Methods and systems for activating a door lock in a vehicle
A method for activating a lock in a vehicle includes capturing an image of an interior of a vehicle, the image comprising an occupant on a seat of the vehicle, detecting a weight value of the occupant on a respective seat of the vehicle, processing the image for determining whether the occupant is a human or an object or an animal, processing, in response to the determination that the occupant is the human, the image for determining a parameter of the human, and activating a lock based on the parameter, or the weight value and the parameter.
1. An automatic door lock system, comprising:
a lock;
an image sensor configured to capture an image of an interior of a vehicle, the image comprising an occupant on a seat of the vehicle;
a weight sensor, wherein the weight sensor is arranged in a respective seat of the vehicle and configured to detect a weight value of the occupant on the respective seat of the vehicle; and
a processor operatively coupled to the image sensor, the weight sensor and the lock and configured to:
receive the image;
process the image to determine an occupant type of the occupant by classifying the occupant into one of a plurality of occupant types, the plurality of occupant types including a first occupant type being only a human, a second occupant type being a human with an object, a third occupant type being a human with an animal, a fourth occupant type being a human with an object and an animal, and a fifth occupant type being an object or an animal without a human;
in response to the determination that the determined occupant type is one of the first, second, third and fourth occupant types:
receive the weight value from the weight sensor;
process the received image to determine a parameter of the human; and
activate the lock based on:
the weight value and the parameter if the determined occupant type is the first occupant type; and
the parameter without the weight if the determined occupant type is the second, third, or fourth occupant type.
2. The automatic door lock system of claim 1 , wherein the parameter of the human is selected from a group comprising an age and a height.
3. The automatic door lock system of claim 2 , wherein:
if the determined occupant type is the first occupant type, the processor is configured to activate the lock in response to either one of:
the age of the human is less than a first threshold; or
the height of the human is less than a second threshold and the detected weight value of the corresponding human is less than a third threshold.
4. The automatic door lock system of claim 2 , wherein to determine the age of the human, the processor is configured to:
detect a face of the human in the image;
in response to detection of the face of the human, calculate a distance between left eye pupil and right eye pupil in each of the detected face; and
determine the age of the human based on the calculated distance in the corresponding detected face.
5. The automatic door lock system of claim 2 , wherein to determine the age of the human, the processor is configured to:
detect a face of the human in the image;
in response to detection of the face of the human, calculate a nose length in each of the detected face; and
determine the age of the human based on the calculated nose length in the corresponding detected face.
6. The automatic door lock system of claim 2 , wherein to determine the height of the human, the processor is configured to:
determine the height of the human based on a reference parameter, wherein said reference parameter comprises a height of a back rest of the seat or a horizontal distance between doors of the vehicle.
7. The automatic door lock system of claim 1 , further comprising:
a human-machine interface (HMI) operatively coupled to the processor and configured to receive an HMI input from a user, wherein in response to the HMI input, the processor is configured to activate/deactivate the lock.
8. A method for activating a lock in a vehicle, the method comprising:
capturing an image of an interior of the vehicle, the image comprising an occupant on a seat of the vehicle;
detecting a weight value of the occupant on a respective seat of the vehicle;
processing the image for determining an occupant type of the occupant by classifying the occupant into one of a plurality of occupant types, the plurality of occupant types including a first occupant type being only a human, a second occupant type being a human with an object, a third occupant type being a human with an animal, a fourth occupant type being a human with an object and an animal, and a fifth occupant type being an object or an animal without a human;
in response to the determination that the determined occupant type is one of the first, second, third and fourth occupant types:
processing the image for determining a parameter of the human; and
activating a lock based on:
the parameter if the determined occupant type is the second, third, or fourth occupant type; and
the weight value and the parameter if the determined occupant type is the first occupant type.
