Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/process/file/efs/guidance/eTD-info-I.jsp.
Claims 1-20 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-20 of US Pat. No. 12,309,223, 11,804,058, U.S. Patent No. 11,308,316. Although the claims at issue are not identical, they are not patentably distinct from each other because they recites similar subject matters, such as vehicle object detection, detecting the object or non-detection of the such object.
Instant Application
US Pat. No. 12,309,223
1. A system for detecting vehicle occupancy, the system comprising:
a roadside imaging device having a field of view;
a processor, in communication with a memory, configured to:
command the first roadside imaging device to capture one or more images;
receive the captured images from the first roadside imaging device; detect a vehicle in the captured images; compute a vehicle occupancy by, in each of the captured images: determining one or more regions of interest in each of the captured images;
detecting instances of occupants and no occupants in the one or more regions of interest; and determining the vehicle occupancy based on the instances of occupants and no occupants in the one or more regions of interest determining a most likely number of occupants based on each determined vehicle occupancy; and transmit the vehicle occupancy to a monitoring system or store the vehicle occupancy in memory.
2. The system of claim 1, wherein the processor is configured to compute the vehicle occupancy in each of the captured images by detecting an impediment for detecting the instances of occupants and no occupants.
3. The system of claim 2, wherein the impediment comprises an obstruction.
4. The system of claim 2, wherein the impediment comprises at least one of poor illumination, inclement weather, poor view angle, and poor image quality.
5. The system of claim 2, wherein the captured image is flagged for further validation when the impediment is detected.
6. The system of claim 2, wherein the determined vehicle occupancy of the captured image is excluded from determining the most likely number of occupants when the impediment is detected.
7. The system of claim 2, wherein detecting the impediment reduces a confidence of the determined vehicle occupancy of that captured image and the most likely number of occupants is determined based in part on the confidence.
8. The system of claim 1, wherein occupants are anonymized in the captured images.
9. The system of claim 1, wherein captured images with no detected regions of interest are discarded or recorded as instances of no occupants.
10. The system of claim 1, wherein captured images with no detected vehicle are discarded or recorded as instances of no occupants.
11. The system of claim 1, wherein no occupants is an absence of occupants in seats of the vehicle or empty seats of the vehicle.
12. The system of claim 1, wherein the processor is further configured to make a toll or enforcement decision based on the most likely number of occupants.
13. A method for detecting vehicle occupancy, the method comprising: receiving captured images from a roadside imaging device; detecting a vehicle in the captured images;computing a vehicle occupancy by, in each of the captured images: determining one or more regions of interest in each of the captured images;detecting instances of occupants and no occupants in the one or more regions of interest; anddetermining the vehicle occupancy based on the instances of occupants and no occupants in the one or more regions of interest; determining a most likely number of occupants based on each determined vehicle occupancy; and transmitting the vehicle occupancy to a monitoring system or storing the vehicle occupancy in memory.
14. The method of claim 13, wherein computing the vehicle occupancy in each of the captured images further comprises detecting an impediment to detecting instances of no occupants.
15. The method of claim 14, wherein the impediment comprises at least one of an obstruction, poor illumination, inclement weather, poor view angle, and poor image quality.
16. The method of claim 14, wherein the method further comprises flagging the captured image for further validation when the impediment is detected.
17. The method of claim 14, wherein the determined vehicle occupancy of the captured image is excluded from determining the most likely number of occupants when the impediment is detected.
18. The method of claim 14, wherein detecting the impediment reduces a confidence of the determined vehicle occupancy of that captured image and the most likely number of occupants is determined based in part on the confidence.
19. The method of claim 13, wherein further comprising anonymizing the occupants in the captured images.
20. The method of claim 13, wherein captured images with no detected regions of interest are discarded or recorded as instances of no occupants, and wherein captured images with no detected vehicle are discarded or recorded as instances of no occupants.
A system for detecting vehicle occupancy, the system comprising:
a first roadside imaging device having a first field of view;
a first roadside light emitter emitting light in the first field of view; a processor, in communication with a memory, configured to:
command the first roadside light emitter to emit light according to a first pattern for a first duration;
command the first roadside imaging device to capture one or more images according to a second pattern associated with the first pattern, during a second duration associated with the first duration;
receive the captured images from the first roadside imaging device; detect a vehicle in the captured images; compute a vehicle occupancy by, in each of the captured images: determining one or more regions of interest in each of the captured images; determining the vehicle occupancy based on the one or more regions of interest; and determining a most likely number of occupants based on each determined vehicle occupancy; and transmit the vehicle occupancy to a monitoring system or store the vehicle occupancy in memory.
2. The system of claim 1, wherein: the first roadside imaging device is positioned to extract data for different perspectives across the field of view; and at least some of the images captured by the first roadside imaging device include the different perspectives.
3. The system of claim 2 wherein the processor is configured to compute a yaw angle relative to a horizontal axis perpendicular to an expected direction, wherein the images captured by the first roadside imaging device include the different perspectives based on the first yaw angle.
