Waymo LLC

Google Inc.

Vlad Constantin Cardei

Lucian Ion

Nirav Dharia

Carl Warren Craddock

Ralph Hamilton Shepard

Giulia Guidi

Matthew Rinehart

Boyd Fowler

Edward Y Chang

Katrina Passarella

Andrey Yatsunenko

Methods, systems, and apparatus, for an autonomous vehicle navigation maintenance system. In one aspect, an autonomous vehicle monitoring system includes a mounting surface located on an autonomous vehicle, and a thermal imaging system affixed to the mounting surface, the thermal imaging system including a thermal imaging camera, a replaceable filter, and a filter fixture configured to affix the replaceable filter to the thermal imaging camera and aligned with an optical axis of the thermal imaging camera, and where maintenance of the replaceable filter does not include re-calibrating the thermal imaging camera.

Autonomous vehicle having a thermal infrared camera with replaceable filter

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.

High bandwidth camera data transmission

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.

Smart sensor scheduler

The technology relates to determining whether a camera is occluded. For instance, an image may be captured using a camera having red, green, and blue pixels each including a photosensor. Output values for the photosensors of each of the red pixels, green pixels, and blue pixels may be determined for the images. The output values of the green pixels may be compared to one or more of the output values of the red pixels or the output values of the blue pixels. That the camera is occluded is determined based on the comparison.

Low-light camera occlusion detection

Systems, apparatus, and methods are presented for event detection. One method may include receiving event data from an event capture device while the event capture device is in a stationary state. The event capture device may be coupled to a vehicle. The method may also include generating a command and sending the command to the event capture device. The command is configured to cause the event capture device to change from the stationary state to a non-stationary state.

Systems, methods, and apparatus for event detection

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 image sensor.

Image sensor architecture

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.

Smart sensor with region of interest capabilities

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.

Sensor region of interest selection based on multisensor data

Systems, apparatus, and methods are presented for rendering color images. One method may include receiving first color values of a first image from a first image capture device. The first color values may represent colors in a first color space. The method also may include applying first color transformation information to the first color values to generate first transformed color values of the first image in a particular color space and applying desaturation information to the first transformed color values to generate first desaturated color values of the first image. Further, the method may include providing the first desaturated color values of the first image for rendering on a display device.

Systems, methods, and apparatus for correcting desaturation of images with transformed color values by appling a matrix

An example method includes using a plurality of switches corresponding to a plurality of capacitors to select a first set of capacitors for charging at a first time. Charging the first set of capacitors corresponds to sampling from a first set of adjacent light detectors. The method includes using the plurality of switches to select a second set of capacitors from the plurality of capacitors for discharging at a second time. The method includes using a sampling switch to sample an output of the second set of capacitors as they discharge. The output of the second set of capacitors corresponds to the first set of adjacent light detectors. The method includes determining, based on sampling the output of the second set of capacitors, a collective intensity of light received by the first set of adjacent light detectors.

Systems and methods for binning light detectors

An example method includes capturing, by an image capture device, a first image having a plurality of pixels. Each pixel includes a plurality of channels, and the first image is captured in accordance with first exposure parameters. The method includes determining, by a controller of the image capture device, average pixel intensities for each of the plurality of channels. The method includes determining, by the controller, a weighted average of pixel intensities using the average pixel intensities. The method includes setting, by the controller, a gain that is proportional to a ratio of a desired average pixel intensity relative to the weighted average of pixel intensities. The method includes setting, by the controller, second exposure parameters for a second image based on the gain. The method includes capturing, by the image capture device, the second image in accordance with the second exposure parameters.

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Redwood City, CA, United States of America

Vlad Constantin Cardei