WO2012052061A1 - Procédé et système d'étalonnage de système de détection de regard - Google Patents

Procédé et système d'étalonnage de système de détection de regard Download PDF

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Publication number
WO2012052061A1
WO2012052061A1 PCT/EP2010/065928 EP2010065928W WO2012052061A1 WO 2012052061 A1 WO2012052061 A1 WO 2012052061A1 EP 2010065928 W EP2010065928 W EP 2010065928W WO 2012052061 A1 WO2012052061 A1 WO 2012052061A1
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Prior art keywords
calibration
gaze
point
calibrating
user
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Ceased
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PCT/EP2010/065928
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English (en)
Inventor
Matthias Laabs
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Institut fuer Rundfunktechnik GmbH
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Institut fuer Rundfunktechnik GmbH
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Priority to PCT/EP2010/065928 priority Critical patent/WO2012052061A1/fr
Publication of WO2012052061A1 publication Critical patent/WO2012052061A1/fr
Anticipated expiration legal-status Critical
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    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
    • G06F3/01—Input arrangements or combined input and output arrangements for interaction between user and computer
    • G06F3/011—Arrangements for interaction with the human body, e.g. for user immersion in virtual reality
    • G06F3/013—Eye tracking input arrangements

Definitions

  • the present invention relates to a gaze detector, and particularly to a method for calibrating a gaze detector.
  • the invention relates to a method for calibrating a gaze detector system according to the preamble of claim 1 .
  • Gaze detectors are devices designed for recognizing the direction of the gaze of a human being, and thus the point he is looking at. Such gaze detectors are useful for several applications, especially belonging to human-machine interaction.
  • Gaze detectors are also frequently used in the automotive field, e.g. to control the degree of attention of a driver, and in particular to detect whether the driver is looking at the road or not.
  • the gaze detectors based on image processing use one or more cameras (usually two) and one or more light sources (e.g. infrared LEDs, and/or visible light) for illumination. The illuminating light is reflected towards the cameras by the user. These cameras provide images of the user's eyes, and by detecting the head position, the face position and the pupil position, the gaze detector can calculate the user's gaze direction. In certain applications, the pupil glint can also be considered as a factor. ln order to properly function, gaze detectors need an appropriate calibration to provide measurements with adequate accuracy.
  • light sources e.g. infrared LEDs, and/or visible light
  • Accuracy is inversely related to the observational error of the measure, defined as the spatial distance separating the point estimated by the gaze detector and the point the user is actually looking at.
  • the calibration shall be particularly accurate.
  • a gaze detector For the calibration of a gaze detector the user looks at a predetermined point (i.e. generated and known by the detector) for a certain amount of seconds.
  • the gaze detector establishes a correlation between the gaze direction derived by the images of the user and the point the user actually is looking at. By repeating these steps for several predetermined points, calibration can be achieved.
  • the method for calibrating a gaze detector comprises the steps of: starting a calibration phase; detecting a measured gaze point observed by a user, preferably by capturing images of the user; comparing the measured gaze point with a calibration point that the user is assumed to observe during the gaze detection; calibrating the gaze detector based on comparison.
  • the calibration phase is automatically started as a calibration event is detected by sensor means; also the calibration point is determined based on the calibration event and its type.
  • the method comprises the further steps of determining a quality value associated to the probability of accuracy of the calibration point and weighing the calibration based on the quality value.
  • different preferred events can be interpreted as calibration events.
  • such events can belong to categories of tasks spontaneously performed by the user during the use of a system. Therefore, the method of calibrating a gaze detector does not require a dedicated time for calibration, in which the user is completely absorbed by the calibration procedure. The calibration procedure thus results in an easier and lighter experience for the user.
  • the method of calibration takes into account the nature of the calibration event triggering the calibration, since different events can have a different reliability for calibration purposes.
  • This feature is implemented by calculating a quality value for each specific calibration event, and by weighting the calibration based on this quality value.
  • the quality value can be a function of the measure gaze point, of the calibration point and of a measure confidence interval, whenever the calibration process is repeated several times.
  • calibration events with a low quality value, caused by bad readings can be discarded during the calibration process.
