Abstract: Disclosed are systems, methods, and non-transitory computer-readable media for varied depth determination using, stereo vision and phase detection auto focus (PDAF). Computer stereo vision (stereo vision) is used to extract three-dimensional information from digital images. To utilize stereo vison, two optical sensors are displaced horizontally from one another and used to capture images depicting two differing views of a real-world environment from two different vantage points. The relative depth of the objects captured in the images is determined using triangulation by comparing the relative positions of the objects in the two images. For example, the relative positions of matching objects (e.g., features) identified in the captured images are used along with the known orientation of the optical sensors (e.g., distance between the optical sensors, vantage points the optical sensors) to estimate the depth of the objects.

Abstract: A system for deformation or bending correction in an Augmented Reality (AR) system. Sensors are positioned in a frame of a head-worn AR system to sense forces or pressure acting on the frame by temple pieces attached to the frame. The sensed forces or pressure are used in conjunction with a model of the frame to determine a corrected model of the frame. The corrected model is used to correct video data captured by the AR system and to correct a video virtual overlay that is provided to a user wearing the head-worn AR system.

Abstract: A system for hand tracking for an Augmented Reality (AR) system. The AR system uses a camera of the AR system to capture tracking video frame data of a hand of a user of the AR system. The AR system generates a skeletal model based on the tracking video frame data and determines a location of the hand of the user based on the skeletal model. The AR system causes a steerable camera of the AR system to focus on the hand of the user.

Abstract: An electronic eyewear device with a shape memory alloy (SMA) actuator to apply torque to the eyewear temples. The torque presses the eyewear temples against the side of a user's head for a snug and comfortable fit. The SMA actuator allows one size of eyewear frames to fit a larger range of users, thereby reducing the number of sizes required to be manufactured for the electronic eyewear device.

Abstract: A system for hand tracking for an Augmented Reality (AR) system. The AR system uses a camera of the AR system to capture tracking video frame data of a hand of a user of the AR system. The AR system generates a skeletal model based on the tracking video frame data and determines a location of the hand of the user based on the skeletal model. The AR system causes a steerable camera of the AR system to focus on the hand of the user.

Abstract: Disclosed are systems, methods, and non-transitory computer-readable media for varied depth determination using stereo vision and phase detection auto focus (PDAF). Computer stereo vision (stereo vision) is used to extract three-dimensional information from digital images. To utilize stereo vision, two optical sensors are displaced horizontally from one another and used to capture images depicting two differing views of a real-world environment from two different vantage points. The relative depth of the objects captured in the images is determined using triangulation by comparing the relative positions of the objects in the two images. For example, the relative positions of matching objects (e.g., features) identified in the captured images are used along with the known orientation of the optical sensors (e.g., distance between the optical sensors, vantage points the optical sensors) to estimate the depth of the objects.

Abstract: Disclosed are systems, methods, and non-transitory computer-readable media for varied depth determination using, stereo vision and phase detection auto focus (PDAF). Computer stereo vision (stereo vision) is used to extract three-dimensional information from digital images. To utilize stereo vison, two optical sensors are displaced horizontally from one another and used to capture images depicting two differing views of a real-world environment from two different vantage points. The relative depth of the objects captured in the images is determined using triangulation by comparing the relative positions of the objects in the two images. For example, the relative positions of matching objects (e.g., features) identified in the captured images are used along with the known orientation of the optical sensors (e.g., distance between the optical sensors, vantage points the optical sensors) to estimate the depth of the objects.

Abstract: A miniaturized active dual pixel stereo system and method for close range depth extraction includes a projector adapted to project a locally distinct projected pattern onto an image of a scene and a dual pixel sensor including a dual pixel sensor array that generates respective displaced images of the scene. A three-dimensional image is generated from the displaced images of the scene by projecting the locally distinct projected pattern onto the image of the scene, capturing the respective displaced images of the scene using the dual pixel sensor, generating disparity images from the respective displaced images of the scene, determining depth to each pixel of the disparity images, and generating the three-dimensional image from the determined depth to each pixel. A three-dimensional image of a user's hands generated by the active dual pixel stereo system may be processed by gesture recognition software to provide an input to an electronic eyewear device.

Abstract: Disclosed are systems, methods, and non-transitory computer-readable media for varied depth determination using stereo vision and phase detection auto focus (PDAF). Computer stereo vision (stereo vision) is used to extract three-dimensional information from digital images. To utilize stereo vision, two optical sensors are displaced horizontally from one another and used to capture images depicting two differing views of a real-world environment from two different vantage points. The relative depth of the objects captured in the images is determined using triangulation by comparing the relative positions of the objects in the two images. For example, the relative positions of matching objects (e.g., features) identified in the captured images are used along with the known orientation of the optical sensors (e.g., distance between the optical sensors, vantage points the optical sensors) to estimate the depth of the objects.