4. The system of claim 1, wherein the processor, to compute the vehicle occupancy, is configured to: discard captured images with no detected vehicle; discard uninteresting regions of the plurality of captured images to generate subsets of the plurality of captured images; and determine a number of visible occupants based on determining one or more regions of interest in the respective subset of the plurality of captures images.
5. The system of claim 1, wherein the first roadside imaging device and the first roadside light emitter are attached to a mobile roadside structure.
6. The system of claim 1, further comprising:a second roadside imaging device, above the first roadside imaging device, the second roadside imaging device having a second field of view; a second roadside light emitter emitting light in the second field of view; wherein the processor is further configured to: command the second roadside light emitter to emit light according to a third pattern for a third duration; command the second roadside imaging device to capture additional images according to a fourth pattern associated with the third pattern, during a fourth duration associated with the third duration; receive the additional captured images from the second roadside imaging device; detect a further vehicle in the additional captured images; compute another vehicle occupancy by, in each of the additional captured images by:determining one or more regions of interest in each of the additional captured images; determining the vehicle occupancy using the one or more regions of interest; and determining a most likely number of occupants based on each determined vehicle occupancy of the further vehicle; and transmit the vehicle occupancy to the monitoring system.
7. The system of claim 6, wherein the first field of view and the second field of view overlap, and the processor is further configured to:determine the one or more regions of interest in the one or more additional captured images; determine a further number of visible occupants in the one or more additional captured images in the one or more regions of interest; and determine the most likely number of occupants based on each determined vehicle occupancy and each determined further number of visible occupants.
8. The system of claim 1, wherein the captured images are anonymized.
9. The system of claim 8, where anonymizing the captured images comprises blurring detected faces.
10. The system of claim 1, further comprising:a sensor for detecting ambient conditions; wherein the processor is further configured to: receive ambient condition information from the sensor; determine an optimal configuration for the imaging device based on the received ambient condition; and transmit a further command signal to the imaging device capture images according to the optimal configuration.
11. The system of claim 1, wherein the light emitter is an LED emitting infrared or near infrared light, the first pattern is 120 pulses per second.
12. A method for detecting vehicle occupancy, the method comprising;commanding a first roadside light emitter to emit light according to a first pattern for a first duration;commanding the first roadside imaging device to capture images according to a second pattern associated with the first pattern, during a second duration associated with the first duration;receiving the captured images from the first roadside imaging device; detecting a vehicle in the captured images; computing a vehicle occupancy by, in each of the captured images: determining one or more regions of interest in each of the captured images; determining the vehicle occupancy in the one or more regions of interest; and determining a most likely number of occupants based on each determined vehicle occupancy; and transmitting the most likely number of occupants to a monitoring system or storing the vehicle occupancy in memory.
13. The method of claim 12, further comprising:discarding captured images with no detected vehicles; discarding uninteresting regions of the plurality of captured images to generate subsets of the plurality of captured images; and determining the number of occupants based on determining one or more regions of interest in the respective subset of the plurality of captures images.
14. The method of claim 12, wherein the one or more regions of interest include at least one of a rear side window and a front side window.
15. The method of claim 12, wherein each of the captured images includes different perspectives based on a yaw angle which encourages image variation.
16. The method of claim 12, the method further comprising:commanding a second roadside imaging device to capture additional images from a second field of view according to a fourth pattern associated with the first pattern, for a fourth duration associated with the first duration;receiving the additional captured images from the second roadside imaging device; detecting a further vehicle in the additional captured images; wherein computing the vehicle occupancy further comprises, for each of the additional captured images: determining one or more additional regions of interest of the vehicle; determining the vehicle occupancy in the additional one or more regions of interest; and determining the most likely number of occupants based on the each of the number of visible occupants and the further number of visible occupants; and transmitting the vehicle occupancy to the monitoring system.
17. The method of claim 16, the method further comprising:commanding a second roadside light emitter to emit light according to a third pattern for a third duration; commanding the second roadside imaging device to capture additional images according to a fourth pattern associated with the third pattern, during a fourth duration associated with the third duration; receiving the additional captured images from the first roadside imaging device; detecting a further vehicle in the additional captured images; computing a further vehicle occupancy by, in each of the additional captured images: determining one or more further regions of interest in each of the additional captured images; determining the further vehicle occupancy based on the one or more further regions of interest; and determining a most likely number of occupants based on each determined further vehicle occupancy; and transmitting the most likely number of occupants to the monitoring system.
18. The method of claim 12 further comprising computing a correction parameter and providing visual guidance using augmented reality avatars on a display device.
19. The method of claim 12, further comprising anonymizing the captured images.
20. The method of claim 19, where anonymizing the captured images comprises blurring detected faces.
US Pat. No. 12,309,223
US Pat. No. 11,804,058
A system for detecting vehicle occupancy, the system comprising:a first roadside imaging device having a first field of view;
a first roadside light emitter emitting light in the first field of view; a processor, in communication with a memory,
configured to: command the first roadside light emitter to emit light according to a first pattern for a first duration;
command the first roadside imaging device to capture one or more images according to a second pattern associated with the first pattern, during a second duration associated with the first duration;
receive the captured images from the first roadside imaging device; detect a vehicle in the captured images; compute a vehicle occupancy by, in each of the captured images: determining one or more regions of interest in each of the captured images; determining the vehicle occupancy based on the one or more regions of interest; and determining a most likely number of occupants based on each determined vehicle occupancy; and transmit the vehicle occupancy to a monitoring system or store the vehicle occupancy in memory.
