DETAILED ACTION
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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 12/03/2025 has been entered.
Response to Arguments
Applicant's arguments filed 10/16/2025 have been fully considered but they are not persuasive.
In response to applicant's argument that the references do not teach detecting patrons, a recitation of the intended use of the claimed invention must result in a structural difference between the claimed invention and the prior art in order to patentably distinguish the claimed invention from the prior art. If the prior art structure is capable of performing the intended use, then it meets the claim.
In response to applicant's argument that Siminoff doesn’t teach changing colour of the bounding box on a GUI and doesn’t teach pillars, the test for obviousness is not whether the features of a secondary reference may be bodily incorporated into the structure of the primary reference; nor is it that the claimed invention must be expressly suggested in any one or all of the references. Rather, the test is what the combined teachings of the references would have suggested to those of ordinary skill in the art. See In re Keller, 642 F.2d 413, 208 USPQ 871 (CCPA 1981).
In response to applicant's argument that the examiner's conclusion of obviousness is based upon improper hindsight reasoning, it must be recognized that any judgment on obviousness is in a sense necessarily a reconstruction based upon hindsight reasoning. But so long as it takes into account only knowledge which was within the level of ordinary skill at the time the claimed invention was made, and does not include knowledge gleaned only from the applicant's disclosure, such a reconstruction is proper. See In re McLaughlin, 443 F.2d 1392, 170 USPQ 209 (CCPA 1971).
In response to applicant’s argument that there is no teaching, suggestion, or motivation to combine the references, the examiner recognizes that obviousness may be established by combining or modifying the teachings of the prior art to produce the claimed invention where there is some teaching, suggestion, or motivation to do so found either in the references themselves or in the knowledge generally available to one of ordinary skill in the art. See In re Fine, 837 F.2d 1071, 5 USPQ2d 1596 (Fed. Cir. 1988), In re Jones, 958 F.2d 347, 21 USPQ2d 1941 (Fed. Cir. 1992), and KSR International Co. v. Teleflex, Inc., 550 U.S. 398, 82 USPQ2d 1385 (2007).
Applicant’s arguments with respect to inter-person spacing have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 1,4-14 and 17-20 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention. No support can be found in the original specification of the instant patent application 18/325158 publication US 20230386309 A1 that “a classification service configured to determine whether the traversal is successful based on spatial thresholds including inter-patron spacing derived from the depth data”, “an inference service implementing a machine learning model executing on the edge device to adapt traversal thresholds over time”, “the inference service configured to update threshold spacing values in response to historical false positive or false negative traversal outcomes”, “the processor is configured to execute the microservices as containerized applications in an edge computing device co-located with the multi-sensor gateway”, “the machine learning model comprises a neural network trained on historical traversal classification data and bounding box measurements”, “the microservices are executed using containerized architecture on an edge computing device”, “the tracking service and classification service operate asynchronously using a shared data bus within the processor”, “a confidence score is associated with each traversal classification result and stored for model retraining”, “the stereo camera generates a disparity map used by the inference service to evaluate spatial compliance”.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1, 4-9, 13-14 are rejected under 35 U.S.C. 103 as being unpatentable over Carter et al. (US 20210287013 A1) in view of Siminoff (US 20180268674 A1) and NAGAI (US 20230230294 A1).
Regarding claims 1, 13. Carter discloses A multi-sensor gateway system for visual detection of carts passing through (figure 1C, [0045] an anti-theft system 400; [0106] The anti-theft system 400 can include additional sensors 460 to provide additional or different functionality), the system comprising:
a first pillar having a plurality of first sensors ([0065] The store can include a pair of conventional EAS (Electronic Article Surveillance) towers at the store exit);
a second pillar having a plurality of second sensors ([0065] The store can include a pair of conventional EAS (Electronic Article Surveillance) towers at the store exit);
a stereo camera configured to capture three-dimensional spatial image data of patrons traversing between the pillars (figure 4A, [0093] The system 400 includes a computer vision unit (CVU) 1000; [0097] The CVU 1000 can include a camera 410. The camera 410 can include a depth camera. The depth camera can include a stereo camera; [0106] The anti-theft system 400 can include additional sensors 460 to provide additional or different functionality, to provide three-dimensional (3D) imaging of the shopping basket 205 or merchandise);
a Wi-Fi* module on the first pillar configured for the pillars to communicate over Wi-Fi* ([0109] The CVU and the cloud platform 470 can communicate by an autonomous WAN gateway 465. The gateway 465 may be a virtual private network (VPN) over a municipal wireless (e.g., WiFi) network);
a platform computer server and processor configured to receive data and process the data ([0049] all of the access points (APs) communicate wirelessly with a central control unit (CCU), either directly or via intermediate access points. The central control unit may be implemented as a desktop computer or hardware server that includes a wireless transceiver card or which is wire-connected to an external transceiver unit. The CCU is generally responsible for collecting, storing and analyzing cart status information);
a display screen displaying output data on a user interface (UI) ([0038] displaying an alert or message; [0052] the CVU may send an alert to store personnel, actuate an alarm, communicate a warning that is displayed to the shopper by a display (or smart navigation module) on the basket);
a computing platform comprising a processor executing a plurality of microservices ([0039] The CVU or the CTU may perform (or communicate to another system to perform) computer vision analysis of the images from the camera 410), the microservices including:
a camera acquisition service configured to receive depth image data from the stereo camera (figure 4A, [0093] The system 400 includes a computer vision unit (CVU) 1000; [0097] The CVU 1000 can include a camera 410. The camera 410 can include a depth camera. The depth camera can include a stereo camera);
a tracking service configured to generate bounding boxes for the carts within the depth image stream and to track traversal paths and change colours as the carts enter or exit the multi-sensor gateway system ([0181] The image data can include annotations such as bounding boxes around the shopping basket or cart involved in the event, around merchandise in the cart, around the customer using the shopping basket, and so forth; [0188] The classified images may be annotated with bounding boxes around objects classified in the image (e.g., the cart, the basket, a shopper, etc.); [0164] Different colors or symbols can be used to distinguish paths of entering or exiting carts; [0004] identify shopping baskets in the image and to determine a load status of the basket; [0002] tracking the movement and status of movable shopping baskets);
a classification service ([0188] The classified images may be annotated with bounding boxes around objects classified in the image (e.g., the cart, the basket, a shopper, etc.; classifying objects including shoppers);
an inference service implementing a machine learning model executing on the edge device (figure 8, a processing pipeline for training a machine learning (ML) model; [0110] the image set can be labeled at block 472 to provide training data for updating the machine learning or computer vision object detection models used by the CVU; [0170] The object recognitions can additionally or alternatively be performed by a variety of machine learning algorithms. Some examples of machine learning algorithms can include artificial neural network algorithms (such as, for example, Perceptron), deep learning algorithms (such as, for example, Deep Boltzmann Machine, or deep neural network));
a UI rendering service configured to display bounding boxes on the UI screen and modify the color of each bounding box based on traversal classification ([0181] The image data can include annotations such as bounding boxes around the shopping basket or cart involved in the event, around merchandise in the cart, around the customer using the shopping basket, and so forth; [0164] Different colors or symbols can be used to distinguish paths of entering or exiting carts).
