Abstract: A method performed by a server can include receiving, from a first computing device, multiple captured images that were captured by a camera, the multiple captured images including instances of a calibration image presented by a display included in a second computing device, the calibration image being a representation of a calibration image file; and based on the multiple captured images, calibrating the camera.

Abstract: A system and method of detecting display fit measurements and/or ophthalmic measurements for a head mounted wearable computing device including a display device is provided. An image of a fitting frame worn by a user of the computing device is captured by the user, through an application running on the computing device. One or more visual markers each including a distinct pattern are detected in the image including the fitting frame. A model of the fitting frame, and configuration information associated with the fitting frame, are determined based on the detection of the pattern. A three-dimensional pose of the fitting frame is determined based on the detected visual marker(s) and patterns, and the configuration information associated with the fitting frame. The display device of the head mounted wearable computing device can then be configured based on the three-dimensional pose of the fitting frame as captured in the image.

Abstract: Systems and methods for validation of modeling and simulation systems that provide for the virtual try-on of wearable devices, such as glasses, by a user, and for the virtual fitting of selected wearable devices for the user. Wearable fit measurements, display fit measurements, ophthalmic fit measurements and other such measurements associated with the fit and function of the wearable device may be detected from image data capturing the wearable device worn by the user. The detected measurements may be compared to corresponding measurements detected in a virtual simulation of the wearable device worn by the user. The comparison may provide for validation and increased accuracy/realism of the modeling and simulation systems.

Abstract: A system and method of detecting display fit measurements and/or ophthalmic measurements for a head mounted wearable computing device including a display device is provided. The system and method may include capturing image data including a face of a user to be fitted for the head mounted wearable computing device. A three-dimensional head pose and gaze measurements may be extracted and a three-dimensional model may be developed from the captured image data. The system may detect display fit measurements and/or ophthalmic fit measurements from the three-dimensional model, and may provide one or more head mounted wearable computing devices that meet the display fit and/or ophthalmic fit requirements.

Abstract: A method performed by a server can include sending a first webpage to a first computing device, the first computing device including a camera, the first webpage including an image-capturing function and including an instruction for a user to obtain a second webpage via a second computing device, the second webpage including a calibration image file; receiving, from the first computing device, multiple captured images that were captured by the camera, the multiple calibration images including instances of a calibration image presented by a display included in the second computing device, the calibration image being a representation of the calibration image file; and based on the multiple captured images, calibrating the camera.

Abstract: Systems and methods for validation of modeling and simulation systems that provide for the virtual fitting of wearable devices, such as glasses, by a user. Three-dimensional modeling and simulation of test subject both with and without fitting frames corresponding to a wearable device may be captured to validate the modeling and simulation modules and associated algorithms and machine learning modules used to simulate the fit of the wearable device on a user. Validation in this manner may provide for increased accuracy/realism of the modeling and simulation systems.

Abstract: A system and method of predicting fit of a wearable device from image data obtained by a computing device together with position and orientation of the computing device is provided. The system and method may include capturing a series of frames of image data, and detecting one or more fixed features in the series of frames of image data. Position and orientation data associated with the capture of the image data is combined with the position data related to the one or more fixed features, to extract depth data from the series of frames of image data. A three-dimensional model of is generated based on the extracted depth data. The three-dimensional model is processed by a simulator and/or a machine learning model to predict fit of the wearable device for the user.

Abstract: A system and method of predicting fit of a wearable device from image data obtained by a computing device together with position and orientation of the computing device is provided. The system and method may include capturing a series of frames of image data, and detecting one or more fixed features in the series of frames of image data. Position and orientation data associated with the capture of the image data is combined with the position data related to the one or more fixed features, to extract depth data from the series of frames of image data. A three-dimensional model is generated based on the extracted depth data. The three-dimensional model and/or key points extracted therefrom, can be processed by a simulator and/or a machine learning model to predict fit of the wearable device for the user.

Abstract: A method includes receiving a face image and lens measurements of a person, and selecting a three dimensional (3-D) model of a frame of a pair of smart glasses from a plurality of 3-D models of frames for placement on the face image of the person. The pair of smart glasses includes a virtual display embedded in, or overlaid on a lens. The method further includes sizing the selected 3-D model of the frame of the pair of smart glasses for placement on the face image of person based on the lens measurements of the person, and determining a gazability of the virtual display in the 3-D model of the pair of smart glasses placed on the face image of the person.

Abstract: A method performed by a server can include sending a first webpage to a first computing device, the first computing device including a camera, the first webpage including an image-capturing function and including an instruction for a user to obtain a second webpage via a second computing device, the second webpage including a calibration image file; receiving, from the first computing device, multiple captured images that were captured by the camera, the multiple calibration images including instances of a calibration image presented by a display included in the second computing device, the calibration image being a representation of the calibration image file; and based on the multiple captured images, calibrating the camera.