2. The system of claim 1, wherein:the first roadside imaging device is positioned to extract data for different perspectives across the field of view; and at least some of the images captured by the first roadside imaging device include the different perspectives.
3. The system of claim 2 wherein the processor is configured to compute a yaw angle relative to a horizontal axis perpendicular to an expected direction, wherein the images captured by the first roadside imaging device include the different perspectives based on the first yaw angle.
4. The system of claim 1, wherein the processor, to compute the vehicle occupancy, is configured to:discard captured images with no detected vehicle; discard uninteresting regions of the plurality of captured images to generate subsets of the plurality of captured images; and determine a number of visible occupants based on determining one or more regions of interest in the respective subset of the plurality of captures images.
5. The system of claim 1, wherein the first roadside imaging device and the first roadside light emitter are attached to a mobile roadside structure.
6. The system of claim 1, further comprising:a second roadside imaging device, above the first roadside imaging device, the second roadside imaging device having a second field of view; a second roadside light emitter emitting light in the second field of view; wherein the processor is further configured to: command the second roadside light emitter to emit light according to a third pattern for a third duration; command the second roadside imaging device to capture additional images according to a fourth pattern associated with the third pattern, during a fourth duration associated with the third duration; receive the additional captured images from the second roadside imaging device; detect a further vehicle in the additional captured images; compute another vehicle occupancy by, in each of the additional captured images by:determining one or more regions of interest in each of the additional captured images; determining the vehicle occupancy using the one or more regions of interest; and determining a most likely number of occupants based on each determined vehicle occupancy of the further vehicle; and transmit the vehicle occupancy to the monitoring system.
7. The system of claim 6, wherein the first field of view and the second field of view overlap, and the processor is further configured to:determine the one or more regions of interest in the one or more additional captured images; determine a further number of visible occupants in the one or more additional captured images in the one or more regions of interest; and determine the most likely number of occupants based on each determined vehicle occupancy and each determined further number of visible occupants.
8. The system of claim 1, wherein the captured images are anonymized.
9. The system of claim 8, where anonymizing the captured images comprises blurring detected faces.
10. The system of claim 1, further comprising:a sensor for detecting ambient conditions; wherein the processor is further configured to: receive ambient condition information from the sensor; determine an optimal configuration for the imaging device based on the received ambient condition; and transmit a further command signal to the imaging device capture images according to the optimal configuration.
11. The system of claim 1, wherein the light emitter is an LED emitting infrared or near infrared light, the first pattern is 120 pulses per second.
12. A method for detecting vehicle occupancy, the method comprising;commanding a first roadside light emitter to emit light according to a first pattern for a first duration;commanding the first roadside imaging device to capture images according to a second pattern associated with the first pattern, during a second duration associated with the first duration;receiving the captured images from the first roadside imaging device; detecting a vehicle in the captured images; computing a vehicle occupancy by, in each of the captured images: determining one or more regions of interest in each of the captured images; determining the vehicle occupancy in the one or more regions of interest; and determining a most likely number of occupants based on each determined vehicle occupancy; and transmitting the most likely number of occupants to a monitoring system or storing the vehicle occupancy in memory.
13. The method of claim 12, further comprising:discarding captured images with no detected vehicles; discarding uninteresting regions of the plurality of captured images to generate subsets of the plurality of captured images; and determining the number of occupants based on determining one or more regions of interest in the respective subset of the plurality of captures images.
14. The method of claim 12, wherein the one or more regions of interest include at least one of a rear side window and a front side window.
15. The method of claim 12, wherein each of the captured images includes different perspectives based on a yaw angle which encourages image variation.
16. The method of claim 12, the method further comprising:commanding a second roadside imaging device to capture additional images from a second field of view according to a fourth pattern associated with the first pattern, for a fourth duration associated with the first duration;receiving the additional captured images from the second roadside imaging device; detecting a further vehicle in the additional captured images; wherein computing the vehicle occupancy further comprises, for each of the additional captured images: determining one or more additional regions of interest of the vehicle; determining the vehicle occupancy in the additional one or more regions of interest; and determining the most likely number of occupants based on the each of the number of visible occupants and the further number of visible occupants; and transmitting the vehicle occupancy to the monitoring system.
17. The method of claim 16, the method further comprising:commanding a second roadside light emitter to emit light according to a third pattern for a third duration; commanding the second roadside imaging device to capture additional images according to a fourth pattern associated with the third pattern, during a fourth duration associated with the third duration; receiving the additional captured images from the first roadside imaging device; detecting a further vehicle in the additional captured images; computing a further vehicle occupancy by, in each of the additional captured images: determining one or more further regions of interest in each of the additional captured images; determining the further vehicle occupancy based on the one or more further regions of interest; and determining a most likely number of occupants based on each determined further vehicle occupancy; and transmitting the most likely number of occupants to the monitoring system.
