Gm Global Technolgoy Operations, Inc.

Sai Vishnu Aluru

Sravan Daruri

Joseph G Machak

Mohannad F Murad

Yun Qian Miao

Steffen P Lindenthal

Brian Yousif-Dickow

Xiaofeng Frank Song

Valor Yaldo

Andrew W Averhart

Jay H Sim

Christopher A Stanek

Mohamed A Naiel

Michael Cervoni

Chandra S Namuduri

Joseph F Szczerba

Wende Zhang

Upali Priyantha Mudalige

Rashmi Prasad

Fred W Huntzicker

Norman Joseph Weigert

Wei Tong

James A Carpenter

Alaa M Khamis

Fahim Javid

Guangyu J Zou

Utkarsh Saini

Timothy D Demetrio

Dhruv Patel

David A Osinski

Justin K Francisco

Abbas Mohammed

Jayasimha V Rao

Dustin Howard Malcom Smith

Taylor A Jakubczak

Ali Atriss

Eyal Lubelski

Logan Elliot Stack

Jonathan Patrick Agnew

Daniel Woodall

Ndikum Atang

Daniel Xie

Syed Mahdi

Joshua Inglese

Aadi Kothari

Michael Dominic Done

A computer-implemented method is executed by data processing hardware of a display calibration system in communication with a camera system of a motor vehicle that has a vehicle display. The method includes computing a first gamma value for a vehicle display based on at least one display specification or a vehicle statistic. Additionally, the method includes receiving a display look-up table, which is modified based on the computed first gamma value to generate a transformation look-up table. Image data from the camera system is received, and the transformation look-up table is applied to the image data to generate transformed image data. Simulated image data is generated based on the transformed image data, and this simulated image data is rendered at a display of the display calibration system. The rendered display corresponds to the vehicle display.

System and method for simulating vehicle display

A self-cleaning sensor system of a motor vehicle includes an object sensor having a lens surface facing a region located external to the motor vehicle. The object sensor generates a signal associated with an image or a video of the region. The system further includes multiple lens treatment devices for applying remedies for removing an obscurity formed on the lens surface. The system further includes a computer having one or more processors and a computer readable medium storing instructions. The processor is programmed to determine a classification of the obscurity, in response to the processor receiving the signal from the object sensor. The processor is further programmed to generate an actuation signal, and the associated lens treatment device applies the remedy, in response to the associated lens treatment device receiving the actuation signal from the processor.

Self-cleaning sensor system of a motor vehicle

Vehicles and related systems and adaptive display adjustment methods include obtaining image data captured using an initial frame rate from an imaging system onboard the vehicle, obtaining current vehicle state information, determining a representative exposure setting for the imaging system based at least in part on the current vehicle state information, determining an estimated illuminance of a surrounding environment of the vehicle based at least in part on the image data and the representative exposure setting and automatically configuring the imaging system for a different, updated frame rate based on the estimated illuminance. Thereafter, the method continues by obtaining subsequent image data captured using the updated frame rate, providing a graphical user interface including a graphical representation of the subsequent image data on a display device associated with the vehicle, and dynamically adjusting a display characteristic after configuring the imaging system for the updated frame rate.

Vehicle systems and methods for environmental camera view display adaptation

Aspects of the present disclosure include methods, apparatuses, and vehicles for performing intrinsic calibration of the cameras in the vehicle. A processor may acquire plural images of a target captured by the camera at different locations. For each image, the processor may tone map the image, binarize the tone-mapped image, define a structuring element based on the digital form of the shape of the target, perform morphology on the image to align and calibrate the structuring elements, filter the target and modify each of the other pixels to black, and compile an output image. Based on the calibration, the principal point values may be shifted to account for discrepancies and store calibrated values in each camera.

Precise intrinsic calibration of vehicle camera

Methods and systems are provided that include obtaining camera images from a camera of a vehicle; obtaining weather data as to a location in which the vehicle is travelling; processing the camera images, via a processor, generating one or more processed frames from the camera images, based on the weather data; and performing a control action for the vehicle, in accordance with instructions provided by the processor, based on the one or more processed frames.

System and method to neutralize the presence of adverse weather artifacts from automotive camera imagery

A method for evaluating edge quality in an image includes receiving an image from a camera of a vehicle, detecting an edge in the image captured by the camera, fitting a polynomial curve to the edge in the image captured by the camera, executing a numerical optimizer to determine a minimum distance from each pixel in the image of the edge to the polynomial curve, determining a modulation transfer function (MTF) value using the minimum distance, determining whether the MTF value is greater than predetermined threshold, and providing an alert in response to determining that the MTF value is not greater than the predetermined threshold.

Control algorithm to precisely evaluate edge quality from imagery

Systems and methods for controlling a vehicle are provided. The systems and methods receive a frame of visible image data from at least one camera of the vehicle and a frame of invisible perception data from a perception sensor. The systems and methods fuse the frame of invisible perception data and the frame of visible image data to provide a fused frame of perception data. Object detection, classification and tracking are performed using a neural network based on the fused frame of perception data to provide object detection data. Steering, propulsion and/or braking of the vehicle are controlled based on the object detection data.

