio.2016.7866606.
Повний текст джерелаShi, Zhen-Feng, Chang Zhou, Wei-Long Zheng, and Bao-Liang Lu. "Attention evaluation with eye tracking glasses for EEG-based emotion recognition." In 2017 8th International IEEE/EMBS Conference on Neural Engineering (NER). IEEE, 2017. http://dx.doi.org/10.1109/ner.2017.8008298.
Повний текст джерелаWang, Yanxin, Hong Zeng, and Jia Liu. "Low-cost eye-tracking glasses with real-time head rotation compensation." In 2016 10th International Conference on Sensing Technology (ICST). IEEE, 2016. http://dx.doi.org/10.1109/icsenst.2016.7796336.
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