18. The method of claim 12 further comprising computing a correction parameter and providing visual guidance using augmented reality avatars on a display device.
19. The method of claim 12, further comprising anonymizing the captured images.
20. The method of claim 19, where anonymizing the captured images comprises blurring detected faces.
1. A system for detecting vehicle occupancy, the system comprising: a first roadside imaging device having a first field of view;
a first roadside light emitter emitting light in the first field of view;
a roadside vehicle detector;
a processor, in communication with a memory, configured to: receive a signal from the roadside vehicle detector; command the first roadside light emitter to emit light according to a first pattern for a first duration;
command the first roadside imaging device to capture one or more images according to a second pattern associated with the first pattern, during a second duration associated with the first duration;
receive the captured images from the first roadside imaging device;
compute a vehicle occupancy by, in each of the captured images: determining one or more regions of interest in each of the captured images;
determining the vehicle occupancy based on the one or more regions of interest; and determining a most likely number of occupants based on each determined vehicle occupancy; and
transmit the vehicle occupancy to a monitoring system or store the vehicle occupancy in memory.
2. The system of claim 1, wherein: the first roadside imaging device is positioned to extract data for different perspectives across the field of view; and at least some of the images captured by the first roadside imaging device include the different perspectives.
3. The system of claim 2 wherein the processor is configured to compute a yaw angle relative to a horizontal axis perpendicular to an expected direction, wherein the images captured by the first roadside imaging device include the different perspectives based on the first yaw angle.
4. The system of claim 1, wherein the processor, to compute the vehicle occupancy, is configured to: discard uninteresting regions of the plurality of captured images to generate subsets of the plurality of captured images; and determine a number of visible occupants based on determining one or more regions of interest in the respective subset of the plurality of captures images.
5. The system of claim 1, wherein the first roadside imaging device, the first roadside light emitter, and the vehicle detector are attached to a mobile roadside structure.
6. The system of claim 1, further comprising: a second roadside imaging device, above the first roadside imaging device, the second roadside imaging device having a second field of view; a second roadside light emitter emitting light in the second field of view; wherein the processor is further configured to: receive another signal from the vehicle detector; command the second roadside light emitter to emit light according to a third pattern for a third duration; command the second roadside imaging device to capture additional images according to a fourth pattern associated with the third pattern, during a fourth duration associated with the third duration; receive the additional captured images from the second roadside imaging device; compute another vehicle occupancy by, in each of the additional captured images by: determining one or more regions of interest in each of the additional captured images; determining the vehicle occupancy using the one or more regions of interest; and determining a most likely number of occupants based on each determined vehicle occupancy of the further vehicle; and transmit the vehicle occupancy to the monitoring system.
7. The system of claim 6, wherein the first field of view and the second field of view overlap, and the processor is further configured to: determine the one or more regions of interest in the one or more additional captured images; determine a further number of visible occupants in the one or more additional captured images in the one or more regions of interest; and determine the most likely number of occupants based on each determined vehicle occupancy and each determined further number of visible occupants.
8. The system of claim 1, wherein the processor is further configured to: monitor, over time, a plurality of signals from the roadside vehicle detector to determine an expected vehicle speed; and adjust one or more parameters of the first roadside imaging device or the first light emitter into a determined optimal configuration for capturing images based on the expected vehicle speed.
9. The system of claim 1, wherein the processor is further configured to: monitor, over time, a plurality of signals from the roadside vehicle detector to determine an expected vehicle speed; and determine the first pattern and the first time window based on the expected vehicle speed.
10. The system of claim 1, further comprising: a sensor for detecting ambient conditions; wherein the processor is further configured to: receive ambient condition information from the sensor; determine an optimal configuration for the imaging device based on the received ambient condition; and transmit a further command signal to the imaging device capture images according to the optimal configuration.
11. The system of claim 1, wherein the light emitter is an LED emitting infrared or near infrared light, the first pattern is 120 pulses per second.
12. A method for detecting vehicle occupancy, the method comprising; receiving a signal from a detector based on a first field of view of a first roadside imaging device; commanding a first roadside light emitter to emit light according to a first pattern for a first duration; commanding the first roadside imaging device to capture images according to a second pattern associated with the first pattern, during a second duration associated with the first duration; receiving the captured images from the first roadside imaging device; computing a vehicle occupancy by, in each of the captured images: determining one or more regions of interest in each of the captured images; determining the vehicle occupancy in the one or more regions of interest; and determining a most likely number of occupants based on each determined vehicle occupancy; and transmitting the most likely number of occupants to a monitoring system or storing the vehicle occupancy in memory.
13. The method of claim 12, further comprising: discarding uninteresting regions of the plurality of captured images to generate subsets of the plurality of captured images; and determining the number of occupants based on determining one or more regions of interest in the respective subset of the plurality of captures images.
