Abstract: A user of a computing device may interact with and control objects and applications displayed on the computing device through the user's eye movement. Detected gaze locations are correlated with actions performed by the user and compared with typical gaze locations for those actions. Based on differences between the detected and expected gaze locations, the eye tracking system can be recalibrated. An area around a gaze location encompassing a set of likely active locations can be enlarged, effectively prompting the user to interact with the desired active location again. The enlarging of the area serves to separate the active locations on the screen, reducing the probability of interpreting the user's gaze incorrectly.

Abstract: An image of a user's eyes and face may be analyzed using computer-vision algorithms. A computing device may use the image to determine the location of the user's eyes and estimate the direction in which the user is looking. The eye tracking technology may be used in a wide range of lighting conditions and with many different and varying light levels. When a user is near a light source, an automatic exposure feature in the camera may result in the user's face and eyes appearing too dark in the image, possibly reducing the likelihood of face and eye detection. Adjusting attributes such as the camera exposure time and the intensity and illumination interval of the light sources based on motion and light levels may improve detection of a user's features.

Abstract: Methods and systems to facilitate eye tracking control are provided. A user input is received at a computing device. Point of regard information associated with a user of the computing device is determined while the user input is being received. The point of regard information indicates a location on a display of the computing device at which the user is looking. An operation associated with a display object identified based on the point of regard information is performed when receipt of the user input is determined to have terminated.

Abstract: Methods and systems to facilitate eye tracking data analysis are provided. Point of regard information from a first client device of a first user is received, where the point of regard information is determined by the first client device by detecting one or more eye features associated with an eye of the first user. The point of regard information is stored. A request to access the point of regard information is received, and the point of regard information is sent in response to the request, where the point of regard information is used in a subsequent operation.

Abstract: Methods and systems to facilitate eye tracking control calibration are provided. One or more objects are displayed on a display of a device, where the one or more objects are associated with a function unrelated to a calculation of one or more calibration parameters. The one or more calibration parameters relate to a calibration of a calculation of gaze information of a user of the device, where the gaze information indicates where the user is looking. While the one or more objects are displayed, eye movement information associated with the user is determined, which indicates eye movement of one or more eye features associated with at least one eye of the user. The eye movement information is associated with a first object location of the one or more objects. The one or more calibration parameters are calculated based on the first object location being associated with the eye movement information.

Abstract: An image of a user's eyes and/or face, captured by a camera on the computing device or on a device coupled to the computing device, may be analyzed using computer-vision algorithms, such as eye tracking and gaze detection algorithms, to determine the location of the user's eyes and estimate the gaze information associated with the user. A user calibration process may be conducted to calculate calibration parameters associated with the user. These calibration parameters may be taken into account to accurately determine the location of the user's eyes and estimate the location on the display at which the user is looking. The calibration process may include determining a plane on which the user's eyes converge and relating that plane to a plane of a screen on which calibration targets are displayed.

Abstract: Systems and methods for reducing, with minimal loss, optical sensor data to be conveyed to another system for processing. An eye tracking device, such as a head-mounted display (HMD), includes a sensor and circuitry. The sensor generates image data of an eye. The circuitry receives the image data, and assigns pixels of the image data to a feature region of the eye by comparing pixel values of the pixels to a threshold value. A feature region refers to an eye region of interest for eye tracking, such as a pupil or glint. The circuitry generates encoded image data by apply an encoding algorithm, such as a run-length encoding algorithm or contour encoding algorithm, to the image data for the pixels of the feature region. The circuitry transmits the encoded image data, having a smaller data size than the image data received from the sensor, for gaze contingent content rendering.

Abstract: The invention is a method for combining eye tracking and voice-recognition control technologies to increase the speed and/or accuracy of locating and selecting objects displayed on a display screen for subsequent control and operations.

Abstract: Methods and systems to facilitate eye tracking control calibration are provided. One or more objects are displayed on a display of a device, where the one or more objects are associated with a function unrelated to a calculation of one or more calibration parameters. The one or more calibration parameters relate to a calibration of a calculation of gaze information of a user of the device, where the gaze information indicates where the user is looking. While the one or more objects are displayed, eye movement information associated with the user is determined, which indicates eye movement of one or more eye features associated with at least one eye of the user. The eye movement information is associated with a first object location of the one or more objects. The one or more calibration parameters are calculated based on the first object location being associated with the eye movement information.

Abstract: Methods and systems to facilitate eye tracking control calibration are provided. One or more objects are displayed on a display of a device, where the one or more objects are associated with a function unrelated to a calculation of one or more calibration parameters. The one or more calibration parameters relate to a calibration of a calculation of gaze information of a user of the device, where the gaze information indicates where the user is looking. While the one or more objects are displayed, eye movement information associated with the user is determined, which indicates eye movement of one or more eye features associated with at least one eye of the user. The eye movement information is associated with a first object location of the one or more objects. The one or more calibration parameters are calculated based on the first object location being associated with the eye movement information.

