Abstract: Systems and methods for providing rear voice recognition (VR) conflict monitoring are provided. The method may comprise receiving one or more VR inputs and, using a computing device, determining whether the one or more VR inputs trigger one or more driver actions or passenger actions, determining whether a driver action is related to a number of one or more passenger actions and is part of a tracked action list, determining whether the driver action contradicts the one or more passenger actions, for each passenger action, increasing a positive index when the passenger action does not contradict the driver action and increasing a negative index when the passenger action contradicts the driver action, calculating a trigger index by subtracting the negative index from the positive index, and prompting a driver to disable a portion of a VR system when the trigger index is less than a threshold.

Abstract: Systems and methods for providing rear voice recognition (VR) conflict monitoring are provided. The method may comprise receiving one or more VR inputs and, using a computing device, determining whether the one or more VR inputs trigger one or more driver actions or passenger actions, determining whether a driver action is related to a number of one or more passenger actions and is part of a tracked action list, determining whether the driver action contradicts the one or more passenger actions, for each passenger action, increasing a positive index when the passenger action does not contradict the driver action and increasing a negative index when the passenger action contradicts the driver action, calculating a trigger index by subtracting the negative index from the positive index, and prompting a driver to disable a portion of a VR system when the trigger index is less than a threshold.

Abstract: Voice recognition (VR) systems and methods for performing VR are provided. The VR system may comprise one or more microphones, one or more speakers, and a computing device, comprising a processor, a memory, and a plurality of buttons. Each button may be associated with a VR functionality, of a plurality of VR functionalities. Each VR functionality may have one or more grammar domains associated with it. The memory may be configured to store instructions that, when executed by the processor, are configured to cause the processor to receive an input from one of the plurality of buttons, specifying a VR functionality, disable one or more grammar domains not associated with the specified VR functionality, receive an audio input, via the one or more microphones, and analyze the audio input absent the disabled one or more grammar domains to determine one or more VR commands from the audio input.

Abstract: Systems and methods for controlling CAN communication in a vehicle are provided. The method may comprise storing CAN message information in the plurality of CAN databases such that each CAN database stores a unique configuration of the CAN message information, determining a system mode of operation comprising determining one or more LSBs of a DLC and comparing the one or more LSBs of the DLC against a database to determine the system mode of operation, generating an RTR message comprising determining one or more MSBs of the DLC and adding the one or more MSBs of the DLC to an end of an identifier, generating an RTR request value comprising the identifier and the one or more MSBs of the DLC, communicating the RTR message, to the plurality of ECUs, interpreting the RTR request value to determine the requested answer value, and communicating the requested answer value.

Abstract: Systems and methods for performing enhanced self-park maneuvers are provided. The system may comprise one or more audio sensors coupled to a vehicle configured to generate audio sensor data, one or more visual sensors coupled to the vehicle configured to generate visual sensor data, and a computing device, comprising a processor and a memory. The memory may comprise instructions that, when executed by the processor, are configured to cause the processor to cause the vehicle to perform a remote smart parking assist (RSPA) function to self-park the vehicle, receive the audio sensor data and the visual sensor data, calculate a risk evaluation based on the audio sensor data and the visual sensor data, using a neural network, generate a confidence score based on the risk evaluation, and determine one or more suitable actions for the vehicle to take, based on the confidence score.

Abstract: Systems and methods for controlling CAN communication in a vehicle are provided. The method may comprise storing CAN message information in the plurality of CAN databases such that each CAN database stores a unique configuration of the CAN message information, determining a system mode of operation comprising determining one or more LSBs of a DLC and comparing the one or more LSBs of the DLC against a database to determine the system mode of operation, generating an RTR message comprising determining one or more MSBs of the DLC and adding the one or more MSBs of the DLC to an end of an identifier, generating an RTR request value comprising the identifier and the one or more MSBs of the DLC, communicating the RTR message, to the plurality of ECUs, interpreting the RTR request value to determine the requested answer value, and communicating the requested answer value.

Abstract: An electronic device and method for content-aware image encoding using a machine learning (ML) model are provided. The electronic device receives at least one foreground region and at least one background region from a first image frame. The electronic device determines a set of first macroblocks associated with the detected at least one foreground region and a set of second macroblocks associated with the detected at least one background region, determines a bit allocation control parameter associated with the determined set of second macroblocks, updates the determined bit allocation control parameter based on an application of a first trained ML model, and encodes the first image frame based on the updated bit allocation control parameter to obtain a second image frame so that a first image quality index associated with the first image frame matches a second image quality index associated with the second image frame within a threshold range.

Abstract: An electronic device and method for content-aware image encoding using a machine learning (ML) model are provided. The electronic device receives at least one foreground region and at least one background region from a first image frame. The electronic device determines a set of first macroblocks associated with the detected at least one foreground region and a set of second macroblocks associated with the detected at least one background region, determines a bit allocation control parameter associated with the determined set of second macroblocks, updates the determined bit allocation control parameter based on an application of a first trained ML model, and encodes the first image frame based on the updated bit allocation control parameter to obtain a second image frame so that a first image quality index associated with the first image frame matches a second image quality index associated with the second image frame within a threshold range.

