Abstract: A computer-implemented method of image-to-image translation that, when executed by data processing hardware, causes the data processing hardware to perform operations comprising applying an inversion technique to an input image to generate a source-domain seed, translating the source-domain seed to a target-domain seed using a translation module, and sampling the target-domain seed to generate a denoised code.

Abstract: A method includes receiving perception images of an area surrounding the vehicle with at least one sensor and detecting at least one perception task from the perception images with the at least one perception task identifying at least one neighboring vehicle. The method calculates a risk factor for the at least one neighboring vehicle by recognizing a behavior of the at least one neighboring vehicle from the perception images and plans the path for the vehicle based on the at least one perception task and the risk factor. The path is then executed for the vehicle.

Abstract: A method for simulating images with aberrations, or a non-transitory computer-readable storage medium on which are recorded instructions. The method includes ray tracing planes of objects to produce plane images, estimating point spread function from the ray tracing, and creating one or more perceived images. The method may include feeding a ray-tracing simulator with one more synthetic impulse images or scenes. The method may include feeding the perceived images into a perception pipeline and generating synthetic imagery from the plane images and the perceived images.

Abstract: A method of controlling a color display screen aboard a motor vehicle includes performing, via a host computer, a color calibration test of a user of the motor vehicle in which the user is subjected to a calibrated set of color-coded test information. The method includes receiving a color perception response of the user to the calibrated set of color-coded test information via the host computer. Additionally, the method includes mapping a reduced visual gamut of the user via the host computer using the color perception response, and then commanding adjustment of user-specific color settings of the motor vehicle using the reduced visual gamut to thereby accommodate a color perception deficiency of the user.

Abstract: A visual perception system includes a scanning camera, color sensor with color filter array (CFA), and a classifier node. The camera captures full color pixel images of a target object, e.g., a traffic light, and processes the pixel images through a narrow band pass filter (BPF), such that the narrow BPF outputs monochromatic images of the target object. The color sensor and CFA receive the monochromatic images. The color sensor has at least three color channels each corresponding to different colors of spectral data in the monochromatic images. The classifier node uses a predetermined classification decision tree to classify constituent pixels of the monochromatic images into different color bins as a corresponding color of interest. The color of interest may be used to perform a control action, e.g., via an automated driver assist system (ADAS) control unit or an indicator device.

Abstract: A method of planning a path for a vehicle. The method includes receiving perception images of an area surrounding the vehicle with at least one sensor and detecting at least one perception task from the perception images with the at least one perception task identifying at least one neighboring vehicle. The method calculates a risk factor for the at least one neighboring vehicle by recognizing a behavior of the at least one neighboring vehicle from the perception images and plans the path for the vehicle based on the at least one perception task and the risk factor. The path is then executed for the vehicle.

Abstract: A method of planning a path for a vehicle is disclosed herein. The method includes receiving a plurality of perception images. At least one perception task is detected from the plurality of perception images including identifying a neighboring vehicle. A plurality of vehicle descriptors of the neighboring vehicle is recognized, and a plurality of predetermined vehicle descriptor sets are associated with a corresponding one of a plurality of cluster values with each cluster value being associated with a risk factor. The risk factor is determined based on mapping the plurality of vehicle descriptors recognized for the neighboring vehicle onto one of the plurality of predetermined vehicle descriptor sets and assigning the risk factor associated with the cluster value to the neighboring vehicle. The path for the vehicle is planned based on the at least one perception task and the risk factor and the path is executed for the vehicle.

Abstract: A method of controlling a color display screen aboard a motor vehicle includes performing, via a host computer, a color calibration test of a user of the motor vehicle in which the user is subjected to a calibrated set of color-coded test information. The method includes receiving a color perception response of the user to the calibrated set of color-coded test information via the host computer. Additionally, the method includes mapping a reduced visual gamut of the user via the host computer using the color perception response, and then commanding adjustment of user-specific color settings of the motor vehicle using the reduced visual gamut to thereby accommodate a color perception deficiency of the user.

Abstract: A vehicle and a system and method of operating the vehicle based on a gesture made by a traffic director. The system includes a camera and at least one neural network. The camera obtains an image of a flag operator. The at least one neural network is to generates an encoded hand vector based on a configuration of a hand of the traffic director from the image, combines a skeleton of the traffic director generated from the image and the encoded hand vector to generate a representation vector, and predicts a gesture of the traffic director from the representation vector.

Abstract: An optical system, and method related thereto, includes a camera configured to capture images. The camera has an adaptive aperture plane configured to change both an aperture size and an aperture shape in response to an aperture signal. The camera also includes a first polarized surface and second polarized surface positioned relative to the adaptive aperture plane, such that light strikes the first polarized surface, the adaptive aperture plane, then the second polarized surface. First and second lenses may be located on opposite sides of the adaptive aperture plane. An image sensor is beyond the second polarized surface and configured to output image signals, and a processor is configured to execute image perception algorithms based on the image signals. The image perception algorithms alter the aperture size and the aperture shape by sending an aperture signal from the processor to the camera for subsequent captured images.

