DETAILED ACTIONS
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 .
Response to Amendment
This office action is in response to the amendments/arguments submitted by the Applicant(s) on 01/19/2026.
Status of the Claims
Claims 1, 3-11, 13-20 are pending.
Claims 1, and 11 are amended.
Claims 2, and 12 are cancelled.
Response to Arguments
Rejections under 35 U.S.C § 102(a)(1):
Applicant argument in the Remarks filed on 01/19/2026 with respect to the rejection(s) of Claims under 35 U.S.C 102(a)(1) has been considered, and are moot because the amendment has necessitated a new ground of rejections. The new rejections are set forth below.
Claim Rejections - 35 USC § 103
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.
Claims 1, 3-11, 13-20 are rejected under 35 U.S.C. 103 as being unpatentable over by Sakagami Akira (JP 6214494 B2, hereinafter Sakagami, previously cited) and in view of Zhou Wu (CN 115955490 A., hereinafter Zhou, a translation preview copy combined with original copy uploaded by the examiner.).
Regarding Claim 1, Sakagami teaches,
A device (Sakagami, Figure 1, user identification device 1) comprising:
a communication interface configured to communicate with cameras monitoring a given area (Sakagami, Figure 1, the imaging device 2/ camera, the display device 4, page 3, bottom paragraph, The image acquisition unit 12 is connected to the imaging device 2 using an interface corresponding to the imaging device 2. (Sakagami, page 4, top paragraph, in a room or the like where only employees of the facility can enter, and processing by the user identification
device 1 is performed); and;
a controller (Sakagami, Figure 2 see below, controlling unit 10) configured to:
maintain an attendee list of persons located within the given area using images received from the cameras via the communication interface, wherein persons appearing in the images are placed on the attendee list; (Sakagami, Figure 1, page 2, upper paragraph, obtained feature quantity with identification information and storing them in a storage device In the user identification device for identifying a person who uses the facility. Figure 6, Page 4, middle paragraph, “the control unit 10 sets the number of visitors in the period until the process is ended to an initial value (zero) (step S101). The control unit 10 reads the image data of the latest frame image into the temporary storage unit 16 from the image data of the plurality of images stored in the image memory by the image acquisition unit 12 (step S102). The control unit 10 extracts a person area in the image based on the read image data (step S103), and calculates a feature amount from the extracted person area (step S104).” NOTE: the number of visitors with identification of employee associated with the facility stored is interpreted as “list of persons of interest”):
categorize, using the images received from the cameras, the POIs into given categories based on all of: whether a POI is being monitored by the cameras, as determined from the POI appearing or not appearing in the images from the cameras after being added to the attendee list based on appearing in previously received images (Sakagami, Page 2, middle paragraph, A user identification device according to the present invention includes an acquisition unit that sequentially acquires image data of a plurality of captured images that are captured in time series by an imaging device installed in a specific place of a facility, Extraction means for extracting a person area from an image based on each of the image data, means for obtaining a feature quantity of the extracted person area, and means for associating the obtained feature quantity with identification information and storing them in a storage device In the user identification device for identifying a person who uses the facility”. Page 3, middle paragraph, “the state information corresponding to the person who has entered is updated”);
whether a location associated with the POI is determined or not determined; and, the location associated with the POI, when determined (Sakagami, Page 2, middle paragraph, “means for obtaining a feature quantity of the extracted person area, and means for associating the obtained feature quantity with identification information and storing them in a storage device In the user identification device for identifying a person who uses the facility” NOTE: person area/location feature is extracted and stored with the persons identification information);
cause, via the communication interface, one or more respective electronic actions to occur in relation to respective POIs associated with a given category into which the respective POIs are categorized; and cause the one or more respective electronic actions associated with the designated highest risk category to occur in relation to the portion of the POIs that are categorized into the designated highest risk category. (Sakagami, page 7,” In the present invention, when the state information associated with the feature amount of the person who has entered the site indicates a predetermined usage state at a predetermined time point, it is determined that an unauthorized entry has been made and the feature
amount is It is stored as the feature quantity of the person to be monitored. Thereby, when a person having a feature amount stored as a monitoring target is imaged next, it is recognized that a person related to an unauthorized entry / exit has entered, and notification is made. Thereby, it becomes possible to prevent repeated illegal entry and exit”).
categorize a portion of the POI s into a designated highest risk category by determining that the portion of the POIs are not being monitored by the cameras after previously being monitored by the cameras due to movement of the portion of the POIs (Sakagami, page 4, bottom paragraph, “FIG. 9 shows the transition of the tracking information of the person ID “0003” in FIG. The person with the person ID “0003” enters the imaging range of the imaging device 2 at 10:00 and is detected as a new person based on the captured image, thereby indicating that the person ID “0003” is “visitor”. Tracking information associated with state information is stored every time the person with the person ID “0003” moves, the tracking information is updated with the section ID specified according to the position of the person area in the captured image. At 10:07, when the specified section ID is “before counter”, it is detected that the reception procedure with the employee has been performed, and the status information is a valid “facility user” after the reception is completed. It has been updated to state information indicating that. At 10:08, the person with the person ID “0003” is not shown in the captured image and the person area is not extracted, but the state information indicates “facility user”. It is presumed that the section ID is updated as “inside the facility”. Thereafter, the tracking information of the person with the person ID “0003” is detected that the reception procedure with the employee is performed when the section ID specified at 12:02 is “before counter”, and the status information Is updated to status information indicating that it is a “scheduled to leave” after completion of reception. Thereafter, when the person with the person ID “0003” leaves and becomes invisible from the imaging range, the section ID is updated to “outside facility. NOTE: when the image does not have a POI, the tracking information of the person is categorized and updated the system, until the person has left the facility and accounted for. Any movement of a person is tracked, this movement could be for any reason. If a public safety event occurs the movement of the person will be recorded based on the image. It is an application choice.).