14. The method of claim 12, wherein the one or more regions of interest include at least one of a rear side window and a front side window.
15. The method of claim 12, wherein each of the captured images includes different perspectives based on a yaw angle which encourages image variation.
16. The method of claim 12, the method further comprising: commanding a second roadside imaging device to capture additional images from a second field of view according to a fourth pattern associated with the first pattern, for a fourth duration associated with the first duration; receive the additional captured images from the second roadside imaging device; wherein computing the vehicle occupancy further comprises, for each of the additional captured images: determining one or more additional regions of interest of the vehicle; determining the vehicle occupancy in the additional one or more regions of interest; and determining the most likely number of occupants based on the each of the number of visible occupants and the further number of visible occupants; and transmitting the vehicle occupancy to the monitoring system.
17. The method of claim 16, the method further comprising: receiving a signal indicating from the detector based on the second field of view; commanding a second roadside light emitter to emit light according to a third pattern for a third duration; commanding the second roadside imaging device to capture additional images according to a fourth pattern associated with the third pattern, during a fourth duration associated with the third duration; receiving the additional captured images from the first roadside imaging device; computing a further vehicle occupancy by, in each of the additional captured images: determining one or more further regions of interest in each of the additional captured images; determining the further vehicle occupancy based on the one or more further regions of interest; and determining a most likely number of occupants based on each determined further vehicle occupancy; and transmitting the most likely number of occupants to the monitoring system.
18. The method of claim 11 further comprising computing a correction parameter and providing visual guidance using augmented reality avatars on a display device
19. The method of claim 12, the method further comprising: monitoring, over time, a plurality of signals from the roadside vehicle detector to determine an expected vehicle speed; and adjusting one or more parameters of the first roadside imaging device or the first light emitter into a determined adjusted configuration for capturing images based on the expected vehicle speed.
20. The method of claim 12, the method further comprising: monitoring, over time, a plurality of signals from the roadside vehicle detector to determine an expected vehicle speed; and determining the first pattern and the first time window based on the expected vehicle speed.
US Pat. No. 11,804,058
US Pat. No. 11,308,316
1. A system for detecting vehicle occupancy, the system comprising: a first roadside imaging device having a first field of view;
a first roadside light emitter emitting light in the first field of view;
a roadside vehicle detector;
a processor, in communication with a memory, configured to: receive a signal from the roadside vehicle detector; command the first roadside light emitter to emit light according to a first pattern for a first duration;
command the first roadside imaging device to capture one or more images according to a second pattern associated with the first pattern, during a second duration associated with the first duration;
receive the captured images from the first roadside imaging device;
compute a vehicle occupancy by, in each of the captured images: determining one or more regions of interest in each of the captured images;
determining the vehicle occupancy based on the one or more regions of interest; and determining a most likely number of occupants based on each determined vehicle occupancy; and
transmit the vehicle occupancy to a monitoring system or store the vehicle occupancy in memory.
2. The system of claim 1, wherein: the first roadside imaging device is positioned to extract data for different perspectives across the field of view; and at least some of the images captured by the first roadside imaging device include the different perspectives.
3. The system of claim 2 wherein the processor is configured to compute a yaw angle relative to a horizontal axis perpendicular to an expected direction, wherein the images captured by the first roadside imaging device include the different perspectives based on the first yaw angle.
4. The system of claim 1, wherein the processor, to compute the vehicle occupancy, is configured to: discard uninteresting regions of the plurality of captured images to generate subsets of the plurality of captured images; and determine a number of visible occupants based on determining one or more regions of interest in the respective subset of the plurality of captures images.
5. The system of claim 1, wherein the first roadside imaging device, the first roadside light emitter, and the vehicle detector are attached to a mobile roadside structure.
6. The system of claim 1, further comprising: a second roadside imaging device, above the first roadside imaging device, the second roadside imaging device having a second field of view; a second roadside light emitter emitting light in the second field of view; wherein the processor is further configured to: receive another signal from the vehicle detector; command the second roadside light emitter to emit light according to a third pattern for a third duration; command the second roadside imaging device to capture additional images according to a fourth pattern associated with the third pattern, during a fourth duration associated with the third duration; receive the additional captured images from the second roadside imaging device; compute another vehicle occupancy by, in each of the additional captured images by: determining one or more regions of interest in each of the additional captured images; determining the vehicle occupancy using the one or more regions of interest; and determining a most likely number of occupants based on each determined vehicle occupancy of the further vehicle; and transmit the vehicle occupancy to the monitoring system.
7. The system of claim 6, wherein the first field of view and the second field of view overlap, and the processor is further configured to: determine the one or more regions of interest in the one or more additional captured images; determine a further number of visible occupants in the one or more additional captured images in the one or more regions of interest; and determine the most likely number of occupants based on each determined vehicle occupancy and each determined further number of visible occupants.
8. The system of claim 1, wherein the processor is further configured to: monitor, over time, a plurality of signals from the roadside vehicle detector to determine an expected vehicle speed; and adjust one or more parameters of the first roadside imaging device or the first light emitter into a determined optimal configuration for capturing images based on the expected vehicle speed.
