Abstract: An apparatus includes an image sensor having a plurality of pixels that form regions of interest (ROIs), analog-to-digital converter (ADC) banks, and multiplexers. Each respective multiplexer is electrically connected to (i) a corresponding ADC bank and (ii) a corresponding subset of the ROIs. The apparatus also includes control circuitry configured to obtain a full-resolution image of an environment by electrically connecting, by way of the multiplexers, each respective ADC bank to the associated respective ROI. The control circuitry is also configured to select a particular ROI based on the full-resolution image and obtain a plurality of ROI images of the particular ROI by (i) electrically connecting, to the particular ROI, a first ADC bank associated with the particular ROI and a second ADC bank associated with another ROI and (ii) digitizing pixels of the particular ROI by way of parallel operation of the first and second ADC banks.

Abstract: A system includes an image sensor having a plurality of pixels that form a plurality of regions of interest (ROIs), image processing resources, and a scheduler configured to perform operations including determining a priority level for a particular ROI of the plurality of ROIs based on a feature detected by one or more image processing resources of the image processing resources within initial image data associated with the particular ROI. The operations also include selecting, based on the feature detected within the initial image data, a particular image processing resource of the image processing resources by which subsequent image data generated by the particular ROI is to be processed. The operations further include inserting, based on the priority level, the subsequent image data into a processing queue of the particular image processing resource to schedule the subsequent image data for processing by the particular image processing resource.

Abstract: A method includes obtaining multiple images captured by pixel sensors of an image sensor, analyzing, using neural network circuitry integrated in the image sensor, the multiple images for object detection, generating, for each of the multiple images using the neural network circuitry integrated in the image sensor, neural network output data related to results of the analysis of the multiple images for object detection, and transmitting, from the image sensor, the neural network output data for each of the multiple images and image data for a subset of the multiple images instead of image data of each of the multiple images.

Abstract: Disclosed are devices and methods that may be used for the calibration of sensors of a vehicle. A calibration system disclosed herein includes a trigger device configured to detect a first sensing event. The calibration system further includes a plurality of sensor targets. Additionally, the calibration system includes a processor configured to reveal the plurality of sensor targets within a given region in response to the first sensing event. The calibration system may be configured to detect light from a LIDAR striking a light sensors. In response to detecting the light from the LIDAR, a plurality of lights, both visible and infrared, may be illuminated to correspond with a position and timing of the LIDAR pulse.

Abstract: A method includes obtaining multiple images captured by pixel sensors of an image sensor, analyzing, using neural network circuitry integrated in the image sensor, the multiple images for object detection, generating, for each of the multiple images using the neural network circuitry integrated in the image sensor, neural network output data related to results of the analysis of the multiple images for object detection, and transmitting, from the image sensor, the neural network output data for each of the multiple images and image data for a subset of the multiple images instead of image data of each of the multiple images.

Abstract: A image sensor includes a first integrated circuit layer including pixel sensors that are grouped based on position into pixel sensor groups, a second integrated circuit layer in electrical communication with the first integrated circuit layer, the second integrated circuit layer including image processing circuitry groups that are configured to each receive pixel information from a corresponding pixel sensor group, the image processing circuitry groups further configured to perform image processing operations on the pixel information to provide processed pixel information during operation of the image sensor, a third integrated circuit layer in electrical communication with the second integrated circuit layer, and the third integrated circuit layer including neural network circuitry groups that are configured to each receive the processed pixel information from a corresponding image processing circuitry group and perform analysis for object detection on the processed pixel information during operation of the

Abstract: A system may include a first sensor of a first type and a second sensor of a second different type and having a detector. A field of view of the second sensor may be formed by a plurality of regions of interest (ROIs) defined by the detector. Control circuitry of the system may be configured to perform operations including obtaining, from the first sensor, first sensor data representing an environment, and determining, based on the first sensor data, information associated with a feature of interest within the environment. The operations may also include determining, based on the information, a particular ROI that corresponds to an expected position of the feature at a later time, obtaining a plurality of ROI sensor data from the particular ROI instead of obtaining full-resolution sensor data, and analyzing the plurality of ROI sensor data to determine one or more attributes of the feature.

Abstract: Example embodiments relate to microlensing for real-time sensing of stray light. An example device includes an image sensor that includes a plurality of light-sensitive pixels. The device also includes a first lens positioned over a first subset of light-sensitive pixels selected from the plurality of light-sensitive pixels. Further, the device includes a controller. The controller is configured to determine a first angle of incidence of a first light signal detected by the first subset of light-sensitive pixels. The controller is also configured to, based on the first determined angle of incidence, determine an amount of stray light incident on the image sensor.

Abstract: Systems and methods for night vision combining sensor image types. Some implementations may include obtaining a long wave infrared image from a long wave infrared sensor; detecting an object in the long wave infrared image; identifying a region of interest associated with the object; adjusting a control parameter of a near infrared sensor based on data associated with the region of interest; obtaining a near infrared image captured using the adjusted control parameter of the near infrared sensor; and determining a classification of the object based on data of the near infrared image associated with the region of interest.

