Waymo LLC

Intersil Americas Inc.

Google Inc.

Lytro, Inc.

Carl Warren Craddock

Vlad Constantin Cardei

Lucian Ion

Andreas Wendel

Ryan M Geiss

Colvin Pitts

Chia-Kai Liang

David W Ritter

Chen Wu

Kurt Akeley

Timothy James Knight

Ajay Chandra Venkata Gummalla

Zhinan Xu

Pieter Kapsenberg

Xiaoying He

Philip Golden

Brendan Elwood Bevensee

Brendan Bevensee

Kevin Brehmer

Kurt Barton Akeley

Yuriy Aleksandrovich Romanenko

A system is provided that includes an image sensor coupled to a vehicle, and control circuitry configured to perform operations including receiving, from the image sensor, an input stream comprising high dynamic range (HDR) image data associated with an environment of the vehicle, and processing the input stream at the vehicle by applying a global tone mapping, followed by offline image processing that can include applying a local tone mapping to the globally tone mapped images of the same input stream.

Systems and methods for a tone mapper solution for an autonomous driving system

The disclosure relates to assessing operation of a camera. In one instance, a volume of space corresponding to a first vehicle in an environment of a second vehicle may be identified using sensor data generated by a LIDAR system of the second vehicle. An image captured by a camera of the second vehicle may be identified. The camera may have an overlapping field of view of the LIDAR system at a time when the sensor data was generated. An area of the image corresponding to the volume of space may be identified and processed in order to identify a vehicle light. The operation of the camera may be assessed based on the processing.

Camera assessment techniques for autonomous vehicles

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

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

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

The disclosure relates to assessing operation of two or more cameras. These cameras may be a group of cameras of a perception system of a vehicle having an autonomous driving mode. A first image captured by a first camera and a second image captured by a second camera may be received. A first feature vector for the first image and a second feature vector for the second image may be generated. A similarity score may be determined using the first feature vector and the second feature vector. This similarity score may be used to assess the operation of the two cameras and an appropriate action may be taken.

RAW images and/or light field images may be compressed through the use of specialized techniques. The color depth of a light field image may be reduced through the use of a bit reduction algorithm such as a K-means algorithm. The image may then be retiled to group pixels of similar intensities and/or colors. The retiled image may be padded with extra pixel rows and/or pixel columns as needed, and compressed through the use of an image compression algorithm. The compressed image may be assembled with metadata pertinent to the manner in which compression was done to form a compressed image file. The compressed image file may be decompressed by following the compression method in reverse.

Compression of light field images

A system and method that compensates for the effects of ambient light in a time of flight (TOF) sensor front end is provided. Moreover, a direct current (DC) correction loop is utilized at the front end, which removes a DC component from a current generated by the TOF sensor and accordingly prevents saturating the front end. The DC correction loop attenuates the DC component without adding significant thermal noise at a modulation frequency and provides a corrected signal to the front end circuitry. The corrected signal is processed and utilized to detect a position of an object within the optical field of the sensor.

Direct current (DC) correction circuit for a time of flight (TOF) photodiode front end

A system and method for automatically calibrating a Time-of-Flight (TOF) transceiver system for proximity/motion detection, is provided. Moreover, the system comprises a component that senses a signal (e.g., current or voltage) at an light emitting diode (LED), an attenuator, a signal injector at a sensor and a switching circuit that toggles between a normal mode (e.g., when signal from the sensor is input to the sensor front end) and a calibration mode (e.g., when signal from the attenuator is input to the sensor front end). During the calibration mode, the sensor front end identifies the phase delay error within the signal path, including board and/or package parasitic, and accounts for the phase delay error during proximity/motion detection in the normal mode.

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San Francisco, CA, United States of America

Carl Warren Craddock