Abstract: Generating a three-dimensional virtual representation of a three-dimensional physical object can be based on capturing or receiving a capture bundle or a set of images. In some examples, generating the virtual representation of the physical object can be facilitated by user interfaces for identifying a physical object and capturing a set of images of the physical object. Generating the virtual representation can include previewing or modifying a set of images. In some examples, generating the virtual representation of the physical object can include generating a first representation of the physical object (e.g., a point cloud) and/or generating a second three-dimensional virtual representation of the physical object (e.g., a mesh reconstruction). In some examples, a visual indication of the progress of the image capture process and/or the generation of the virtual representation of the three-dimensional object can be displayed, such as in a capture user interface.

Abstract: Various implementations generate geometric representations based on depth information detected in physical environments. For example, an example process may include acquiring sensor data of an object in a physical environment, the sensor data including images of a physical environment captured via a camera on the device. The process may further include generating a three-dimensional (3D) voxel representation of the object based on the images. The process may further include determining signed distance values (SDVs) of voxel corners for voxels of the 3D voxel representation, the SDVs representing distances to surfaces of the object; determining occupancy data for the voxels of the 3D voxel representation, the occupancy data corresponding to whether the voxels are occupied by the object. The process may further include generating a 3D mesh of the object based on the SDVs of the voxel corners and the occupancy data for the 3D voxel representation.

Abstract: Techniques are disclosed relating to biometric authentication, e.g., facial recognition. In some embodiments, a device is configured to verify that image data from a camera unit exhibits a pseudo-random sequence of image capture modes and/or a probing pattern of illumination points (e.g., from lasers in a depth capture mode) before authenticating a user based on recognizing a face in the image data. In some embodiments, a secure circuit may control verification of the sequence and/or the probing pattern. In some embodiments, the secure circuit may verify frame numbers, signatures, and/or nonce values for captured image information. In some embodiments, a device may implement one or more lockout procedures in response to biometric authentication failures. The disclosed techniques may reduce or eliminate the effectiveness of spoofing and/or replay attacks, in some embodiments.

Abstract: Generating a three-dimensional virtual representation of a three-dimensional physical object can be based on capturing or receiving a capture bundle or a set of images. In some examples, generating the virtual representation of the physical object can be facilitated by user interfaces for identifying a physical object and capturing a set of images of the physical object. Generating the virtual representation can include previewing or modifying a set of images. In some examples, generating the virtual representation of the physical object can include generating a first representation of the physical object (e.g., a point cloud) and/or generating a second three-dimensional virtual representation of the physical object (e.g., a mesh reconstruction). In some examples, a visual indication of the progress of the image capture process and/or the generation of the virtual representation of the three-dimensional object can be displayed, such as in a capture user interface.

Abstract: In some examples, an electronic device in communication with a display and one or more input devices performs a capture process for generating a virtual representation of an environment. In some examples, performing the capture process includes, during a first phase of the capture process, presenting, via the display, one or more first virtual elements in a representation of the environment for positioning the electronic device in a first manner while capturing images of the environment. In some examples, performing the capture process includes, during a second phase of the capture process, presenting, via the display, one or more second virtual elements in the representation of the environment for positioning the electronic device in a second manner while capturing images of the environment.

Abstract: Techniques are disclosed relating to biometric authentication, e.g., facial recognition. In some embodiments, a device is configured to verify that image data from a camera unit exhibits a pseudo-random sequence of image capture modes and/or a probing pattern of illumination points (e.g., from lasers in a depth capture mode) before authenticating a user based on recognizing a face in the image data. In some embodiments, a secure circuit may control verification of the sequence and/or the probing pattern. In some embodiments, the secure circuit may verify frame numbers, signatures, and/or nonce values for captured image information. In some embodiments, a device may implement one or more lockout procedures in response to biometric authentication failures. The disclosed techniques may reduce or eliminate the effectiveness of spoofing and/or replay attacks, in some embodiments.