9. The system of claim 1, wherein the processor is further configured to: monitor, over time, a plurality of signals from the roadside vehicle detector to determine an expected vehicle speed; and determine the first pattern and the first time window based on the expected vehicle speed.
10. The system of claim 1, further comprising: a sensor for detecting ambient conditions; wherein the processor is further configured to: receive ambient condition information from the sensor; determine an optimal configuration for the imaging device based on the received ambient condition; and transmit a further command signal to the imaging device capture images according to the optimal configuration.
11. The system of claim 1, wherein the light emitter is an LED emitting infrared or near infrared light, the first pattern is 120 pulses per second.
12. A method for detecting vehicle occupancy, the method comprising; receiving a signal from a detector based on a first field of view of a first roadside imaging device; commanding a first roadside light emitter to emit light according to a first pattern for a first duration; commanding the first roadside imaging device to capture images according to a second pattern associated with the first pattern, during a second duration associated with the first duration; receiving the captured images from the first roadside imaging device; computing a vehicle occupancy by, in each of the captured images: determining one or more regions of interest in each of the captured images; determining the vehicle occupancy in the one or more regions of interest; and determining a most likely number of occupants based on each determined vehicle occupancy; and transmitting the most likely number of occupants to a monitoring system or storing the vehicle occupancy in memory.
13. The method of claim 12, further comprising: discarding uninteresting regions of the plurality of captured images to generate subsets of the plurality of captured images; and determining the number of occupants based on determining one or more regions of interest in the respective subset of the plurality of captures images.
14. The method of claim 12, wherein the one or more regions of interest include at least one of a rear side window and a front side window.
15. The method of claim 12, wherein each of the captured images includes different perspectives based on a yaw angle which encourages image variation.
16. The method of claim 12, the method further comprising: commanding a second roadside imaging device to capture additional images from a second field of view according to a fourth pattern associated with the first pattern, for a fourth duration associated with the first duration; receive the additional captured images from the second roadside imaging device; wherein computing the vehicle occupancy further comprises, for each of the additional captured images: determining one or more additional regions of interest of the vehicle; determining the vehicle occupancy in the additional one or more regions of interest; and determining the most likely number of occupants based on the each of the number of visible occupants and the further number of visible occupants; and transmitting the vehicle occupancy to the monitoring system.
17. The method of claim 16, the method further comprising: receiving a signal indicating from the detector based on the second field of view; commanding a second roadside light emitter to emit light according to a third pattern for a third duration; commanding the second roadside imaging device to capture additional images according to a fourth pattern associated with the third pattern, during a fourth duration associated with the third duration; receiving the additional captured images from the first roadside imaging device; computing a further vehicle occupancy by, in each of the additional captured images: determining one or more further regions of interest in each of the additional captured images; determining the further vehicle occupancy based on the one or more further regions of interest; and determining a most likely number of occupants based on each determined further vehicle occupancy; and transmitting the most likely number of occupants to the monitoring system.
18. The method of claim 11 further comprising computing a correction parameter and providing visual guidance using augmented reality avatars on a display device
19. The method of claim 12, the method further comprising: monitoring, over time, a plurality of signals from the roadside vehicle detector to determine an expected vehicle speed; and adjusting one or more parameters of the first roadside imaging device or the first light emitter into a determined adjusted configuration for capturing images based on the expected vehicle speed.
20. The method of claim 12, the method further comprising: monitoring, over time, a plurality of signals from the roadside vehicle detector to determine an expected vehicle speed; and determining the first pattern and the first time window based on the expected vehicle speed.
1. A system for detecting occupancy of a vehicle travelling in an expected direction of travel along a road, the system comprising: a first roadside imaging device positioned on a roadside, having a first field of view of the road, the first field of view incident on a side of the vehicle when the vehicle is on the road within the first field of view;
a first roadside light emitter emitting light towards vehicles in the first field of view; a roadside vehicle detector;
a processor, in communication with a memory, configured to: receive a signal from the roadside vehicle detector indicating that the vehicle is within the first field of view or proximate, relative to the expected direction of vehicle travel, to the first field of view;
command the first roadside light emitter to emit light according to a first pattern for a first duration; command the first roadside imaging device to capture one or more images of the side of the vehicle according to a second pattern associated with the first pattern, during a second duration associated with the first duration; receive the captured images of the side of the vehicle from the first roadside imaging device;
compute a vehicle occupancy of the vehicle by, in each of the captured images: determining one or more regions of interest of the vehicle in each of the captured images;
determining the vehicle occupancy as a number of visible occupants in the one or more regions of interest; and determining a most likely number of occupants based on each determined vehicle occupancy; and
transmit the vehicle occupancy to a monitoring system.
2. The system of claim 1, wherein: the first roadside imaging device is positioned to extract data for different perspectives of occupants as the vehicle travels horizontally across the field of view; and each of the images captured by the first roadside imaging device include different perspectives of the side of the vehicle.