  • Figures 1 a, 1 b, 1 c and 1d show various stages of the functioning of the system according to the invention
  • FIG. 2 is a flow chart of a method according to the invention.
  • Figures 1 a trough 1 d represent an example of the system for calibrating a gaze detector, whose functioning is described in the following.
  • the system implements the method according to the present invention.
  • the system of the example of Figure 1 a to 1d preferably comprises:
  • - imaging means 1 to acquire videos or images of the user 2, while he is performing tasks; at least one computational unit 6 adapted to measure a gaze point by analysis of the acquired images;
  • the imaging means to acquire images of the user 2 comprise at least one camera 1 , pointed in such a direction so that the face of the user 2 can be viewed at all times.
  • the camera 1 can advantageously be sensitive to infrared and/or ultraviolet light in addition to visible light, so that its imaging performances can be raised.
  • special illumination for the user 2 can be provided (not represented in the Figures) so that his features can be more easily detected by the camera 1 .
  • imaging means 1 also commercially available, can be miniaturized and located wherever needed (in frames of appliances, inside a car, on a wall, ...)
  • the camera 1 is connected to a computational unit 6 comprising means to analyze the images and measure a gaze point which the user is looking at. This measure can be performed with different degrees of accuracy, depending on the calibration.
  • the present invention provides means for improving such calibration.
  • the user 2 is standing in front of the camera 1 , performing an activity.
  • This activity can be anything that might require, at a certain time, to determine the user's gaze direction. Examples of this activity can be interacting with a display using a mouse, driving, surfing the web, performing an ATM cash withdrawal, selecting items on a touchscreen, and so on.
  • a "calibration event” occurs, and is detected by the system.
  • Such calibration event is an event belonging to a predetermined set of events (or category), that are used for calibrating the system 1 .
  • Such events can be initiated by the user performing a particular action, or can correspond to external inputs presented to user and recognized by the system.
  • the user 2 presses a button 3.
  • the pressing of the button 3 can happen independently by the calibration method; in other words, the user 2 may decide spontaneously to press button 3, or may be prompted to do so.
  • the pressing of the button 3 can result in effects other than or additional to the calibration of the system, i.e. turning on a light, or playing music, or initiating a computer procedure.
  • the user may regard such "calibration events", depending on the situation, as something completely unrelated to the calibration process, being natural tasks that he would anyway perform.
  • these natural tasks are used according to the present invention to provide a system calibration.
  • the system in response to the calibration event (i.e. pressing of the button 3), can identify a calibration point (i.e. the button 3 itself).
  • the acquired image 4, the calibration point 3 and the kind of calibration event are passed to a computational unit 6 adapted to perform the calibration method 5, that will be described in more depth in the following and is now schematized as revolving gears.
  • Another example of calibration event useful for indirect calibration of the system as explained, can be the use of a GUI (Graphical User Interface) of a notebook.
  • GUI Graphic User Interface
  • the user utilizes a mouse to point and click icons shown on a display; when the user clicks on a particular icon, it is likely that he is looking exactly at the pointer of the mouse. Therefore, the mouse click represent a calibration event, and the position of the mouse pointer at the instant of the click represent the calibration point.
  • a calibration event is the pressure of a certain combination of keys on a keyboard of a computer, such as the command CTRL+ALT+DEL.
  • the execution of this command is likely to cause, in people that write from left to right, to look from the bottom left corner of the keyboard (where the CTRL key is) moving right towards the DEL key. It is clear that this calibration event can be less reliable than the latter, and the method can take into account this difference as it will be described in the following.
  • the invention can be implemented in a car. While driving, the driver often stares at the rear-view mirror or at each of the side view mirrors. These actions are rather frequent, and can be elected as calibration events, knowing the exact position of the calibration points on the respective mirrors.
  • the external sensors of the car can be employed to find external calibration points, such as traffic lights.
  • a calibration event is the switching to the green light
  • the green lamp of the traffic light is the actual point looked by the driver.
  • further calibration events can be determined with the aid of a GPS navigation system, frequently installed in vehicles, by providing to the gaze detector information about the surroundings and the movement of the car.
  • calibration events for the invention implemented in a car can the use of radio or air conditioning controls.
