Abstract: A system for imaging a retina of an eye includes a first lens for positioning proximate to the eye; a light source positioned to illuminate the eye when the system is aligned with the eye; an image sensor adapted to capture a retinal image of the retina through the first lens; an aperture disposed along an optical path extending from the image sensor and passing through the first lens; and a processing apparatus communicatively coupled to the image sensor and the light source, wherein the processing apparatus includes logic that when executed by the processing apparatus causes the system to perform operations including: illuminating the eye with the light source and capturing the retinal image with the image sensor.

Abstract: A system for imaging a retina includes an optical relay system having a first lens for positioning proximate to an eye, a light source positioned to illuminate the eye, an image sensor positioned to capture a retinal image of the retina through the first lens, an aperture disposed between the image sensor and the first lens along an optical path extending from the image sensor through the first lens, and a processing apparatus. The aperture surrounds the optical path and is adapted to block off-axis reflections from the eye.

Abstract: In one embodiment, a computing system may receive an uncompressed image from a camera. The computing system may generate a compressed image by performing a compression process on the uncompressed image, wherein a decompressed image may be generated as a byproduct during the compression process. The computing system may send the decompressed image to a machine-learning model that was trained using decompressed images. The computing system may generate, by the machine-learning model, an output based on the decompressed image. The computing system may provide operational instructions to a vehicle based on the output.

Abstract: A system for imaging a retina includes an optical relay system having a first lens for positioning proximate to an eye, a light source positioned to illuminate the eye, an image sensor positioned to capture a retinal image of the retina through the first lens, an aperture disposed between the image sensor and the first lens along an optical path extending from the image sensor through the first lens, and a processing apparatus. The aperture surrounds the optical path and is adapted to block off-axis reflections from the eye.

Abstract: In one embodiment, a method includes, by a computing device of a first sensor receiving synchronization information from a controller. The synchronization information being generated based on a clock of the controller. The method also includes determining, based on the synchronization information, a first offset between a first clock of the first sensor and the clock of the controller; storing the first offset; and synchronizing, based on the stored first offset and the first clock of the first sensor, a first data capture by the first sensor with a second data capture by a second sensor. The first data capture and the second data capture being requested by the controller.

Abstract: A method of imaging an interior of an eye includes illuminating the interior of the eye with one or more beams of light from a light source, and said illuminating is configured to trigger a change to a pupil of the eye. An image sensor captures a sequence of images of light reflected by the interior of the eye during an expected timeframe when a width of the pupil is changing in response to said illuminating. A processing apparatus combines images in the sequence of images to form a composite image having a larger depth of field than a depth of field of each of the images in the sequence of images. The depth of field for each of the images corresponds to the width of the pupil when each of the images is captured.

Abstract: In particular embodiments, a computing system may detect a number of objects captured within an overlapping region between a first field of view associated with a first camera and a second field of view associated with a second camera. The system may determine a respective priority ranking for each of the objects. The system may select an object from the objects based on the respective priority ranking for the object. The system may determine, for the first camera, a first lighting condition associated with the first field of view. The system may determine, for the second camera, a second lighting condition associated with the second field of view. The system may determine a shared exposure time for the selected object based on the first lighting condition and the second lighting condition. The system may cause at least one image of the selected object to be captured using the shared exposure time.

Abstract: In one embodiment, a method includes, by a computing device of a first sensor receiving synchronization information from a controller. The synchronization information being generated based on a clock of the controller. The method also includes determining, based on the synchronization information, a first offset between a first clock of the first sensor and the clock of the controller; storing the first offset; and synchronizing, based on the stored first offset and the first clock of the first sensor, a first data capture by the first sensor with a second data capture by a second sensor. The first data capture and the second data capture being requested by the controller.

Abstract: In one embodiment, a method includes, by a computing device of a first sensor receiving synchronization information from a controller. The synchronization information being generated based on a clock of the controller. The method also includes determining, based on the synchronization information, a first offset between a first clock of the first sensor and the clock of the controller; storing the first offset; and synchronizing, based on the stored first offset and the first clock of the first sensor, a first data capture by the first sensor with a second data capture by a second sensor. The first data capture and the second data capture being requested by the controller.

Abstract: In particular embodiments, a computing system may detect a number of objects captured within on overlapping region between a first field of view associated with a first camera and a second field of view associated with a second camera. The system may determine a respective priority ranking for each of the objects. The system may select an object from the objects based on the respective priority ranking for the object. The system may determine, for the first camera, a first lighting condition associated with the first field of view. The system may determine, for the second camera, a second lighting condition associated with the second field of view. The system may determine a shared exposure time for the selected object based on the first lighting condition and the second lighting condition. The system may cause at least one image of the selected object to be captured using the shared exposure time.

Abstract: In one embodiment, a computing system may determine a first target region within a first field of view of a first camera and a second target region within a second field of view of a second camera. The first field of view and the second field of view may be partially overlapping. The system may determine first lighting conditions of the first target region. The system may determine a first exposure time for at least the first camera and the second camera based at least in part on the determined first lighting conditions. The system may instruct the first camera and the second camera to take pictures using the determined first exposure time.

Abstract: In one embodiment, a computing system may receive an uncompressed image from a camera. The computing system may generate a compressed image by performing a compression process on the uncompressed image, wherein a decompressed image may be generated as a byproduct during the compression process. The computing system may send the decompressed image to a machine-learning model that was trained using decompressed images. The computing system may generate, by the machine-learning model, an output based on the decompressed image. The computing system may provide operational instructions to a vehicle based on the output.

Abstract: In one embodiment, a computing system may determine a first target region within a first field of view of a first camera and a second target region within a second field of view of a second camera. The first field of view and the second field of view may be partially overlapping. The system may determine first lighting conditions of the first target region. The system may determine a first exposure time for at least the first camera and the second camera based at least in part on the determined first lighting conditions. The system may instruct the first camera and the second camera to take pictures using the determined first exposure time.

Abstract: In one embodiment, a method includes, by a computing device of a first sensor receiving synchronization information from a controller. The synchronization information being generated based on a clock of the controller. The method also includes determining, based on the synchronization information, a first offset between a first clock of the first sensor and the clock of the controller; storing the first offset; and synchronizing, based on the stored first offset and the first clock of the first sensor, a first data capture by the first sensor with a second data capture by a second sensor. The first data capture and the second data capture being requested by the controller.

Abstract: A method of imaging an interior of an eye includes illuminating the interior of the eye with one or more beams of light from a light source, and said illuminating is configured to trigger a change to a pupil of the eye. An image sensor captures a sequence of images of light reflected by the interior of the eye during an expected timeframe when a width of the pupil is changing in response to said illuminating. A processing apparatus combines images in the sequence of images to form a composite image having a larger depth of field than a depth of field of each of the images in the sequence of images. The depth of field for each of the images corresponds to the width of the pupil when each of the images is captured.