Abstract: A computer that includes a processor and a memory, the memory including instructions executable by the processor to determine a first prediction with a machine learning system based on receiving a first image from a first camera and determine a second prediction with a machine learning system based on receiving a second image from a second camera. When the first prediction does not equal the second prediction within a user determined tolerance, determine color consistency based on comparing pixel values from the first image with a threshold determined based on previously determined pixel values, determine color correction parameters by determining pixel statistics based on pixel values from the first image to include in an image signal processing system and apply the color correction parameters to a third image from the first camera by receiving the third image at the image signal processing system.

Abstract: A computer includes a processor and a memory, and the memory stores instructions executable by the processor to sequentially activate a plurality of lamps aimed at a scene, the lamps mounted to a vehicle; receive image data of the scene generated while sequentially activating the lamps; generate a map of surface normals of the scene by executing a photometric stereo algorithm on the image data; and in response to a speed of the vehicle being below a speed threshold, navigate the vehicle based on the map of the surface normals.

Abstract: A vehicle control system includes a camera configured to capture image data depicting a field of view proximate the vehicle is disclosed. The vehicle control system further includes a plurality of light sources in connection with the vehicle and a controller. The controller is configured to activate a plurality of lights in an alternating pattern and capture light reflected from at least one object with the camera at a time and corresponding to the alternating pattern of the plurality of lights. In response to variations in the light impinging upon the at least one object from the alternating pattern, the controller is configured to identify a distance of the object.

Abstract: A computer includes a processor and a memory, and the memory stores instructions executable by the processor to sequentially activate a plurality of lamps aimed at a scene, the lamps mounted to a vehicle; receive image data of the scene generated while sequentially activating the lamps; generate a map of surface normals of the scene by executing a photometric stereo algorithm on the image data; and in response to a speed of the vehicle being below a speed threshold, navigate the vehicle based on the map of the surface normals.

Abstract: Devices, systems, and methods for generating illumination-invariant images are disclosed. A method may include activating, by a device, a camera to capture first image data; while the camera is capturing the first image data, activating of a first, light source; receiving the first image data, the first image data having pixels having first color values; identifying first light generated by the first light source while the camera is capturing the first image data; identifying, based on the first image data, second light generated by a second light source; generating, based on the first light and the second light, second image data that are illumination-invariant; and presenting the second image data.

Abstract: Removal of PII is provided. Sensor data is captured using sensors of a vehicle. Object detection is performed on the sensor data to create a sematic labeling of objects in the sensor data. A model is utilized to classify regions of the sensor data with a public or private labeling according to the sematic labeling and a PII filter corresponding to a jurisdiction of a current location of the vehicle. The sensor data is utilized in accordance with the public or private labeling.

Abstract: Embodiments include systems for determining one or more properties of an object. In an embodiment, a system includes a gripping element, a light source, a probe element including an optical fiber, a spectrometer, and a processor. The gripping element is configured to grasp the object. The light source is configured to illuminate the object. The probe element is operatively coupled to the gripping element. The optical fiber is configured to transmit reflected light from the object. The spectrometer configured to: (i) receive the transmitted reflected light from the optical fiber and (ii) generate spectral data based on the received transmitted reflected light. The processor is configured to: (i) receive the generated spectral data from the spectrometer and (ii) determine one or more properties of the object based on the received generated spectral data.

Abstract: A vehicle control system includes a camera configured to capture image data depicting a field of view proximate the vehicle is disclosed. The vehicle control system further includes a plurality of light sources in connection with the vehicle and a controller. The controller is configured to activate a plurality of lights in an alternating pattern and capture light reflected from at least one object with the camera at a time and corresponding to the alternating pattern of the plurality of lights. In response to variations in the light impinging upon the at least one object from the alternating pattern, the controller is configured to identify a distance of the object.

Abstract: A computer that includes a processor and a memory, the memory including instructions executable by the processor can activate a plurality of light sources in an alternating pattern at an illumination frequency and acquire image data depicting light reflected from an object at a timing corresponding to the alternating pattern at the illumination frequency. In response to variations in the light impinging upon the object from the alternating pattern, an object contour can be determined based on estimating one or more object surface normals based on photometric stereo. One or more of object identity and object depth can be determined based on combining the object contour with the image data.

Abstract: Devices, systems, and methods for generating illumination-invariant images are disclosed. A method may include activating, by a device, a camera to capture first image data; while the camera is capturing the first image data, activating of a first, light source; receiving the first image data, the first image data having pixels having first color values; identifying first light generated by the first light source while the camera is capturing the first image data; identifying, based on the first image data, second light generated by a second light source; generating, based on the first light and the second light, second image data that are illumination-invariant; and presenting the second image data.

Abstract: Removal of PII is provided. Sensor data is captured using sensors of a vehicle. Object detection is performed on the sensor data to create a sematic labeling of objects in the sensor data. A model is utilized to classify regions of the sensor data with a public or private labeling according to the sematic labeling and a PII filter corresponding to a jurisdiction of a current location of the vehicle. The sensor data is utilized in accordance with the public or private labeling.

Abstract: Devices, systems, and methods for enhancing color consistency in images are disclosed. A method may include activating, by a device, a camera to capture first image data; while the camera is capturing the first image data, activating of a first light source; receiving the first image data, the first image data having pixels having first color values; identifying first light generated by the first light source while the camera is capturing the first image data; identifying, based on the first image data, second light generated by a second light source; generating, based on the first light, the second light, and a distance between the camera and the vehicle light, second color values for the pixels of the first image data; generating second image data based on the second color values; and presenting the second image data.

Abstract: The disclosure is generally directed to systems and methods for sharing a video feed of a camera among multiple image processing components in a vehicle. A first priority may be applied to a first image processing component that performs a first image processing function. A second priority that is lower than the first priority, is applied to a second image processing component that performs a second image processing function. The first function may be deemed more important than the second function due to various reasons. Consequently, the first image processing component is offered priority to apply a first set of camera settings on the camera. The second image processing component may prefer to apply a different set of camera settings for executing the second image processing function. An access arbitrator allows the second image processing component to do so when the first image processing component relinquishes control of the camera.

Abstract: The disclosure is generally directed to systems and methods for sharing a video feed of a camera among multiple image processing components in a vehicle. A first priority may be applied to a first image processing component that performs a first image processing function. A second priority that is lower than the first priority, is applied to a second image processing component that performs a second image processing function. The first function may be deemed more important than the second function due to various reasons. Consequently, the first image processing component is offered priority to apply a first set of camera settings on the camera. The second image processing component may prefer to apply a different set of camera settings for executing the second image processing function. An access arbitrator allows the second image processing component to do so when the first image processing component relinquishes control of the camera.