Abstract: A system and method are provided for sizing and fitting a head mounted wearable computing device for a user based on image data of the head of the user, including a known reference device having a known scale. The system and method may include capturing image data including a face of the user to be fitted for the head mounted wearable computing device. The known reference device having the known scale is compared to features detected in the image data to determine a scaling factor. The scaling factor is used to size, or assign measures to facial features detected in the image data. A three-dimensional model of the head of the user may be generated from the captured image data.

Abstract: A system and method of predicting the fitting of a head mounted wearable device for a user is provided. The system detects fixed facial landmarks in image data captured by a computing device of the user. Measurements associated with the detected fixed facial landmarks may be processed by one or more machine learning models and associated algorithm(s) to predict the probability of fitting of a head mounted wearable device on the head of the user.

Abstract: A system and method of detecting scale from image data obtained by a computing device together with position and orientation of the computing device is provided. The scale may be used for the virtual selection and/or fitting of a wearable device such as a head mounted wearable device and other such wearable devices. The system and method may include capturing a series of frames of image data, and detecting one or more fixed features in the series of frames of image data. Position and orientation data associated with the capture of the image data is combined with the position data related to the one or more fixed features to set a scale that is applicable to the image data. Scale may be determined without the use of a reference object having known scale, specialized equipment, and the like.

Abstract: A system and method of detecting display fit measurements and/or ophthalmic measurements for a head mounted wearable computing device including a display device is provided. The system and method may include capturing image data including a face of a user to be fitted for the head mounted wearable computing device. A three-dimensional head pose and gaze measurements may be extracted and a three-dimensional model may be developed from the captured image data. The system may detect display fit measurements and/or ophthalmic fit measurements from the three-dimensional model, and may provide one or more head mounted wearable computing devices that meet the display fit and/or ophthalmic fit requirements.

Abstract: Systems and methods for validation of modeling and simulation systems that provide for the virtual try-on of wearable devices, such as glasses, by a user, and for the virtual fitting of selected wearable devices for the user. Wearable fit measurements, display fit measurements, ophthalmic fit measurements and other such measurements associated with the fit and function of the wearable device may be detected from image data capturing the wearable device worn by the user. The detected measurements may be compared to corresponding measurements detected in a virtual simulation of the wearable device worn by the user. The comparison may provide for validation and increased accuracy/realism of the modeling and simulation systems.

Abstract: Systems and methods for validation of modeling and simulation systems that provide for the virtual fitting of wearable devices, such as glasses, by a user. Three-dimensional modeling and simulation of test subject both with and without fitting frames corresponding to a wearable device may be captured to validate the modeling and simulation modules and associated algorithms and machine learning modules used to simulate the fit of the wearable device on a user. Validation in this manner may provide for increased accuracy/realism of the modeling and simulation systems.

Abstract: A method includes receiving a face image and lens measurements of a person, and selecting a three dimensional (3-D) model of a frame of a pair of smart glasses from a plurality of 3-D models of frames for placement on the face image of the person. The pair of smart glasses includes a virtual display embedded in, or overlaid on a lens. The method further includes sizing the selected 3-D model of the frame of the pair of smart glasses for placement on the face image of person based on the lens measurements of the person, and determining a gazability of the virtual display in the 3-D model of the pair of smart glasses placed on the face image of the person.

Abstract: A system and method of detecting display fit measurements and/or ophthalmic measurements for a head mounted wearable computing device including a display device is provided. The system and method may include capturing image data including a face of a user to be fitted for the head mounted wearable computing device. A three-dimensional head pose and gaze measurements may be extracted and a three-dimensional model may be developed from the captured image data. The system may detect display fit measurements and/or ophthalmic fit measurements from the three-dimensional model, and may provide one or more head mounted wearable computing devices that meet the display fit and/or ophthalmic fit requirements.

Abstract: A method may receive a first three-dimensional model of at least a body part of a person. A method may receive a second three-dimensional model of a wearable device comprising a head-mounted display configured to project a display. A method may predict, by at least one machine-learning model using the first three-dimensional model and the second three-dimensional model as inputs, a plurality of contact points between the first three-dimensional model and the second three-dimensional model. A method may compute a display fit value based on the plurality of contact points.

Abstract: According to an aspect, a method for designing an eye tracker on a wearable device includes selecting a first three-dimensional (3D) model of at least a head of a person, selecting a second 3D model of a wearable device, positioning a synthetic eye within the first 3D model, positioning an eye tracker component at a first location on the second 3D model, the eye tracker component including at least one of an eye tracker sensor or a light source, moving at least one of the first 3D model or the second 3D model such that at least a portion of the first 3D model contacts at least a portion of the second 3D model, and generating performance data with the eye tracker component positioned at the first location on the second 3D model.