3. The system of claim 2 wherein the processor is configured to compute a yaw angle relative to a horizontal axis perpendicular to the expected direction of vehicle travel, wherein the images captured by the first roadside imaging device include the different perspectives of the side of the vehicle based on the first yaw angle.
4. The system of claim 1, wherein the processor, to compute the vehicle occupancy of the vehicle, is configured to: discard uninteresting regions of the plurality of captured images to generate subsets of the plurality of captured images; and determine the number of visible occupants based on determining one or more regions of interest of the vehicle in the respective subset of the plurality of captures images.
5. The system of claim 1, wherein the first roadside imaging device, the first roadside light emitter, and the vehicle detector are attached to a mobile roadside structure.
6. The system of claim 1, further comprising: a second roadside imaging device, above the first roadside imaging device, the second roadside imaging device having a second field of view of a second lane of the road, the second lane being further from the first roadside imaging device than a first lane of the road, the second field of view incident on a side of a further vehicle when the further vehicle is in the second lane within the second field of view; a second roadside light emitter adjacent to the road and emitting light towards vehicles in the second field of view; wherein the processor is further configured to: receive another signal from the vehicle detector indicating that the further vehicle is within or proximate, relative to the expected direction of vehicle travel, to the second field of view; command the second roadside light emitter to emit light according to a third pattern for a third duration; command the second roadside imaging device to capture additional images of the side of the further vehicle according to a fourth pattern associated with the third pattern, during a fourth duration associated with the third duration; receive the additional captured images of the side of the further vehicle from the second roadside imaging device; compute a vehicle occupancy of the further vehicle by, in each of the additional captured images by: determining one or more regions of interest of the further vehicle in each of the additional captured images; determining the vehicle occupancy of the further vehicle as a number of visible occupants of the further vehicle in the one or more regions of interest of the further vehicle; and determining a most likely number of occupants of the further vehicle based on each determined vehicle occupancy of the further vehicle; and transmit the vehicle occupancy of the further vehicle to the monitoring system.
7. The system of claim 6, wherein the first field of view and the second field of view overlap, and the processor is further configured to: determine the one or more regions of interest of the vehicle in the one or more additional captured images; determine a further number of visible occupants of the vehicle in the one or more additional captured images in the one or more regions of interest; and determine the most likely number of occupants of the vehicle based on each determined vehicle occupancy and each determined further number of visible occupants.
8. The system of claim 1, wherein the processor is further configured to: monitor, over time, a plurality of signals from the roadside vehicle detector to determine an expected vehicle speed of the vehicle; and adjust one or more parameters of the first roadside imaging device or the first light emitter into a determined optimal configuration for capturing vehicles travelling the expected vehicle speed.
9. The system of claim 1, wherein the processor is further configured to: monitor, over time, a plurality of signals from the roadside vehicle detector to determine an expected vehicle speed of the vehicle; and determine the first pattern and the first time window based on the expected vehicle speed.
10. The system of claim 1, further comprising: a sensor for detecting ambient conditions; wherein the processor is further configured to: receive ambient condition information from the sensor; determine an optimal configuration for the imaging device based on the received ambient condition; and transmit a further command signal to the imaging device capture images according to the optimal configuration.
11. The system of claim 1, wherein the light emitter is an LED emitting infrared or near infrared light, the first pattern is 120 pulses per second, and the regions of interest are a rear side window and a front side window.
12. A method for detecting occupancy of a vehicle travelling in an expected direction of travel along a road, the method comprising; receiving a signal indicating that the vehicle is within or proximate, relative to the expected direction of vehicle travel, to a first field of view of a first roadside imaging device; commanding a first roadside light emitter to emit light according to a first pattern for a first duration; commanding the first roadside imaging device to capture images of a side of the vehicle according to a second pattern associated with the first pattern, during a second duration associated with the first duration; receiving the captured images of the side of the vehicle from the first roadside imaging device; computing a vehicle occupancy of the vehicle by, in each of the captured images: determining one or more regions of interest of the side of the vehicle in each of the captured images; determining the vehicle occupancy in the one or more regions of interest; and determining a most likely number of occupants based on each determined vehicle occupancy; and transmitting the most likely number of occupants to a monitoring system.
13. The method of claim 12, further comprising: discarding uninteresting regions of the plurality of captured images to generate subsets of the plurality of captured images; and determining the number of visible occupants based on determining one or more regions of interest of the vehicle in the respective subset of the plurality of captures images.
14. The method of claim 12, wherein the one or more regions of interest include at least one of a rear side window and a front side window.
15. The method of claim 12, wherein each of the captured images includes the side of the vehicle at different perspectives based on a yaw angle which encourages image variation.
16. The method of claim 12, the method further comprising: commanding a second roadside imaging device to capture additional images of the side of the vehicle from a second field of view according to a fourth pattern associated with the first pattern, for a fourth duration associated with the first duration; receive the additional captured images of the side of the vehicle from the second roadside imaging device; wherein computing the vehicle occupancy of the vehicle further comprises, for each of the additional captured images: determining one or more additional regions of interest of the vehicle; determining the vehicle occupancy of the vehicle in the additional one or more regions of interest of the vehicle; and determining the most likely number of occupants of the vehicle based on the each of the number of visible occupants and the further number of visible occupants; and transmitting the vehicle occupancy of the further vehicle to the monitoring system.
