Patent Issued for Apparatuses, systems and methods for integrating vehicle operator gesture detection within geographic maps (USPTO 11321951): State Farm Mutual Automobile Insurance Company

2022 MAY 19 (NewsRx) -- By a News Reporter-Staff News Editor at Insurance Daily News -- According to news reporting originating from Alexandria, Virginia, by NewsRx journalists, a patent by the inventors Chan, Aaron Scott (Bloomington, IL, US), Sanchez, Kenneth J. (San Francisco, CA, US), filed on January 19, 2018, was published online on May 3, 2022.

The assignee for this patent, patent number 11321951, is State Farm Mutual Automobile Insurance Company (Bloomington, Illinois, United States).

Reporters obtained the following quote from the background information supplied by the inventors: “Vehicles are being provided with more complex systems. For example, vehicles commonly include a plethora of entertainment systems, such as stereos, USB interfaces for mobile telephones, video players, etc. Vehicles often have a host of other operator interfaces, such as emergency calling systems, vehicle navigation systems, heating and air conditioning systems, interior and exterior lighting controls, air bags, seatbelts, etc.

“Vehicle operating environments are becoming more complex as well. For example, some roadways include U-turn lanes, round-a-bouts, no-left turn, multiple lanes one way in the morning and the other way in the afternoon, etc. Increases in traffic are also contributing to increased complexity.

“These additional complexities contribute to increases in driver risk. What is needed are methods and systems for generating data representative of vehicle in-cabin insurance risk evaluations based on data representative of skeletal diagrams of a driver that are indicative of degrees of driver risk.”

In addition to obtaining background information on this patent, NewsRx editors also obtained the inventors’ summary information for this patent: “A device for determining vehicle operator gestures and incorporating the vehicle operator gestures within geographic maps may include a previously classified image data receiving module stored on a memory that, when executed by a processor, causes the processor to receive previously classified image data from at least one previously classified image database. The previously classified image data may be representative of previously classified vehicle occupant gestures. The device may also include a current image data receiving module stored on a memory that, when executed by a processor, causes the processor to receive current image data from at least one vehicle interior sensor. The current image data may be representative of current vehicle occupant gestures. The device may further include a current image data classification module stored on a memory that, when executed by a processor, causes the processor to classify the current image data by comparing the current image data to the previously classified image data. The currently classified image data may be representative of at least one current vehicle occupant gesture. The device may yet further include a currently classified image data transmission module stored on a memory that, when executed by a processor, causes the processor to transmit the currently classified image data to at least one geographic map application programming interface.

“In another embodiment, a computer-implemented method for determining vehicle occupant gestures and for incorporating the vehicle occupant gestures within geographic maps may include receiving, at a processor of a computing device, previously classified image data from at least one previously classified image database in response to the processor executing a previously classified image data receiving module. The previously classified image data is representative of previously classified vehicle occupant gestures. The method may also include receiving, at a processor of a computing device, current image data from at least one vehicle interior sensor a current image data receiving module, in response to the processor executing a current image data receiving module. The current image data may be representative of at least one current vehicle occupant gesture. The method may further include classifying, using a processor of a computing device, at least one gesture associated with a vehicle occupant, based on a comparison of the current image data with the previously classified image data, in response to the processor executing a current image data classification module. The method may yet further include transmitting, using a processor of a computing device, the currently classified image data to at least one geographic map application programming interface, in response to the processor executing a currently classified image data transmission module.

“In a further embodiment, a non-transitory computer-readable medium storing computer-readable instructions that, when executed by a processor, may cause the processor to determine vehicle occupant gestures and incorporate the vehicle occupant gestures within geographic maps. The non-transitory computer-readable medium may include a previously classified image data receiving module that, when executed by a processor, may cause the processor to receive previously classified image data from at least one previously classified image database. The previously classified image data may be representative of previously classified vehicle occupant gestures. The non-transitory computer-readable medium may also include a current image data receiving module that, when executed by a processor, may cause the processor to receive current image data from at least one vehicle interior sensor. The current image data may be representative of current vehicle occupant gestures. The non-transitory computer-readable medium may further include a current image data classification module that, when executed by a processor, may cause the processor to classify the current image data by comparing the current image data to the previously classified image data. The currently classified image data may be representative of at least one current vehicle occupant gesture. The non-transitory computer-readable medium may yet further include a currently classified image data transmission module that, when executed by a processor, may cause the processor to transmit the currently classified image data to at least geographic map application programming interface.”

The claims supplied by the inventors are:

“1. A device for determining patterns in vehicle occupant gestures and correlating the pattern of vehicle occupant gestures with a respective hazard type, and providing data that is representative of the hazard type to at least one geographic map application programming interface to generate a geographic map display that incorporates the hazard type, the device comprising: one or more processors and one or more memories; a previously classified image data receiving module stored on the one or more memories that, when executed by the one or more processors, causes the processor to receive previously classified image data from at least one previously classified image database, wherein the previously classified image data is representative of a pattern of previously classified vehicle occupant gestures that are correlated with a respective hazard type, and wherein the pattern of previously classified vehicle occupant gestures includes at least one gesture that is based on an orientation of a head of at least one vehicle occupant toward a particular side; a current image data receiving module stored on the one or more memories that, when executed by the one or more processors, causes the processor to receive current image data from at least one vehicle interior sensor, wherein the current image data is representative of a pattern of current vehicle occupant gestures; a current image data classification module stored on the one or more memories that, when executed by the one or more processors, causes the processor to classify the current image data, based on the pattern in vehicle occupant gestures, by comparing the current image data to the previously classified image data, wherein the currently classified image data is representative of at least one hazard type selected from: an accident, a traffic jam, a road closure, or road construction; a currently classified image data transmission module stored on the one or more memories that, when executed by the one or more processors, causes the processor to transmit the currently classified image data to at least one individual other than a vehicle operator; a geographic map application programming interface stored on the one or more memories that, when executed by the one or more processors, causes the processor to incorporate data representative of at least one hazard type and a respective hazard location; and a geographic map display generation module stored on the one or more memories that, when executed by the one or more processors, causes the processor to generate a real-time geographic map display incorporating the at least one hazard type at a respective geographic location within the geographic map display.

