Eye Tracking Technologies Samples †MyAssignmenthelp.com

Question: Discuss about the Eye Tracking Technologies. Answer: Introduction In this new era of technology world eye tracking is one of the greatest opportunities to control the things by seeing them only. It can help in operating various operations by the movement of eyes and using Near Infrared lights to input commands in a system. This report explains the meaning of Eye Tracking technology and the various components used in this device. This report also explains how those components work and what their uses in the present world are and they can be used in future to make this world better. This report emphasis on the advantages of eye tracking comparing with other technologies and also few of the disadvantages are also provided below as there are not much disadvantage of this technology. Eye Tracking Eye tracking is a process of tracking the motion of eye with respect to the head or measure point of gaze means, where an individual is looking. It is a process for measuring the positions and movement of eyes (Gandhi et al. 2016). There are three types of tracker listed as first, Eye-attached tracking which generally uses lens to measure the movement of an object attaching that lens. Second, Optical Tracking, which process without involvement of the direct eye contact. Third is Electric potential measurement, which uses electrodes placing around the eyes. Eye tracker is a technology that can put control of a device to an individual by using the movement of eyes as he naturally would. Components of eye tracker are camera, projectors, sensors and algorithm (Xiong et al. 2014). The sensors are custom-designed hardware designed to perform as high performance sensor which consist of several custom components and highly advanced optics which are explained below: Advanced Micro Projectors Reflection pattern of Near Infrared (NIR) light on the eyes are created by using advanced micro projectors. The Sensors High-frame rate images of the eye of user and their reflection pattern are captured by using these sensors. The Image-Processing Algorithm The main intelligence of the system is the image-processing algorithm which, specifies the reflection patterns generated by the infrared coming back from the object or the screen and the details of the eye of a user and interprets the image stream which was generated by the sensors (Kassner, Patera and Bulling 2014). Users eye and the gaze point on a device screen are calculated by the Image-processing algorithms. User-Oriented Applications An intelligent application layer is added to the system in order to enable the various ways in which a technology can be used. Working of Eye Tracker Most of the eye trackers in this modern world which are available in the market are using near-infrared technology along with a camera of high resolution to track the movement of the eyes which is based on a straightforward concept referred to as Pupil Center Corneal Reflection (PCCR) (Lappi 2015). Visible reflections in the outer-most part of the eye (Cornea) are caused by the interaction of near-infrared (NIR) directly towards the pupil (center of the eye) which are tracked by camera. The accuracy of gaze direction measurement is dependent on the detection of corneal reflection and on a clear demarcation of the pupil, so eye tracking cannot be done with a source of ordinary light. Satisfying tracking result can be accomplished only by using infrared spectrum. Based on working and irrespective of the technology it can be classified into two groups: Remote Eye Tracker Often called as screen-based devices which require an individual is needed to interact with the screen-based content and monitor by sitting in front of it (Jones et al. 2014). It can record movement of an eye at a distance. Mobile Eye Tracker Kunze et al. (2013) stated that in this tracker device, respondents are allowed to move freely as the devices are fitted near the eyes which are usually mounted onto frames of eyeglass. Applications of Eye Tracker Eye trackers are used for various purposes some of them are listed as firstly, in psycholinguistics research, in research on the visual system, in marketing, in product design and as a device to input human-computer interactions. There are lots of application of eye tracking now a days some of them can be listed as firstly, Driving car which can be difficult but can be practiced by eye tracking (Lupu 2013). Secondly Surfing the internet and search anything there and buy groceries or play video-game or complete training exercise or even an individual can watch movie, download it or operate mobile devices. Future of Eye Tracking TOBII REX: According to Marcus (2013) Tobii a Stockholm-based company is planning to launch Rex USB-connected eye-tracking device which tracks vision by sitting in front of a computer screen and completely relies on image sensor and infrared-light-emitting micro-projector. Behind the Wheel: Toyota, General Motors and Carmakers has invested on a system to research towards attention and vision-monitoring system in cars