Abstract: In some examples, an electronic device presents a user interface for generating a virtual representation of one or more physical objects of a three-dimensional environment. In some examples, while presenting a first view of the three-dimensional environment, the electronic device initiates a capture process for generating a virtual representation of at least a portion of the one or more physical objects. In some examples, the electronic device presents a virtual reticle in the three-dimensional environment in response to initiating the capture process. In some examples, the electronic device presents the virtual reticle at an orientation and/or location in the three-dimensional environment corresponding to a feature of a surface targeted by the virtual reticle.

Abstract: An exemplary process acquires frames of image data in a physical environment including an object, tracks an orientation of the device with respect to the object during the acquiring of the frames, selects keyframes from the frames based on detecting a first condition and selecting a first frame as a keyframe based on a first keyframe selection criterion and the orientation of the device at the first frame, and based on detecting a second condition, selecting a second frame as a keyframe based on a second keyframe selection criterion and the orientation of the device at the second frame, wherein the second keyframe selection criterion is different than the first keyframe selection criterion, and generates an object scan (e.g., a pose graph) based on the frames of image data and the selected keyframes.

Abstract: Various implementations generate a preview of a three-dimensional (3D) representation of the object. For example, an example process may include obtaining a first frame of image data of an object in a physical environment. The process may further include generating first data including data identified based on the first frame specifying one or more features identified within a plurality of 3D volumes within a 3D area. The process may further include generating a 3D representation of the object based on the first data and features from a generic model. The process may further include presenting the 3D representation of the object, where presenting the 3D representation of the object occurs prior to obtaining a second frame of image data of the object and updating the 3D representation based on the second frame.

Abstract: Various implementations disclosed herein provide feedback to a user during object scanning based on how well sensor data of the scanned object has been captured. During object scanning a user may move an electronic device with sensors (e.g., cameras, depth sensors, etc.) around an object to capture sensor data for use in generating a final 3D model of the object. Live feedback during the scanning process is enabled by assessing how well the captured sensor data represents different portions of the object. In some implementations, a 3D model is generated, updated, and assessed based on the sensor data live during the scanning process. This live 3D model may be coarser (i.e., having fewer details) than the final 3D model.

Abstract: Various implementations disclosed herein provide feedback to a user during object scanning based on how well sensor data of the scanned object has been captured. During object scanning a user may move an electronic device with sensors (e.g., cameras, depth sensors, etc.) around an object to capture sensor data for use in generating a final 3D model of the object. Live feedback during the scanning process is enabled by assessing how well the captured sensor data represents different portions of the object. In some implementations, a 3D model is generated, updated, and assessed based on the sensor data live during the scanning process. This live 3D model may be coarser (i.e., having fewer details) than the final 3D model.

Abstract: Generating a three-dimensional virtual representation of a three-dimensional physical object can be based on capturing or receiving a capture bundle or a set of images. In some examples, generating the virtual representation of the physical object can be facilitated by user interfaces for identifying a physical object and capturing a set of images of the physical object. Generating the virtual representation can include previewing or modifying a set of images. In some examples, generating the virtual representation of the physical object can include generating a first representation of the physical object (e.g., a point cloud) and/or generating a second three-dimensional virtual representation of the physical object (e.g., a mesh reconstruction). In some examples, a visual indication of the progress of the image capture process and/or the generation of the virtual representation of the three-dimensional object can be displayed, such as in a capture user interface.

Abstract: Various implementations disclosed herein include devices, systems, and methods that track a position of a device within an object-based coordinate system. An example process may include, at a device and prior to movement of an object, acquiring first images of the object, identifying three-dimensional (3D) keypoints on surfaces of the object, and tracking positions of the device in an object-based coordinate system during acquisition of the first images. The process may further include, subsequent to a movement of the object, acquiring second images of the object, identifying the 3D keypoints on surfaces of the object, and tracking positions of the device in the object-based coordinate system during acquisition of the second images based on identifying the 3D keypoints. The process may further include generating a 3D model of the object based on the first and second images and the tracked positions of the device during acquisition of the images.