Abstract: Systems and methods are disclosed for implementing enhanced security measures for working against unwanted intrusion from outside attackers into a vehicle's controller area network (CAN) bus. The enhanced security measures utilize existing data frames that are transmitted within the CAN bus to encrypt message identifications (IDs) for certain messages that are related to important features of a vehicle.

Abstract: A method for controlling controller area network (CAN) communication in a vehicle including a plurality of electronic control units (ECUs) and a plurality of CAN databases accessible by the plurality of ECUs can include: storing CAN message information in the plurality of CAN databases such that each CAN database stores a unique configuration of the CAN message information; establishing a plurality of periodic intervals; and when a subsequent interval among the plurality of periodic intervals begins: receiving a plurality of measurement values deriving from a plurality of sensors equipped in the vehicle, calculating a database reference number based upon the plurality of measurement values, the database reference number newly identifying a particular CAN database among the plurality of CAN databases, and performing CAN communication, by each ECU, based upon the uniquely configured CAN message information stored in the newly identified CAN database.

Abstract: Systems and methods are disclosed for implementing enhanced security measures that include utilizing a backup database included on node devices connected to a CAN bus, so that certain message identifiers are updated according to a matching table stored on the backup database. By updating the message identifiers, outside attackers will not be privy to the new message identifier assigned to the messages and will no longer target such messages.

Abstract: Systems and methods are disclosed for implementing enhanced security measures for working against unwanted intrusion from outside attackers into a vehicle's controller area network (CAN) bus. The enhanced security measures utilize existing data frames that are transmitted within the CAN bus to encrypt message identifications (IDs) for certain messages that are related to important features of a vehicle.

Abstract: Systems and methods are disclosed for implementing enhanced security measures that include utilizing a backup database included on node devices connected to a CAN bus, so that certain message identifiers are updated according to a matching table stored on the backup database. By updating the message identifiers, outside attackers will not be privy to the new message identifier assigned to the messages and will no longer target such messages.

Abstract: A media processing apparatus and method for frame rate control based on rendered objects. The media processing apparatus receives a first plurality of image frames which may include a first plurality of objects from a first image capturing device. The media processing apparatus receives a first user input corresponding to a first object from a first media rendering device. The media processing apparatus determines a first speed of movement of the first object based on an analysis of a first set of consecutive image frames from the first plurality of image frames and calculates a first frame rate based on the determined first speed of movement of the first object. The first image capturing device captures a second plurality of image frames at the first frame rate. The media processing apparatus transmits the captured second plurality of image frames to the first media rendering device.

Abstract: A media processing apparatus and method for frame rate control based on rendered objects. The media processing apparatus receives a first plurality of image frames which may include a first plurality of objects from a first image capturing device. The media processing apparatus receives a first user input corresponding to a first object from a first media rendering device. The media processing apparatus determines a first speed of movement of the first object based on an analysis of a first set of consecutive image frames from the first plurality of image frames and calculates a first frame rate based on the determined first speed of movement of the first object. The first image capturing device captures a second plurality of image frames at the first frame rate. The media processing apparatus transmits the captured second plurality of image frames to the first media rendering device.

Abstract: An image processing device is disclosed. The image processing device controls an image capture device to capture at least first image that comprises one or more objects. The image processing device identifies at least a first object in the first image. The image processing device determines a first blur value of identified first object and determines the identified first object as a blur object based on the first blur value. The image processing device adjusts a focal point of the image capture device to focus on the blurred first object. The image processing device controls the image capture device to capture a second image of the first object based on adjusted focal point. The image processing device replaces the first object in first image with the first object in the second image to generate an output image and further controls the display screen to display well-focused output image.

Abstract: An image processing device is disclosed. The image processing device controls an image capture device to capture at least first image that comprises one or more objects. The image processing device identifies at least a first object in the first image. The image processing device determines a first blur value of identified first object and determines the identified first object as a blur object based on the first blur value. The image processing device adjusts a focal point of the image capture device to focus on the blurred first object. The image processing device controls the image capture device to capture a second image of the first object based on adjusted focal point. The image processing device replaces the first object in first image with the first object in the second image to generate an output image and further controls the display screen to display well-focused output image.

Abstract: A method for controlling controller area network (CAN) communication in a vehicle including a plurality of electronic control units (ECUs) and a plurality of CAN databases accessible by the plurality of ECUs can include: storing CAN message information in the plurality of CAN databases such that each CAN database stores a unique configuration of the CAN message information; establishing a plurality of periodic intervals; and when a subsequent interval among the plurality of periodic intervals begins: receiving a plurality of measurement values deriving from a plurality of sensors equipped in the vehicle, calculating a database reference number based upon the plurality of measurement values, the database reference number newly identifying a particular CAN database among the plurality of CAN databases, and performing CAN communication, by each ECU, based upon the uniquely configured CAN message information stored in the newly identified CAN database.