  • system 1 may comprise several different means to detect calibration events.
  • Calibration event detecting means trigger the computational unit via connecting means 7, when a specific event belonging to a predetermined category happens.
  • the computational unit 6 recognizes the origin of the trigger signal, and acquires information relative to the calibration event.
  • information can be the time of the calibration event, the nature of the calibration event (i.e. the category or subcategory of the event), the referenced calibration point and information related to the actual user's gaze measured. This pieces of information can be retained and stored (fully or partially, in volatile or non volatile form) in a memory of computational unit 6, in order to improve subsequent readings of other calibration events.
  • the gaze detector can determine the gaze direction of the user using different techniques, more or less invasive, featuring contact or non-contact sensors; all known gaze measuring techniques can be applied.
  • the system 1 is based on video or image analysis that outputs the position of the measured gaze point of the user as a function of time.
  • the gaze measuring means can be based on:
  • a border detection algorithm preferably based on the Laplace operator
  • FIG. 2 exemplifies a flowchart of other aspects of the invention, describing in detail the calibration method.
  • a calibration event 201 can be detected by the system, when an appropriate signal is triggered at the instant N, as previously described.
  • the detection of the calibration event sets into motion an instance of the calibration of the gaze detector. This method can efficiently be performed while the gaze detector is active and being utilized by the user, or when the gaze detector is active even though the user is not currently using it directly.
  • a calibration event belongs to a predetermined category as previously described, i.e. "click of mouse” or “press of a button” and so on .
  • the calibration event category is predetermined, the calibration event itself may or may not be predetermined by the system, i.e. the time at which the event occurs may not be forecast by the system, being a consequence of the user's own initiative.
  • the gaze detecting system acquires the necessary data for estimating the user's gaze direction.
  • the system acquires one or more images 203 or videos of the user immediately after the calibration event 201 , from one or more points of view.
  • Other embodiments may consider a plurality of images from a plurality of point of views, belonging to different instants of time, i.e. several images when the user is moving his gaze on a pattern (i.e. as described above with reference of the pressing of CTRL+ALT+DEL on a keyboard).
  • the system is therefore capable of estimating a measured gaze point 204 of the user.
  • the gaze detector 205 is adequately calibrated, the actual point looked at by the user can be identified.
  • the calibration method according to the invention is used.
  • 206 can be identified with more or less accuracy. As exemplified above, when the user clicks with a mouse, he is probably looking at the pointer on the screen. When he presses a point of a touchscreen, he is probably looking at the point itself.
  • one or more calibration points 206 can be identified, corresponding to a particular calibration event 201 .
  • This points 206 can be advantageously used for calibrating the system, according to the invention.
  • the calibration point is, generally, a point that the user is probably looking at. Even in known solutions, there is no guarantee that the user is actually looking at the point as requested. Similarly, in this case, there are types of calibration points 206 that have a higher probability of being correctly identified by the system, and others that might have a smaller probability. In example, a click of a mouse has more probability of being a reliable calibration point, if compared to the use of video objects moving on a display or physical objects moving outside of a car.
  • a value related to the reliability of a particular calibration event is determined.
  • a value 207 corresponding to the reliability of the event type is determined; preferably, this value can be a probability value between 0 and 1 .
  • an overall quality 208 can associated to the calibration available for the system at all times.
  • the gaze detector 205 can have a calibration status that is known having a more or less reliable calibration. The procedure for making the overall quality 208 known will be described in the following.
  • An initial or partial calibration for the gaze detector 205 has to be available, in order to measure the gaze point 204.
  • This measure is therefore associated to a confidence interval 209 given at instance N-1 of calibration (i.e. the previous calibration instance); this confidence interval 209 is related to the expected observational error of the measure; i.e. the better the calibration, the higher will be the measure confidence 209.
  • a measure quality 210 can therefore be determined, to take into account that, even if a reliable calibration event 201 with a high probability 207 is provided, the system could more or less capable of correctly using this information.
  • the measured gaze point 204 and the information on the actual position of the calibration point 206 are cross-examined, to obtain the existing difference 21 1 between them.