Abstract: Methods and systems to facilitate eye tracking control on mobile devices are provided. An image of a portion of a user is received at an eye tracking device, where the image includes reflections caused by light emitted on the user from one or more light sources located within the eye tracking device. One or more eye features associated with an eye of the user is detected using the reflections. Point of regard information is determined using the one or more eye features, where the point of regard information indicates a location on a display of a computing device coupled to the eye tracking device at which the user was looking when the image of the portion of the user was taken. The point of regard information is sent to an application capable of performing a subsequent operation using the point of regard information.

Abstract: Methods and systems to facilitate eye tracking control on mobile devices are provided. An image of a portion of a user is received at an eye tracking device, where the image includes reflections caused by light emitted on the user from one or more light sources located within the eye tracking device. One or more eye features associated with an eye of the user is detected using the reflections. Point of regard information is determined using the one or more eye features, where the point of regard information indicates a location on a display of a computing device coupled to the eye tracking device at which the user was looking when the image of the portion of the user was taken. The point of regard information is sent to an application capable of performing a subsequent operation using the point of regard information.

Abstract: The invention is a method for authenticating a system user based on eye tracking or eye parameters.

Abstract: An augmented reality (AR) device can access a library of applications or user interfaces (UIs) designed to control a set of devices. The AR device can determine which UI to present based on detection of a device to be controlled near the AR device. For example, a user wearing an AR device may look at a thermostat placed on a wall and a UI to control the thermostat may be presented to the user. The determination that the user is looking at the thermostat may be made by correlating the gaze tracking information of the user-facing camera with the location of the thermostat in an image captured by a world-facing camera. Determination of the location of the thermostat in the image can be performed using image recognition technology. The UI can be selected based on a database record pairing the UI with the thermostat.

Abstract: Eye tracking technology may be used in a wide range of lighting conditions and with many different and varying light levels. In some embodiments, an eye tracking device may employ active illumination (e.g., in the form of infrared light-emitting diodes (LEDs)). However, employing active illumination may reduce the battery life of the device. Under some circumstances (e.g., in a dark environment), the light intensity may be excessive and could be reduced, thereby reducing energy consumption and extending the battery life of the device. An algorithm may be used to adjust the duration of light in eye tracking systems that employ active illumination.

Abstract: A mobile gaze-tracking system is provided. The user operates the system by looking at the gaze tracking unit and at pre-defined regions at the fringe of the tracking unit. The gaze tracking unit may be placed on a smartwatch, a wristband, or woven into a sleeve of a garment. The unit provides feedback to the user in response to the received command input. The unit provides feedback to the user on how to position the mobile unit in front of his eyes. The gaze tracking unit interacts with one or more controlled devices via wireless or wired communications. Example devices include a lock, a thermostat, a light or a TV. The connection between the gaze tracking unit may be temporary or longer-lasting. The gaze tracking unit may detect features of the eye that provide information about the identity of the user.

Abstract: A user of a computing device may interact with the computing device through the user's eye movement. An image of the user's eyes or face, captured by a camera on the computing device, may be analyzed using computer-vision algorithms, such as eye tracking and gaze detection algorithms. During use of the computing device, one or more lights illuminating the user, or cameras viewing the user, may become blocked. The device may be equipped with more lights or cameras than are necessary to perform gaze detection by the device. In an over-equipped device, the additional lights or cameras can remain dormant until a blockage is detected. In response to a camera or light becoming blocked, a dormant light or camera can be activated.

Abstract: A user of a computing device may interact with and control objects and applications displayed on the computing device through the user's eye movement. Detected gaze locations are correlated with actions performed by the user and compared with typical gaze locations for those actions. Based on differences between the detected and expected gaze locations, the eye tracking system can be recalibrated. An area around a gaze location encompassing a set of likely active locations can be enlarged, effectively prompting the user to interact with the desired active location again. The enlarging of the area serves to separate the active locations on the screen, reducing the probability of interpreting the user's gaze incorrectly.

Abstract: Gaze information of a user can be determined by a computing device that analyzes images of the user. Gaze information of a user includes information such as the user's line of sight, point of regard information, the direction of the user's gaze, the depth of convergence of the user's gaze, and the like. The computing device is able to estimate the distance from the user at which the user is focusing (for example, at a screen near the user or at an object farther away). The visibility and display characteristics of objects displayed on the HUD may be based on the gaze information. For example, content on a heads-up display (HUD) on a windshield may be more transparent while the user is looking through the windshield and more opaque (or otherwise enhanced) while the user is focusing on the HUD.

Abstract: An image of a user's eyes and/or face, captured by a camera on the computing device or on a device coupled to the computing device, may be analyzed using computer-vision algorithms, such as eye tracking and gaze detection algorithms, to determine the location of the user's eyes and estimate the gaze information associated with the user. A user calibration process may be conducted to calculate calibration parameters associated with the user. These calibration parameters may be taken into account to accurately determine the location of the user's eyes and estimate the location on the display at which the user is looking. The calibration process may include determining a plane on which the user's eyes converge and relating that plane to a plane of a screen on which calibration targets are displayed.