Methods and system for controlling a vehicle using fusion of multi_modality perception data

Systems, methods, and apparatus are provided for real-time adjustment of image quality parameters. The system includes a controller configured to: acquire an image frame, having a fixed-pixel region that defines a region-of-interest, from one or more imaging devices; apply image processing techniques to determine a modified fixed-pixel region that excludes non-relevant object pixels; alter one or more image quality parameters based on statistics of pixels in the modified fixed-pixel region; and provide the altered one or more image quality parameters to the one or more imaging devices for use with subsequent image frames; wherein the one or more imaging devices produce an image that is tuned, based on the altered one or more image quality parameters, to the portions of the image in the region-of-interest that does not include the non-relevant object pixels.

Viewing system to dynamic real time optimize image quality for every customer viewport

Methods and systems are provided for generating image data from a vehicle having a plurality of cameras. A method includes: activating, by the processor, initial video feed from each of the plurality of cameras; determining, by the processor, configuration parameters for each of the plurality of cameras based on the initial video feed; in response to a trigger event, performing frame synchronization of subsequent video feed from each of the plurality of cameras based on the configuration parameters; and generating, by the processor, the image data based on the frame synchronization.

Methods and systems for automated frame synchronization after initial video feed

A dimension calculation system in a host vehicle for dynamically calculating a vehicle dimension using solar shadow information is disclosed. The system is configured to: calculate solar position and an expected vehicle shadow based on geocode location, time and vehicle dynamics; detect an actual vehicle shadow in an image from a vehicle camera; compare the actual vehicle shadow to an expected vehicle shadow; determine a dimension profile and max height point for a vehicle plus vehicle cargo based on a comparison of the actual vehicle shadow to the expected vehicle shadow; calculate a confidence level for the dimension profile and max height point for the vehicle plus cargo; and use the dimension profile and max height point to provide one or more dimension notifications when the confidence level for the dimension profile and max height point for the vehicle plus cargo are above a first threshold level.

System and method for dynamic dimensioning of vehicle and trailer from shadow profiling

An in-vehicle violence detection system includes a speech and non-speech audio recognition module capturing occupant threat words and non-speech audio events. In-vehicle accelerometers generate data analyzed in a shaking movement recognition module. A heart rate and breathing rate detection module measures physiological changes in occupant heart rates and breathing rhythms. An in-vehicle semantic scene recognition module analyzes occupant non-verbal interactions. Occupant threat indicators including an audible threat indicator are generated by the speech and non-speech audio event recognition module. Visual threat indicators are generated by the in-vehicle semantic scene recognition module. Physiological threat indicators are generated by the heart rate and breathing rate detection module. Vibration-based threat indicators are generated by the shaking movement recognition module. The four threat indicators are fused to estimate a threat level, consolidated by incorporating contextual information including a vehicle location and time. Different actions are taken based on the consolidated threat level.

In-vehicle multimodal violence detection for shared vehicles and self-driving shuttles

A method for surveilling with a vehicle includes receiving an area-of-interest data from a vehicle user. The area-of-interest data delineates a virtual fence around the vehicle. The virtual fence is boundary of an area of interest around the vehicle. The vehicle is parked adjacent to an infrastructure. The method further includes receiving sensor data from a sensor of the vehicle that is monitoring the area of interest. Further, the method includes detecting a predetermined activity by a predetermined object of interest within the area of interest based on the sensor data received from the sensor of the vehicle. Also, the method includes notifying the vehicle user of the predetermined activity sensed using the sensor of the vehicle.

Vehicle surveillance system

A clearance risk detection system is provided in a vehicle. The clearance risk detection system is configured to: identify a terrain object in a vehicle travel path; classify the terrain object based on whether the host vehicle can clear the terrain object or cannot clear the terrain object; provide a first indicator that indicates that the host vehicle can clear the terrain object when appropriate; provide a second indicator that indicates that the host vehicle can clear the terrain object with a suggested raising of vehicle ride height when appropriate; automatically raise the vehicle ride height when appropriate; and provide a third indicator that indicates that the host vehicle cannot clear the terrain object even with raising vehicle ride height when appropriate.

System and method for tracking terrain objects

In exemplary embodiments, methods and systems are provided that include or utilize one or more automotive equipped cameras and a processor. The one or more automotive equipped cameras are configured to be onboard a vehicle and to obtain camera images during operation of the vehicle, the camera images including a view of one or more wheels of the vehicle. The processor is coupled to the one or more cameras, and is configured to at least facilitate: processing the camera images; and determining one or more states of the one or more wheels, including an alignment thereof, a health thereof, or both, based on the processing of the camera images.

Method to monitor wheel health and alignment using camera system for proactive vehicle maintenance

Methods and systems are provided for generating a virtual view of a scene associated with a vehicle. In one embodiment, a method includes: obtaining image data including a plurality of images captured by a plurality of cameras of the vehicle; obtaining steering angle data captured by a sensor of the vehicle; detecting, by a processor, a shadow in at least one image of the plurality of images; determining, by the processor, auto-white balance data for each image of the plurality of images; selectively combining, by the processor, the auto-white balance data of the images based on the detected shadow, and the steering angle data; and generating, by the processor, output image data based on the combined auto-white balance data and the image data.

Methods and systems for color harmonization in surround view systems

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Commerce, MI, United States of America

Sai Vishnu Aluru