  • This is provided mainly for calibration purposes, since the calibration 212 of the gaze detector is based on updating a set of parameters related to the gaze point measure, in order to minimize the error between the measured gaze point and the actual calibration points, when available.
  • the updated set of parameters is therefore passed over to the gaze detector 205 to be used for subsequent measurements.
  • the difference 21 1 can be employed to increase the precision on the measure quality 210, in order to discard calibration events whose readings may not be advantageous for the system calibration.
  • the measure quality 201 is obtained as a function of the difference 21 1 between the measured gaze point and the calibration point, and the value of the measure confidence 209. More in particular, the measure quality 210 can be determined as a statistical correlation between the variance of the measure related to the measure confidence 209 and the difference 21 1 . If the distance 21 1 is much smaller than its variance, the measure quality 210 value will be high; instead, if the distance 21 1 is much larger than its variance, the measure quality 210 of event N will be low.
  • the measure quality is expressed as a probability having a value between 0 and 1 .
  • the event's type probability 207 and the measure quality 210 are combined together to determine the calibration event quality 213.
  • the event's type probability 207 and the measure quality 210 are simply multiplied for each other.
  • the information on the calibration event quality 213 can be used to improve the calibration process.
  • the calibration of the parameters of the gaze detector can be weighted to give more importance to the measurements obtained by calibration events with good quality 213 (i.e. above 0.8 of probability).
  • the calibration event quality 213 at instance N can contribute to determine the overall quality of calibration 208, i.e. the latter being the average of the qualities of all the calibration events 1 ,...,N considered.
  • calibration events 201 having qualities 213 in a wide range can be used for calibration (i.e. ranging from 0.4 to 1 .0), while after a certain overall calibration 208 quality has been achieved (i.e. above 0.9), all events with a quality 203 lower than the overall quality 208 can be discarded, so that the calibration can be steadily improved.
  • the present method collects calibration points for the calibration process automatically, without requiring any user's aware contribution. It is clear that the method allows to use the gaze detector in an straight forward manner, without wasting time for an explicit calibration process.
  • the method assesses the quality of the detected calibration events, in order to avoid events providing inaccurate data that might damage the calibration process.
  • the method being iterative, continuously improves the calibration accuracy because more and more calibration events are detected with time.
  • the method described above and the system implementing the method provides an automatic and iterative calibration process for a gaze detector.
  • the present invention can find applications for the interaction of a user with graphical interfaces, such as computers or interactive displays in general.
  • the invention is particularly useful whenever the user can interact with the interface using both his gaze and other input means (such as mouse, touchpad, touchscreen, keyboard, special devices for impaired users, and so on) so as to provide a plurality of possible calibration events.
  • other input means such as mouse, touchpad, touchscreen, keyboard, special devices for impaired users, and so on
  • the present invention can find other applications in the automotive field, in which the gaze of a driver is monitored for safety of control purposes.

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  • Engineering & Computer Science (AREA)
  • General Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Human Computer Interaction (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Eye Examination Apparatus (AREA)

Abstract

L'invention concerne un procédé d'étalonnage d'un détecteur de regard comprenant les étapes consistant à : a) débuter une phase d'étalonnage dudit détecteur de regard ; b) détecter un point de regard mesuré (204) observé par un utilisateur (2) au moyen dudit détecteur de regard, de préférence en capturant (203) au moins une image (4) d'au moins un oeil dudit utilisateur (2) ; c) comparer ledit point de regard mesuré (204) avec un point d'étalonnage (206, 3), ledit point d'étalonnage (206, 3) étant un point que l'utilisateur est supposé observer pendant la détection de regard à l'étape b) ; d) étalonner (212) ledit détecteur de regard (205) sur la base de la comparaison de l'étape c). La phase d'étalonnage est débutée automatiquement alors qu'un événement d'étalonnage (201) est détecté par des moyens formant capteur (3, 7) et le point d'étalonnage (206, 3) est déterminé sur la base de l'événement d'étalonnage (201) et du type (202) d'événement d'étalonnage (201). L'invention concerne également un système correspondant de détection de regard.
