Abstract:
A system includes a memory storing computer-readable instructions and a processor to execute the instructions to perform operations including generating multiple exposure windows for light pulses for a camera, the multiple exposure windows having a sequence comprising a first exposure window having an opening for a duration of time and each other exposure window of the multiple exposure windows having an opening for the duration of time except for a closing for a subset of the duration of time corresponding to a distance from one of a light source and the camera, wherein none of the closings of the multiple exposure windows overlaps another closing of the multiple exposure windows and determining a difference between an indication of an amount of light captured at the camera during the first exposure window and each other exposure window of the multiple exposure windows.
Abstract:
A system and method for calculating an ambient light estimate using an image sensor in a camera of a device. An array of pixels is obtained using the image sensor. A matrix of grid elements is defined. Each grid element is comprised of multiple adjacent pixels of the array of pixels. A first measurement value is generated for a grid element of the matrix of grid elements based on the pixels associated with a respective grid element. A set of grid elements are identified having a first measurement value that satisfies a brightness criteria. A weighted measurement value is calculated using the identified set of grid elements. The ambient light estimate is calculated based on the weighted measurement value and the first measurement value.
Abstract:
Aspects of the present disclosure involve example systems and methods for remote sensing of objects. In one example, a system includes a light source, a camera, a light source timing circuit, an exposure window timing circuit, and a range determination circuit. The light source timing circuit is to generate light pulses using the light source. The exposure window timing circuit generates multiple exposure windows for the light pulses for the camera, each of the multiple exposure windows representing a corresponding first range of distance from the camera. The range determination circuit processes an indication of an amount of light captured at the camera during an opening of each of the multiple exposure windows for one of the light pulses to determine a presence of an object within a second range of distance from the camera, the second range having a lower uncertainty than the first range.
Abstract:
A facial recognition authentication process may utilize images of a user's face that are captured while the user is being illuminated using both flood infrared illumination and patterned illumination (e.g., speckle pattern illumination). As the user's face is illuminated by both flood infrared illumination and patterned illumination, the captured images may include both flood infrared illumination data and depth map image data. Flood infrared illumination data may be generated from the images to assess two-dimensional features of the user in the captured images. Depth map image data may be generated from the pattern data in the images to assess three-dimensional (depth) features of the user in the captured images. The flood infrared illumination data and the depth map image data may be used separately by facial recognition authentication process to attempt to authenticate the user in the captured images as an authorized user of the device.
Abstract:
A system and method for calculating an ambient light estimate using an image sensor in a camera of a device. An array of pixels is obtained using the image sensor. A matrix of grid elements is defined. Each grid element is comprised of multiple adjacent pixels of the array of pixels. A first measurement value is generated for a grid element of the matrix of grid elements based on the pixels associated with a respective grid element. A set of grid elements are identified having a first measurement value that satisfies a brightness criteria. A weighted measurement value is calculated using the identified set of grid elements. The ambient light estimate is calculated based on the weighted measurement value and the first measurement value.
Abstract:
A light beam scanning device includes a lens element assembly which dynamically adjusts a divergence of the beam. The lens element assembly can include multiple lens elements, one or more of which translates parallel to the light beam to adjust beam divergence. Divergence adjustment can include adjusting the beam divergence along one or more cross sectional axes of the beam. Beam divergence can be adjusted between consecutive scans, during a scan, etc. Beam divergence can be adjusted based on the field of view and scan rate. Beam divergence adjustment can enable dynamic adjustment of the spot size of the beam, which can enable the apparatus to adjust between scanning a wide divergence beam to detect objects in a scene and scanning a narrow divergence beam to generate detailed point clouds of the detected objects. Beam divergence adjustment can enable adjustment of reflection point intensity, enabling detection of low-reflectivity objects.
Abstract:
Subepidermal imaging of a face may be used to assess subepidermal features such as blood vessels (e.g., veins) when the device is attempting to authenticate a user in a facial recognition authentication process. Assessment of the subepidermal features may be used to distinguish between users that have closely related facial features (e.g., siblings or twins) in situations where the facial recognition authentication process has less certainty in a decision about recognition of the user's face as an authorized user.
Abstract:
A light beam scanning device includes a lens element assembly which dynamically adjusts a divergence of the beam. The lens element assembly can include multiple lens elements, one or more of which translates parallel to the light beam to adjust beam divergence. Divergence adjustment can include adjusting the beam divergence along one or more cross sectional axes of the beam. Beam divergence can be adjusted between consecutive scans, during a scan, etc. Beam divergence can be adjusted based on the field of view and scan rate. Beam divergence adjustment can enable dynamic adjustment of the spot size of the beam, which can enable the apparatus to adjust between scanning a wide divergence beam to detect objects in a scene and scanning a narrow divergence beam to generate detailed point clouds of the detected objects. Beam divergence adjustment can enable adjustment of reflection point intensity, enabling detection of low-reflectivity objects.
Abstract:
A light beam scanning device includes a lens element assembly which dynamically adjusts a divergence of the beam. The lens element assembly can include multiple lens elements, one or more of which translates parallel to the light beam to adjust beam divergence. Divergence adjustment can include adjusting the beam divergence along one or more cross sectional axes of the beam. Beam divergence can be adjusted between consecutive scans, during a scan, etc. Beam divergence can be adjusted based on the field of view and scan rate. Beam divergence adjustment can enable dynamic adjustment of the spot size of the beam, which can enable the apparatus to adjust between scanning a wide divergence beam to detect objects in a scene and scanning a narrow divergence beam to generate detailed point clouds of the detected objects. Beam divergence adjustment can enable adjustment of reflection point intensity, enabling detection of low-reflectivity objects.
Abstract:
A system and method for estimating an ambient light condition is using an image sensor of a digital camera. An array of pixels is obtained using the image sensor. A matrix of grid elements is defined. Each grid element comprises multiple adjacent pixels of the array of pixels. A first measurement value is generated for a grid element of the matrix of grid elements based on the pixels associated with the grid element. A set of grid elements are identified having a first measurement value that satisfies a brightness criteria. A second measurement is generated using the identified set of grid elements. A simulated-light-sensor array is generated using the second measurement value. An estimate of the ambient light condition is calculated using the simulated-light-sensor array.