9. The method of claim 8 , wherein the parameter of the human is selected from a group comprising an age and a height.
10. The method of claim 9 , wherein:
if the determined occupant type is the first occupant type, activating the lock comprises activating the lock in response to either one of:
the age of the human is less than a first threshold; or
the height of the human is less than a second threshold and the detected weight value of the corresponding human is less than a third threshold,
if the determined occupant type is one of the second, third, or fourth occupant types, activating the lock comprises activating the lock in response to either one of:
the age of the human is less than the first threshold; or
the height of the human is less than the second threshold.
11. The method of claim 9 , wherein determining the age of the human comprises:
detecting a face of the human in the image;
in response to detecting of the face of the human, calculating a distance between left eye pupil and right eye pupil in each of the detected face; and
determining the age of the human based on the calculated distance in the corresponding detected face.
12. The method of claim 9 , wherein determining the age of the human comprises:
detecting a face of the human;
in response to detecting the face of the human, calculating a nose length in each of the detected face; and
determining the age of the human based on the calculated nose length in the corresponding face.
13. The method of claim 9 , wherein determining the height of the human comprises:
determining the height of the human based on a reference parameter, wherein said reference parameter comprises a height of a back rest of the seat or a horizontal distance between doors of the vehicle.
14. The method of claim 8 , further comprising:
receiving a human-machine interface (HMI) input from a user; and
activating/deactivating the lock based on the HMI input.
15. A non-transitory computer-readable medium storing computer executable instructions when executed by a processor causes the processor to perform operations of:
capturing an image of an interior of the vehicle, the image comprising an occupant on a seat of the vehicle;
detecting a weight value of the occupant on a respective seat of the vehicle;
processing the image for determining an occupant type of the occupant by classifying the occupant into one of a plurality of occupant types, the plurality of occupant types including a first occupant type being only a human, a second occupant type being a human with an object, a third occupant type being a human with an animal, a fourth occupant type being a human with an object and an animal, and a fifth occupant type being an object or an animal without a human;
in response to the determination that the determined occupant type is one of the first, second, third and fourth occupant types:
processing the image for determining a parameter of the human; and
activating a lock based on:
the parameter if the determined occupant type is the second, third, or fourth occupant type; and
the weight value and the parameter if the determined occupant type is the first occupant type.
16. The non-transitory computer-readable medium of claim 15 , wherein the parameter of the human is selected from a group comprising an age and a height.
17. The non-transitory computer-readable medium of claim 16 , wherein:
if the determined occupant type is the first occupant type, the computer executable instructions further comprise instructions, which when executed by the processor causes the processor to perform operation of activating the lock in response to either one of:
the age of the human is less than a first threshold; or
the height of the human is less than a second threshold and the detected weight value of the corresponding human is less than a third threshold,
if the determined occupant type is one of the second, third, or fourth occupant types, the computer executable instructions further comprise instructions, which when executed by the processor causes the processor to perform operation of activating the lock in response to either one of:
the age of the human is less than the first threshold; or
the height of the human is less than the second threshold.
18. The non-transitory computer-readable medium of claim 16 , wherein:
the computer executable instructions further comprise instructions, which when executed by the processor causes the processor to perform operations of:
detecting a face of the human in the image;
in response to detecting of the face of the human, calculating a distance between left eye pupil and right eye pupil in each of the detected face; and
determining the age of the human based on the calculated distance in the corresponding detected face, and
the computer executable instructions further comprise instructions, which when executed by the processor causes the processor to perform operations of:
determining the height of the human based on a reference parameter, wherein said reference parameter comprises a height of a back rest of the seat or a horizontal distance between doors of the vehicle.
19. The non-transitory computer-readable medium of claim 16 , wherein:
the computer executable instructions further comprise instructions, which when executed by the processor causes the processor to perform operations of:
detecting a face of the human in the image;
in response to detecting the face of the human, calculating a nose length in each of the detected face; and
determining the age of the human based on the calculated nose length in the corresponding face, and
the computer executable instructions further comprise instructions, which when executed by the processor causes the processor to perform operations of:
determining the height of the human based on a reference parameter, wherein said reference parameter comprises a height of a back rest of the seat or a horizontal distance between doors of the vehicle.