Abstract: Devices, systems, and methods are disclosed for partial point cloud registration. In some implementations, a method includes obtaining a first set of three-dimensional (3D) points corresponding to an object in a physical environment, the first set of 3D points having locations in a first coordinate system, obtaining a second set of 3D points corresponding to the object in the physical environment, the second set of 3D points having locations in a second coordinate system, predicting, via a machine learning model, locations of the first set of 3D points in the second coordinate system, and determining transform parameters relating the first set of 3D points and the second set of 3D points based on the predicted location of the first set of 3D points in the second coordinate system.

Abstract: Techniques are disclosed relating to biometric authentication, e.g., facial recognition. In some embodiments, a device is configured to verify that image data from a camera unit exhibits a pseudo-random sequence of image capture modes and/or a probing pattern of illumination points (e.g., from lasers in a depth capture mode) before authenticating a user based on recognizing a face in the image data. In some embodiments, a secure circuit may control verification of the sequence and/or the probing pattern. In some embodiments, the secure circuit may verify frame numbers, signatures, and/or nonce values for captured image information. In some embodiments, a device may implement one or more lockout procedures in response to biometric authentication failures. The disclosed techniques may reduce or eliminate the effectiveness of spoofing and/or replay attacks, in some embodiments.

Abstract: A device implementing a system for providing predicted RGB images includes at least one processor configured to obtain an infrared image of a subject, and to obtain a reference RGB image of the subject. The at least one processor is further configured to provide the infrared image and the reference RGB image to a machine learning model, the machine learning model having been trained to output predicted RGB images of subjects based on infrared images and reference RGB images of the subjects. The at least one processor is further configured to provide a predicted RGB image of the subject based on output by the machine learning model.

Abstract: Various implementations disclosed herein include devices, systems, and methods that generates a three-dimensional (3D) model of an object based on images and tracked positions of a device during acquisition of the images. For example, an example process may include acquiring sensor data during movement of the device in a physical environment including an object, the sensor data including images of a physical environment acquired via a camera on the device, identifying the object in at least some of the images, tracking positions of the device during acquisition of the images based on identifying the object in the at least some of the images, the positions identifying positioning of the device with respect to a coordinate system defined based on a position and orientation of the object, and generating a 3D model of the object based on the images and positions of the device during acquisition of the images.

Abstract: Techniques are disclosed relating to biometric authentication, e.g., facial recognition. In some embodiments, a device is configured to verify that image data from a camera unit exhibits a pseudo-random sequence of image capture modes and/or a probing pattern of illumination points (e.g., from lasers in a depth capture mode) before authenticating a user based on recognizing a face in the image data. In some embodiments, a secure circuit may control verification of the sequence and/or the probing pattern. In some embodiments, the secure circuit may verify frame numbers, signatures, and/or nonce values for captured image information. In some embodiments, a device may implement one or more lockout procedures in response to biometric authentication failures. The disclosed techniques may reduce or eliminate the effectiveness of spoofing and/or replay attacks, in some embodiments.

Abstract: Generating a three-dimensional virtual representation of a three-dimensional physical object can be based on capturing or receiving a capture bundle or a set of images. In some examples, generating the virtual representation of the physical object can be facilitated by user interfaces for identifying a physical object and capturing a set of images of the physical object. Generating the virtual representation can include previewing or modifying a set of images. In some examples, generating the virtual representation of the physical object can include generating a first representation of the physical object (e.g., a point cloud) and/or generating a second three-dimensional virtual representation of the physical object (e.g., a mesh reconstruction). In some examples, a visual indication of the progress of the image capture process and/or the generation of the virtual representation of the three-dimensional object can be displayed, such as in a capture user interface.

Abstract: Generating a three-dimensional virtual representation of a three-dimensional physical object can be based on capturing or receiving a capture bundle or a set of images. In some examples, generating the virtual representation of the physical object can be facilitated by user interfaces for identifying a physical object and capturing a set of images of the physical object. Generating the virtual representation can include previewing or modifying a set of images. In some examples, generating the virtual representation of the physical object can include generating a first representation of the physical object (e.g., a point cloud) and/or generating a second three-dimensional virtual representation of the physical object (e.g., a mesh reconstruction). In some examples, a visual indication of the progress of the image capture process and/or the generation of the virtual representation of the three-dimensional object can be displayed, such as in a capture user interface.