Abstract: A image sensor includes a first integrated circuit layer including pixel sensors that are grouped based on position into pixel sensor groups, a second integrated circuit layer in electrical communication with the first integrated circuit layer, the second integrated circuit layer including image processing circuitry groups that are configured to each receive pixel information from a corresponding pixel sensor group, the image processing circuitry groups further configured to perform image processing operations on the pixel information to provide processed pixel information during operation of the image sensor, a third integrated circuit layer in electrical communication with the second integrated circuit layer, and the third integrated circuit layer including neural network circuitry groups that are configured to each receive the processed pixel information from a corresponding image processing circuitry group and perform analysis for object detection on the processed pixel information during operation of the

Abstract: Systems and methods for night vision combining sensor image types. Some implementations may include obtaining a long wave infrared image from a long wave infrared sensor; detecting an object in the long wave infrared image; identifying a region of interest associated with the object; adjusting a control parameter of a near infrared sensor based on data associated with the region of interest; obtaining a near infrared image captured using the adjusted control parameter of the near infrared sensor; and determining a classification of the object based on data of the near infrared image associated with the region of interest.

Abstract: Disclosed are devices and methods that may be used for the calibration of sensors of a vehicle. A calibration system disclosed herein includes a trigger device configured to detect a first sensing event. The calibration system further includes a plurality of sensor targets. Additionally, the calibration system includes a processor configured to reveal the plurality of sensor targets within a given region in response to the first sensing event. The calibration system may be configured to detect light from a LIDAR striking a light sensors. In response to detecting the light from the LIDAR, a plurality of lights, both visible and infrared, may be illuminated to correspond with a position and timing of the LIDAR pulse.

Abstract: A image sensor includes a first integrated circuit layer including pixel sensors that are grouped based on position into pixel sensor groups, a second integrated circuit layer in electrical communication with the first integrated circuit layer, the second integrated circuit layer including image processing circuitry groups that are configured to each receive pixel information from a corresponding pixel sensor group, the image processing circuitry groups further configured to perform image processing operations on the pixel information to provide processed pixel information during operation of the image sensor, a third integrated circuit layer in electrical communication with the second integrated circuit layer, and the third integrated circuit layer including neural network circuitry groups that are configured to each receive the processed pixel information from a corresponding image processing circuitry group and perform analysis for object detection on the processed pixel information during operation of the

Abstract: A method includes obtaining multiple images captured by pixel sensors of an image sensor, analyzing, using neural network circuitry integrated in the image sensor, the multiple images for object detection, generating, for each of the multiple images using the neural network circuitry integrated in the image sensor, neural network output data related to results of the analysis of the multiple images for object detection, and transmitting, from the image sensor, the neural network output data for each of the multiple images and image data for a subset of the multiple images instead of image data of each of the multiple images.

Abstract: A method includes determining temperature values for roadway areas ahead of a vehicle, determining lubricant state values for the roadway areas, and determining lubricant thickness values for the roadway areas. The method also includes determining a tire-road friction estimate for each of the roadway areas using the temperature values, the lubricant state values, and the lubricant thickness values, and defining a friction map that relates the tire-road friction estimates to the roadway areas. The method also includes determining a motion plan based at least in part on the friction map, and controlling the vehicle based on the motion plan.

Abstract: An object detection system includes an infrared light source and an imaging system that generates an image from a portion of the infrared spectrum characterized by full absorption of solar radiation. A control system detects an object using the image, determines a command based on a location of the object, and sends a command to one or more vehicle systems. Another object detection system includes an imaging system that generates a first image based on a visible spectrum and a second image based an infrared spectrum. A control system receives a disparity indication associated with object detection and sends a command to one or more vehicle systems to implement a disparity response based on the disparity indication. The disparity indication includes information that an object is not detected within the first image and that the object is detected within the second image.

Abstract: A machine vision system having a first camera configured to be coupled to a vehicle. The camera includes an optical stack having a color filter array with a plurality of sections. Each section includes a first white filter portion, a yellow filter portion, a magenta filter portion, and a second white filter portion.

Abstract: An imaging device can include an image sensor, a control unit coupled to the image sensor, and a light blocking element coupled to the control unit. The control unit can be configured to adjust the light blocking element in response to image information received from the image sensor. The light blocking element can be configured to regulate light received at the image sensor.

Abstract: Systems and methods for night vision combining sensor image types. Some implementations may include obtaining a long wave infrared image from a long wave infrared sensor; detecting an object in the long wave infrared image; identifying a region of interest associated with the object; adjusting a control parameter of a near infrared sensor based on data associated with the region of interest; obtaining a near infrared image captured using the adjusted control parameter of the near infrared sensor; and determining a classification of the object based on data of the near infrared image associated with the region of interest.

Abstract: A machine vision system having a first camera configured to be coupled to a vehicle, The camera includes an optical stack having a color filter array with a plurality of sections. Each section includes a first white filter portion, a yellow filter portion, a magenta filter portion, and a second white filter portion.