which will improve safety by involving eye-tracking tech. Reading Enhanced: Software named Text 2.0 on which German researchers are working intends to pop-up translations and meaning of foreign words on the web display. Advantages of Eye Tracking Technology The movement of eyes is faster in eye tracking than other input media that we are using now. There is no need of training or any other particular coordination to operate this technology for a common user. It can determine at the particular point where the interest of a user is focused automatically and faster which other technologies cannot do (Fielder et al. 2013). It is more helpful than other technologies in usability studies in order to understand the interaction of the users with their suitable environments. Based on simplicity there are many points firstly, Setup can be done quickly as there are no complicated hardware involved in this setup. Secondly, User interface are spontaneous. For more than one application no calibration is required, automatic suppression and blink detection, Interface eye tracking with other applications become very busy due to the implementation of powerful SDK. With respect to flexibility its range is selected between 30Hz and 60 Hz operation modes, i t provides minimum tolerance to head movement by giving options like Glint-only tracking, Pupil-only tracking or chose both. Real-time Interface between the computers provides maximum flexibility to this technology. Disadvantages of Eye Tracking Technology This is very expensive to outfit a lab with decent eye-tracker even Google has outfitted only one of its lab with this facility. Many people are automatically not qualified to use eye-tracking based on the variety of attributes and also long eye lashes can get in the way of device function properly (Lupu and Ungureanu 2013). Another disadvantage is that setup of a participant and calibration with the device can consume time resulting in the lack of interest of an individual in using this device. Haans, De Brujin and IJsselsteijn (2014) discussed that eyes movement are often non-intentional (Midas Touch) so they must be interpreted carefully in order to eliminate unwanted responses to the users, major problem in this set up is that people are not accustomed to such operating devices in simple way by moving their eyes. Conclusion Based on the above report it can be concluded that this is a very new technology for this era which need to spread across the world and applications need to be expanded. It has the better and faster input facility for any command as compared with any other technology present at this moment. This may be a complicated operation but the outputs are more beneficial than the trouble made during the implementation of these devices so these are the necessary troubles which can be bearable in order to make this more advanced world. There are lots of advantages of this technology as explained above and very few disadvantages which are depicted in the last paragraph of this report. References: Fiedler, S., Glckner, A., Nicklisch, A. and Dickert, S., 2013. Social Value Orientation and information search in social dilemmas: An eye-trackinganalysis.Organizational behavior and human decision processes,120(2), pp.272-284. Gandhi, A., Patil, K., Deshpande, R. and Nazirkar, G., 2016. iMouseEye Tracking Application.Imperial Journal of Interdisciplinary Research,2(7). Haans, A., de Bruijn, R. and IJsselsteijn, W.A., 2014. A virtual midas touch? Touch, compliance, and confederate bias in mediated communication.Journal of Nonverbal Behavior,38(3), pp.301-311. Jones, P.R., Kalwarowsky, S., Atkinson, J., Braddick, O.J. and Nardini, M., 2014. Automated Measurement of Resolution Acuity in Infants Using Remote Eye-TrackingAutomated Acuity in Infants.Investigative ophthalmology visual science,55(12), pp.8102-8110. Kassner, M., Patera, W. and Bulling, A., 2014, September. Pupil: an open source platform for pervasive eye tracking and mobile gaze-based interaction. InProceedings of the 2014 ACM international joint conference on pervasive and ubiquitous computing: Adjunct publication(pp. 1151-1160). ACM. Kunze, K., Kawaichi, H., Yoshimura, K. and Kise, K., 2013, August. The Wordometer--Estimating the Number of Words Read Using Document Image Retrieval and Mobile Eye Tracking. InDocument Analysis and Recognition (ICDAR), 2013 12th International Conference on(pp. 25-29). IEEE. Lappi, O., 2015. Eye Tracking in the Wild: the Good, the Bad and the Ugly.Journal of Eye Movement Research,8(5). Lupu, R.G. and Ungureanu, F., 2013. A survey of eye tracking methods and applications.Bul Inst Polit Iasi, pp.71-86. Lupu, R.G. and Ungureanu, F., 2013. A survey of eye tracking methods and applications.Bul Inst Polit Iasi, pp.71-86. Marcus, A., 2013, November. Mobile user-experience design trends. InSIGGRAPH Asia 2013 Courses(p. 12). ACM. Xiong, X., Liu, Z., Cai, Q. and Zhang, Z., 2014, September. Eye gaze tracking using an RGBD camera: a comparison with a RGB solution. InProceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct Publication(pp. 1113-1121). ACM.