PCT/EP2010/065928 2010-10-22 2010-10-22 Procédé et système d'étalonnage de système de détection de regard Ceased WO2012052061A1 (fr)

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Cited By (25)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2014125380A3 (fr) * 2013-02-14 2014-11-06 The Eye Tribe Aps Systèmes et procédés permettant un étalonnage de commande de suivi des yeux
WO2014197408A1 (fr) * 2013-06-06 2014-12-11 Microsoft Corporation Étalonnage de système d'oculométrie par entrée tactile
US20150131850A1 (en) * 2013-11-12 2015-05-14 Fuji Xerox Co., Ltd. Identifying user activities using eye tracking data, mouse events, and keystrokes
DE102013019117A1 (de) 2013-11-15 2015-05-21 Audi Ag Verfahren zum Kalibrieren einer Blickrichtungserfassungseinrichtung für ein Kraftfahrzeug, Kalibrierungseinrichtung und Kraftfahrzeug
EP2940555A1 (fr) * 2014-04-22 2015-11-04 Lenovo (Singapore) Pte. Ltd. Étalonnage automatique du regard
WO2016146488A1 (fr) * 2015-03-13 2016-09-22 SensoMotoric Instruments Gesellschaft für innovative Sensorik mbH Procédé d'identification automatique d'au moins un utilisateur d'un suiveur oculaire et suiveur oculaire
CN106462733A (zh) * 2014-05-19 2017-02-22 微软技术许可有限责任公司 视线检测校准
CN106662917A (zh) * 2014-04-11 2017-05-10 眼球控制技术有限公司 眼睛跟踪校准系统和方法
US9727135B2 (en) 2014-04-30 2017-08-08 Microsoft Technology Licensing, Llc Gaze calibration
CN107407977A (zh) * 2015-03-05 2017-11-28 索尼公司 信息处理设备、控制方法及程序
DE102016210288A1 (de) * 2016-06-10 2017-12-14 Volkswagen Aktiengesellschaft Bedienvorrichtung mit Eyetrackereinheit und Verfahren zum Kalibrieren einer Eyetrackereinheit einer Bedienvorrichtung
US9851791B2 (en) 2014-11-14 2017-12-26 Facebook, Inc. Dynamic eye tracking calibration
US9961258B2 (en) 2015-02-23 2018-05-01 Facebook, Inc. Illumination system synchronized with image sensor
US10067561B2 (en) 2014-09-22 2018-09-04 Facebook, Inc. Display visibility based on eye convergence
WO2019014756A1 (fr) * 2017-07-17 2019-01-24 Thalmic Labs Inc. Systèmes et procédés d'étalonnage dynamique destinés à des dispositifs d'affichage tête haute à porter sur soi
CN110502099A (zh) * 2018-05-16 2019-11-26 托比股份公司 可靠地检测注视与刺激之间的关联的方法
CN112148112A (zh) * 2019-06-27 2020-12-29 北京七鑫易维科技有限公司 校准方法及装置、非易失性存储介质和处理器
US11194161B2 (en) 2018-02-09 2021-12-07 Pupil Labs Gmbh Devices, systems and methods for predicting gaze-related parameters
US11393251B2 (en) 2018-02-09 2022-07-19 Pupil Labs Gmbh Devices, systems and methods for predicting gaze-related parameters
US11537202B2 (en) 2019-01-16 2022-12-27 Pupil Labs Gmbh Methods for generating calibration data for head-wearable devices and eye tracking system
US11556741B2 (en) 2018-02-09 2023-01-17 Pupil Labs Gmbh Devices, systems and methods for predicting gaze-related parameters using a neural network
US11676422B2 (en) 2019-06-05 2023-06-13 Pupil Labs Gmbh Devices, systems and methods for predicting gaze-related parameters
CN118860141A (zh) * 2024-07-01 2024-10-29 成都集思鸣智科技有限公司 眼动追踪校准方法、装置、系统及存储介质
US12140771B2 (en) 2020-02-19 2024-11-12 Pupil Labs Gmbh Eye tracking module and head-wearable device
US12353617B2 (en) 2019-06-18 2025-07-08 Pupil Labs Gmbh Systems and methods for determining one or more parameters of a user's eye