17. The method of claim 16, the method further comprising: receiving a signal indicating that a further vehicle is within or proximate, relative to the expected direction of vehicle travel, to the second field of view; commanding a second roadside light emitter to emit light according to a third pattern for a third duration; commanding the second roadside imaging device to capture additional images of a side of the further vehicle according to a fourth pattern associated with the third pattern, during a fourth duration associated with the third duration; receiving the additional captured images of the side of the vehicle from the first roadside imaging device; computing a vehicle occupancy of the further vehicle by, in each of the additional captured images: determining one or more further regions of interest of a side of the further vehicle in each of the additional captured images; determining the further vehicle occupancy as a number of visible occupants in the one or more further regions of interest; and determining a most likely number of occupants of the further vehicle based on each determined further vehicle occupancy; and transmitting the most likely number of occupants of the further vehicle to the monitoring system.
18. The method of claim 11 further comprising computing a correction parameter and providing visual guidance using augmented reality avatars on a display device
19. The method of claim 12, the method further comprising: monitoring, over time, a plurality of signals from the roadside vehicle detector to determine an expected vehicle speed of the vehicle; and adjusting one or more parameters of the first roadside imaging device or the first light emitter into a determined adjusted configuration for capturing vehicles travelling the expected vehicle speed.
20. The method of claim 12, the method further comprising: monitoring, over time, a plurality of signals from the roadside vehicle detector to determine an expected vehicle speed of the vehicle; and determining the first pattern and the first time window based on the expected vehicle speed.
Allowable Subject Matter
The following is an examiner’s statement of reasons for allowance:
US 11475576 provided a method for detecting a vehicle including receiving continuously captured front images, setting a search area of the vehicle in a target image based on a location of the vehicle or a vehicle area detected from a previous image among the front images, detecting the vehicle in the search area according to a machine learning model, and tracking the vehicle in the target image by using feature points of the vehicle extracted from the previous image according to a vehicle detection result based on the machine learning model. Since the entire image is not used as a vehicle detection area, a processing speed may be increased, and a forward vehicle tracked in an augmented reality navigation may be continuously displayed without interruption, thereby providing a stable service to the user.
US 20220147745 A1 involves bounding a vehicle (110) detected from video frames of a video (120) in a vehicle bounding box using processors of an edge device (102), where the video is captured by video image sensors of the edge device. A set of lanes of a roadway detected from the video frames in a set of polygons is bounded using the processors, where one of the polygons i.e. lane-of-interest (LOI) polygon, bounds a LOI. A potential traffic violation is detected based in part on an overlap of a portion of the box and the part of LOI polygon.
US8682035B2 imaging the surrounding of a vehicle is provided. The method includes the steps of (i) taking a series of two dimensional images of the vehicle surrounding, (ii) taking a series of three dimensional images of the vehicle surrounding that including depth information, (iii) determining at least one object in an area of interest in one of the series of images and tracking the object in the area of interest, (iv) processing the others of the series of images to retrieve object information from said other series of images, (v) adjusting the objects to be tracked in the one series of images in accordance with the object information received from processing the other series of images.
None of the cited prior arts discloses “a roadside imaging device having a field of view;a processor, in communication with a memory, configured to: command the first roadside imaging device to capture one or more images; receive the captured images from the first roadside imaging device; detect a vehicle in the captured images; compute a vehicle occupancy by, in each of the captured images: determining one or more regions of interest in each of the captured images; detecting instances of occupants and no occupants in the one or more regions of interest; and determining the vehicle occupancy based on the instances of occupants and no occupants in the one or more regions of interest determining a most likely number of occupants based on each determined vehicle occupancy; and transmit the vehicle occupancy to a monitoring system or store the vehicle occupancy in memory.”
Any comments considered necessary by applicant must be submitted no later than the payment of the issue fee and, to avoid processing delays, should preferably accompany the issue fee. Such submissions should be clearly labeled “Comments on Statement of Reasons for Allowance.”
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
US 11475576 B2 Method for detecting vehicle and device for executing the same
US 20220147745 A1 Method for detecting a potential traffic violation, involves bounding a vehicle detected from multiple video frames of a video in a vehicle bounding box using multiple processors of an edge device
US 20220036473 A1 SYSTEM AND METHOD FOR ADVERSE VEHICLE EVENT DETERMINATION
US 8682035 B2 Method for imaging the surrounding of a vehicle
US 20120158250 A1 Method for controlling function in vehicle, involves controlling function of vehicle based on retrieved object information by processing series of images
US 20110063445 A1 RUNWAY SURVEILLANCE SYSTEM AND METHOD
US 20100139995 A1 Mobile Robotic Vehicle
US 7579940 B2 Information display system for a vehicle
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/FRANK F HUANG/Primary Examiner, Art Unit 2485
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