Abstract: A visual perception system includes a scanning camera, color sensor with color filter array (CFA), and a classifier node. The camera captures full color pixel images of a target object, e.g., a traffic light, and processes the pixel images through a narrow band pass filter (BPF), such that the narrow BPF outputs monochromatic images of the target object. The color sensor and CFA receive the monochromatic images. The color sensor has at least three color channels each corresponding to different colors of spectral data in the monochromatic images. The classifier node uses a predetermined classification decision tree to classify constituent pixels of the monochromatic images into different color bins as a corresponding color of interest. The color of interest may be used to perform a control action, e.g., via an automated driver assist system (ADAS) control unit or an indicator device.

Abstract: A vehicle communication and control system includes a first vehicle in signal communication with a remote computing system and/or a second vehicle. The first vehicle includes a sensor configured to capture a raw image having a first image volume and including at least one target object. An image encoder included in the vehicle converts the raw image into a masked image having a second image volume that is less than the first image volume. A segmentation unit included in the remote computing system and/or the second vehicle determines the at least one target object from the masked image, generates a masked segmented image including a sparse segmentation of the at least one target object, and converts the sparse segmentation of the at least one target object into at least one recovered segmented target object indicative of the at least one target object.

Abstract: A vehicle and a system and method of operating the vehicle based on a gesture made by a traffic director. The system includes a camera and at least one neural network. The camera obtains an image of a flag operator. The at least one neural network is to generates an encoded hand vector based on a configuration of a hand of the traffic director from the image, combines a skeleton of the traffic director generated from the image and the encoded hand vector to generate a representation vector, and predicts a gesture of the traffic director from the representation vector.

Abstract: A method in a rate adaptive system includes categorizing, by an encoder, a plurality of clusters of data in a segmented image into one of a plurality of categories corresponding to a different predetermined label with a predetermined priority level; vectorizing, by the encoder, the data to generate a sparse vector xi for its corresponding label; encoding, by the encoder, a plurality of the sparse vectors xi by multiplying a measurement matrix Ai(t) with the sparse vector xi to generate a set of encoded information yi; transmitting, by the encoder to the decoder, the plurality of sets of the encoded information yi in a prioritized order; decoding, by the decoder, the plurality of sets of encoded information yi to determine the plurality of the sparse vectors xi based on determining measurement matrix Ai(t); and uniting the plurality of the sparse vectors xi into a single image frame.

Abstract: A vehicle communication and control system includes a first vehicle in signal communication with a remote computing system and/or a second vehicle. The first vehicle includes a sensor configured to capture a raw image having a first image volume and including at least one target object. An image encoder included in the vehicle converts the raw image into a masked image having a second image volume that is less than the first image volume. A segmentation unit included in the remote computing system and/or the second vehicle determines the at least one target object from the masked image, generates a masked segmented image including a sparse segmentation of the at least one target object, and converts the sparse segmentation of the at least one target object into at least one recovered segmented target object indicative of the at least one target object.

Abstract: A method in a rate adaptive system includes categorizing, by an encoder, a plurality of clusters of data in a segmented image into one of a plurality of categories corresponding to a different predetermined label with a predetermined priority level; vectorizing, by the encoder, the data to generate a sparse vector xi for its corresponding label; encoding, by the encoder, a plurality of the sparse vectors xi by multiplying a measurement matrix Ai(t) with the sparse vector xi to generate a set of encoded information yi; transmitting, by the encoder to the decoder, the plurality of sets of the encoded information yi in a prioritized order; decoding, by the decoder, the plurality of sets of encoded information yi to determine the plurality of the sparse vectors xi based on determining measurement matrix Ai(t); and uniting the plurality of the sparse vectors xi into a single image frame.

Abstract: The present application relates to a method and apparatus for generating a three-dimensional point cloud generation using a polarimetric camera in a drive assistance system equipped vehicle including a camera configured to capture a color image for a field of view and a polarimetric data of the field of view, a processor configured to perform a neural network function in response to the color image and the polarimetric data to generate a depth map of the field of view, and a vehicle controller configured a perform an advanced driving assistance function and to control a vehicle movement in response to the depth map.

Abstract: The present application relates to a method and apparatus for generating a three-dimensional point cloud generation using a polarimetric camera in a drive assistance system equipped vehicle including a camera configured to capture a color image for a field of view and a polarimetric data of the field of view, a processor configured to perform a neural network function in response to the color image and the polarimetric data to generate a depth map of the field of view, and a vehicle controller configured a perform an advanced driving assistance function and to control a vehicle movement in response to the depth map.