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP1209553A1 (fr) 1998-02-20 2002-05-29 Thomas E. Hutchinson Détecteur de direction du regard
EP1906296A2 (fr) * 2006-09-27 2008-04-02 Malvern Scientific Solutions Limited Procédé d'utilisation d'un système de suivi de direction du regard pour contrôler un ordinateur
WO2008141460A1 (fr) * 2007-05-23 2008-11-27 The University Of British Columbia Procédés et appareils pour estimer un point de regard en trois dimensions
WO2010071928A1 (fr) * 2008-12-22 2010-07-01 Seeing Machines Limited Étalonnage automatique d'un algorithme de direction du regard à partir du comportement de l'utilisateur

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP1209553A1 (fr) 1998-02-20 2002-05-29 Thomas E. Hutchinson Détecteur de direction du regard
EP1906296A2 (fr) * 2006-09-27 2008-04-02 Malvern Scientific Solutions Limited Procédé d'utilisation d'un système de suivi de direction du regard pour contrôler un ordinateur
WO2008141460A1 (fr) * 2007-05-23 2008-11-27 The University Of British Columbia Procédés et appareils pour estimer un point de regard en trois dimensions
WO2010071928A1 (fr) * 2008-12-22 2010-07-01 Seeing Machines Limited Étalonnage automatique d'un algorithme de direction du regard à partir du comportement de l'utilisateur

Cited By (46)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2014125380A3 (fr) * 2013-02-14 2014-11-06 The Eye Tribe Aps Systèmes et procédés permettant un étalonnage de commande de suivi des yeux
US9791927B2 (en) 2013-02-14 2017-10-17 Facebook, Inc. Systems and methods of eye tracking calibration
US9693684B2 (en) 2013-02-14 2017-07-04 Facebook, Inc. Systems and methods of eye tracking calibration
US9189095B2 (en) 2013-06-06 2015-11-17 Microsoft Technology Licensing, Llc Calibrating eye tracking system by touch input
CN105378595A (zh) * 2013-06-06 2016-03-02 微软技术许可有限责任公司 通过触摸输入校准眼睛跟踪系统
CN105378595B (zh) * 2013-06-06 2018-12-07 微软技术许可有限责任公司 通过触摸输入校准眼睛跟踪系统的方法
WO2014197408A1 (fr) * 2013-06-06 2014-12-11 Microsoft Corporation Étalonnage de système d'oculométrie par entrée tactile
US9256785B2 (en) * 2013-11-12 2016-02-09 Fuji Xerox Co., Ltd. Identifying user activities using eye tracking data, mouse events, and keystrokes
US20150131850A1 (en) * 2013-11-12 2015-05-14 Fuji Xerox Co., Ltd. Identifying user activities using eye tracking data, mouse events, and keystrokes
DE102013019117A1 (de) 2013-11-15 2015-05-21 Audi Ag Verfahren zum Kalibrieren einer Blickrichtungserfassungseinrichtung für ein Kraftfahrzeug, Kalibrierungseinrichtung und Kraftfahrzeug
US9785233B2 (en) 2014-04-11 2017-10-10 Facebook, Inc. Systems and methods of eye tracking calibration
CN106662917A (zh) * 2014-04-11 2017-05-10 眼球控制技术有限公司 眼睛跟踪校准系统和方法
EP2940555A1 (fr) * 2014-04-22 2015-11-04 Lenovo (Singapore) Pte. Ltd. Étalonnage automatique du regard
US9727135B2 (en) 2014-04-30 2017-08-08 Microsoft Technology Licensing, Llc Gaze calibration
US9727136B2 (en) * 2014-05-19 2017-08-08 Microsoft Technology Licensing, Llc Gaze detection calibration
CN106462733A (zh) * 2014-05-19 2017-02-22 微软技术许可有限责任公司 视线检测校准
US20170336867A1 (en) * 2014-05-19 2017-11-23 Microsoft Technology Licensing, Llc Gaze detection calibration
CN106462733B (zh) * 2014-05-19 2019-09-20 微软技术许可有限责任公司 一种用于视线检测校准的方法和计算设备
US10248199B2 (en) 2014-05-19 2019-04-02 Microsoft Technology Licensing, Llc Gaze detection calibration