“2. The device as in claim 1, wherein the at least one vehicle interior sensor is selected from: at least one digital image sensor, at least one ultra-sonic sensor, at least one radar-sensor, at least one infrared light sensor, or at least one laser light sensor.

“3. The device as in claim 1, further comprising: a pattern recognition algorithm stored on the one or more memories that, when executed by the one or more processors, causes the processor to categorize previously-uncategorized behaviors based on comparing the current image data to the previously classified image data, wherein the currently classified image data is representative of the categorized previously-uncategorized behaviors.

“4. The device as in claim 1, wherein the current image data is representative of a three-dimensional representation of at least one occupant within the vehicle interior.

“5. The device as in claim 1, wherein the previously classified image data is representative of a three-dimensional representation of at least one occupant within the vehicle interior.

“6. The device as in claim 1, wherein the current image data includes images and/or extracted image features that are representative of a vehicle occupant using a cellular telephone, a vehicle occupant looking out a vehicle side window, a vehicle occupant adjusting a vehicle radio, a vehicle occupant adjusting a vehicle heating, ventilation and air conditioning system, two vehicle occupants talking with one-another, a vehicle occupant reading a book or magazine, a vehicle occupant putting on makeup, a vehicle occupant looking at themselves in a mirror, a vehicle occupant eating, or a vehicle occupant drinking.

“7. The device as in claim 1, wherein the previously classified image data includes images and/or extracted image features that have previously been classified as being representative of a vehicle occupant using a mobile device, a vehicle occupant looking out a vehicle side window, a vehicle occupant adjusting a vehicle radio, a vehicle occupant adjusting a vehicle heating, ventilation and air conditioning system, two vehicle occupants talking with one-another, a vehicle occupant reading a book or magazine, a vehicle occupant putting on makeup, a vehicle occupant looking at themselves in a mirror, a vehicle occupant eating, or a vehicle occupant drinking.

“8. A computer-implemented method for determining patterns in vehicle occupant gestures and for correlating the pattern of vehicle occupant gestures with a respective hazard type, and to include the hazard type within a geographic map display, the method comprising: receiving, at a processor of a computing device, previously classified image data from at least one previously classified image database in response to the processor executing a previously classified image data receiving module, wherein the previously classified image data is representative of patterns of previously classified vehicle occupant gestures; receiving, at the processor of the computing device, current image data from at least one vehicle interior sensor in response to the processor executing a current image data receiving module, wherein the current image data is representative of at least one pattern of current vehicle occupant gestures; classifying, using the processor of the computing device, at least one pattern of gestures associated with a vehicle occupant, based on a comparison of the current image data with the previously classified image data, in response to the processor executing a current image data classification module, wherein the at least one pattern of gestures is representative of a hazard type selected from: an accident, a traffic jam, a road closure, or road construction, and wherein the at least one pattern of gestures includes at least one gesture that is based on an orientation of a head of at least one vehicle occupant toward a particular side; transmitting, using the processor of the computing device, the currently classified image data to at least one geographic map application programming interface, in response to the processor executing a currently classified image data transmission module; a geographic map application programming interface that, when executed by a processor, causes the processor to incorporate data representative of at least one hazard type and respective hazard location into a geographic map; and generating, using the processor of the computing device, a real-time geographic map display incorporating the hazard type at the hazard location in response to the processor executing a geographic map display generation module.

“9. The method as in claim 8, wherein the at least one vehicle interior sensor is selected from: at least one digital image sensor, at least one ultra-sonic sensor, at least one radar-sensor, at least one infrared light sensor, or at least one laser light sensor.

“10. The method as in claim 8, wherein the current image data is representative of a three-dimensional representation of at least one occupant within the vehicle interior.

“11. The method as in claim 8, wherein at least one vehicle operator gesture is determined using a probability function.

“12. The method as in claim 8, wherein the previously classified image data is representative of a three-dimensional representation of at least one occupant within the vehicle interior.

“13. The method as in claim 8, wherein the current image data includes images and/or extracted image features that are representative of vehicle occupant locations/orientations, cellular telephone locations/orientations, vehicle occupant eye locations/orientations, vehicle occupant head location/orientation, vehicle occupant hand location/orientation, a vehicle occupant torso location/orientation, a seat belt location, or a vehicle seat location/orientation.

“14. The method as in claim 8, wherein the previously classified image data includes images and/or extracted image features that have previously been classified as being representative of known vehicle occupant locations/orientations, known cellular telephone locations/orientations, known vehicle occupant eye locations/orientations, known vehicle occupant head location/orientation, known vehicle occupant hand location/orientation, a known vehicle occupant torso location/orientation, a known seat belt location, or a known vehicle seat location/orientation.”

There are additional claims. Please visit full patent to read further.

For more information, see this patent: Chan, Aaron Scott. Apparatuses, systems and methods for integrating vehicle operator gesture detection within geographic maps. U.S. Patent Number 11321951, filed January 19, 2018, and published online on May 3, 2022. Patent URL: http://patft.uspto.gov/netacgi/nph-Parser?Sect1=PTO1&Sect2=HITOFF&d=PALL&p=1&u=%2Fnetahtml%2FPTO%2Fsrchnum.htm&r=1&f=G&l=50&s1=11321951.PN.&OS=PN/11321951RS=PN/11321951

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