Siminoff discloses changing color to green if a person traversal through a multi-sensor gateway system is classified as successful, and to red if classified as unsuccessful ([0002]; [0146] These LED lights are capable of emitting different colors of light based on the severity of the threat the person may pose (e.g., a green color for authorized visitors, a red color for intruders, a yellow color for unidentified persons, etc.)).
NAGAI discloses an inter-person spacing is classified as inadequate using 3D spatial map/depth map ([0034] The three-dimensional space recognizer 22c maps an object detected by the object recognizer 22a in a three-dimensional space specified by the depth map acquired from the imaging device 10; [0070] the three-dimensional space recognizer 22c stores the detected frame picture; [0081] the object recognizer 22a can output a distance approach detection signal to the warning controller 25 when a distance between the persons is equal to or less than a set value in the frame picture).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the inventions of Carter, to apply a multi-sensor gateway system for visual detection of patrons, and to combine the inventions of Carter, Siminoff and NAGAI, to change the color of the bounding box on the UI display screen to indicate whether a traversal is successful based on inter-person spacing, in order to prevent intruders.
Regarding claim 4. Carter discloses The system of Claim 1 wherein the micro-services is selected from a list consisting of a magnetic sensor acquisition service ([0068] one or more magnetic markers or strips (MAG) may optionally be provided. Each magnetic strip can have a unique magnetic pattern that can be sensed by an optional magnetic sensor), a magnetic sensor classification service ([0068] Each magnetic strip can have a unique magnetic pattern that can be sensed by an optional magnetic sensor. The magnetic markers thus serve as magnetic bar codes that identify specific locations (the magnetic markers are classified based on locations)), an inference server service (figure 8, a processing pipeline for training a machine learning (ML) model; [0110] the image set can be labeled at block 472 to provide training data for updating the machine learning or computer vision object detection models used by the CVU), a screen controller service ([0047] a display unit), a sound indicator controller service ([0084] an indicator 335 (e.g., visual and/or audible) to provide a notification to the user), a camera acquisition service (figure 4A, [0093] The system 400 includes a computer vision unit (CVU) 1000; [0097] The CVU 1000 can include a camera 410. The camera 410 can include a depth camera. The depth camera can include a stereo camera).
Siminoff discloses an API service ([0080] a backend API (application programming interface) 120).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the inventions of Carter and Siminoff, to include an API service in the system, in order to better prevent intruders (Siminoff [0090] one or more API servers may receive (e.g., from the A/V recording and communication device 100) captured images and/or biometric data of a person at an entry of a property and use the received images/data to determine whether the person poses a threat or not).
Regarding claim 5. See the analysis in claim 1.
Regarding claim 6. See the analysis in claim 1.
Regarding claim 7. See the analysis in claim 1.
Regarding claim 8. Carter discloses displaying alert messages ([0084] an indicator 335 (e.g., visual and/or audible) to provide a notification to the user. The indicator may include a light (e.g., a light emitting diode (LED)) that illuminates or flashes as a notification to the user. The indicator may include audible alerts or notifications).
Regarding claim 9. Carter discloses emitting an audible alert ([0084] an indicator 335 (e.g., visual and/or audible) to provide a notification to the user. The indicator can include a speaker to output the audible notification; [0056] the CCU or CVU may be configured to activate an audible alarm or a video camera upon detecting an unauthorized exit event).
Regarding claim 14. Carter discloses The method of Claim 13 further comprising the step of transmitting the data to operations and to security personnel ([0094] the remote node may be accessible (e.g., via a web browser) by authorized store personnel who can view statistics about exit events (e.g., theft situations) or images or video of exit events (e.g., video of shoppers attempting pushout theft)).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to XIAOLAN XU whose telephone number is (571)270-7580. The examiner can normally be reached Mon. to Fri. 9am-5pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, SATH V. PERUNGAVOOR can be reached on (571) 272-7455. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/XIAOLAN XU/ Primary Examiner, Art Unit 2488