CN110569750A (zh) * 2014-05-19 2019-12-13 微软技术许可有限责任公司 一种用于视线检测校准的方法和计算设备
US10067561B2 (en) 2014-09-22 2018-09-04 Facebook, Inc. Display visibility based on eye convergence
US9851791B2 (en) 2014-11-14 2017-12-26 Facebook, Inc. Dynamic eye tracking calibration
US10013056B2 (en) 2014-11-14 2018-07-03 Facebook, Inc. Dynamic eye tracking calibration
US9961258B2 (en) 2015-02-23 2018-05-01 Facebook, Inc. Illumination system synchronized with image sensor
CN107407977A (zh) * 2015-03-05 2017-11-28 索尼公司 信息处理设备、控制方法及程序
EP3267295A4 (fr) * 2015-03-05 2018-10-24 Sony Corporation Dispositif de traitement d'information, procédé de commande et programme
US11003245B2 (en) 2015-03-13 2021-05-11 Apple Inc. Method for automatically identifying at least one user of an eye tracking device and eye tracking device
WO2016146488A1 (fr) * 2015-03-13 2016-09-22 SensoMotoric Instruments Gesellschaft für innovative Sensorik mbH Procédé d'identification automatique d'au moins un utilisateur d'un suiveur oculaire et suiveur oculaire
US10521012B2 (en) 2015-03-13 2019-12-31 Apple Inc. Method for automatically identifying at least one user of an eye tracking device and eye tracking device
DE102016210288A1 (de) * 2016-06-10 2017-12-14 Volkswagen Aktiengesellschaft Bedienvorrichtung mit Eyetrackereinheit und Verfahren zum Kalibrieren einer Eyetrackereinheit einer Bedienvorrichtung
US10635170B2 (en) 2016-06-10 2020-04-28 Volkswagen Aktiengesellschaft Operating device with eye tracker unit and method for calibrating an eye tracker unit of an operating device
WO2019014756A1 (fr) * 2017-07-17 2019-01-24 Thalmic Labs Inc. Systèmes et procédés d'étalonnage dynamique destinés à des dispositifs d'affichage tête haute à porter sur soi
US11340461B2 (en) 2018-02-09 2022-05-24 Pupil Labs Gmbh Devices, systems and methods for predicting gaze-related parameters
US11194161B2 (en) 2018-02-09 2021-12-07 Pupil Labs Gmbh Devices, systems and methods for predicting gaze-related parameters
US11393251B2 (en) 2018-02-09 2022-07-19 Pupil Labs Gmbh Devices, systems and methods for predicting gaze-related parameters
US11556741B2 (en) 2018-02-09 2023-01-17 Pupil Labs Gmbh Devices, systems and methods for predicting gaze-related parameters using a neural network
CN110502099B (zh) * 2018-05-16 2023-06-23 托比股份公司 可靠地检测注视与刺激之间的关联的方法
CN110502099A (zh) * 2018-05-16 2019-11-26 托比股份公司 可靠地检测注视与刺激之间的关联的方法
US11537202B2 (en) 2019-01-16 2022-12-27 Pupil Labs Gmbh Methods for generating calibration data for head-wearable devices and eye tracking system
US11676422B2 (en) 2019-06-05 2023-06-13 Pupil Labs Gmbh Devices, systems and methods for predicting gaze-related parameters
US12154383B2 (en) 2019-06-05 2024-11-26 Pupil Labs Gmbh Methods, devices and systems for determining eye parameters
US12353617B2 (en) 2019-06-18 2025-07-08 Pupil Labs Gmbh Systems and methods for determining one or more parameters of a user's eye
CN112148112A (zh) * 2019-06-27 2020-12-29 北京七鑫易维科技有限公司 校准方法及装置、非易失性存储介质和处理器
CN112148112B (zh) * 2019-06-27 2024-02-06 北京七鑫易维科技有限公司 校准方法及装置、非易失性存储介质和处理器
US12140771B2 (en) 2020-02-19 2024-11-12 Pupil Labs Gmbh Eye tracking module and head-wearable device
CN118860141A (zh) * 2024-07-01 2024-10-29 成都集思鸣智科技有限公司 眼动追踪校准方法、装置、系统及存储介质

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