Sakagami teaches generating a current list of POI and updated every time a person entered based on the image.
Sakagami is silent on determining that the given area meets a given condition, wherein the given condition comprises a public-safety incident occurring in the given area: use a current version of the attendee list, that represents persons within the given area when the public-safety incident occurs, to generate a person-of-interest (POI) list of POIs within the given area when the public-safety incident occurs.
However, Zhou teaches determining that the given area meets a given condition, wherein the given condition comprises a public-safety incident occurring in the given area (Zhou, Page 2, top paragraph, “The invention belongs to the field of intelligent building monitoring technology and rescue system monitoring, and particularly relates to a personnel number detector and a personnel number detection method NOTE: personnel number detected in real time at the time of fire or public safety event, see abstract l), : use a current version of the attendee list, that represents persons within the given area when the public-safety incident occurs to generate a person-of-interest (POI) list of POIs within the given area when the public-safety incident occurs (Zhou, page 2, middle paragraph, in particular to a personnel number detector and a personnel number detection method. an indoor count detector configured to detect the presence of a person and to monitor a change in the number of persons in the room” page 6, bottom paragraph, “an indoor counting detector 1 configured to detect the presence of people and monitor the number change of the number of people in the room, perform data storage and send data to an indoor control module, a corridor detector, a floor display and a control center for the detected real-time number change, and perform data analysis on an in-and-out moving object,”).
It would have been obvious to a person having ordinary skill in the art before the effective filing date to modify Sakagami’s method for determining POI list to incorporate the person number detection method as taught by Zhou, obtaining real time number of people present in the facility when a public safety event such as fire has occurred using imaged, wireless, visual and statistical analysis of data with the benefit of an accurate determination of POI’s (Zhou, abstract). It would have been obvious to a person of ordinary skill to include the well-known Zhou method of identifying persons present in a facility using the existing list of POI’s list and determining the change in the number of people present after the public safety along with Sakagami method, in order to yield the predicted results of generating accurate POI list, yet with higher accuracy (KSR).
Regarding claim 3, combination of Sakagami and Zhou teaches the device of
claim 1,
Sakagami further teaches further teaches wherein the one or more respective electronic actions associated with the designated highest risk category comprise initiating one or more calls to one or more communication devices associated with communication addresses registered in association with the portion of the POIs Is that are categorized into the designated highest risk category.(Sakagami, Figures 6, page 10, bottom paragraph, The control unit 10 determines whether or not the feature amount corresponding to the selected person corresponds to the feature amount included in the employee information 111 (step S114). If the control unit 10 determines in step S114 that the feature does not correspond (S114: NO), the control unit 10 determines whether the feature amount corresponding to the selected person corresponds to the feature amount included in the specific monitoring information 113. Is a monitoring target person (step S115. When it is determined in step S115 that it is not a monitoring target (S115: NO), the control unit 10 determines whether a predetermined reception procedure by the selected person has been detected (step S116). Page 11, If it is determined in step S119 that fraud has been detected (S119: YES), the control unit 10 adds information indicating that notification is to be made to the tracking information (step S120), and the display unit 14 and the notification unit 15 Then, the display device 4 and the notification device 5 are notified by image and voice (step S121)”).
Regarding claim 4, combination of Sakagami and Zhou teaches the device of
claim 1,
Sakagami further teaches wherein the one or more respective electronic actions associated with the designated highest risk category comprise connecting one or more public-safety answering point (PSAP) calls from one or more registered communication addresses, associated with the portion of the POIs that are categorized into the designated highest risk category, to one or more communication devices associated with one or more first responders (Sakagami, Page 8, upper paragraph, “Further, in the example shown in FIG. 1, the user identification device 1 is connected to a moving image recording device 3, a display device 4, and a notification device 5. As a result, the user identification device 1 automatically detects unauthorized use according to the content of the trend indicated by the status information of each person, and causes the display device 4 and the notification device 5 to
notify the presence or content of unauthorized use. To the employee or the like, or the moving image data captured by the imaging device 2 is recorded in the moving image recording device 3. By automatically performing notification or recording, employees can immediately take appropriate measures against unauthorized use”.).
Regarding claim 5, combination of Sakagami and Zhou teaches the device of
claim 1,
Sakagami further teaches wherein the one or more respective electronic actions associated with the designated highest risk category comprise providing information collected during one or more public-safety answering point (PSAP) calls, from one or more registered communication addresses, associated with the portion of the POIs, that are categorized into the designated highest risk category, to one or more communication devices associated with one or more first responders (Sakagami, Page 11,Figure 7, bottom paragraph, “If it is determined in step S119 that fraud has been detected (S119: YES), the control unit 10 adds information indicating that notification is to be made to the tracking information (step S120), and the display unit 14 and the notification unit 15 Then, the display device 4 and the
notification device 5 are notified by image and voice (step S121). The control unit 10 further retains the tracking information corresponding to the fraud detection condition in the storage unit 11 as the specific monitoring information 113 (step S122), and advances the processing to the next step S124. Note that the process of step S122 may be omitted depending on the contents of the fraud detection condition. For example, in the tracking information of the selected person, the state information indicates a state where the reception procedure has not
been completed, but the associated section ID is near the facility, the process of step S122 May be omitted. This is because such a user should be notified in order to prompt the reception procedure”.).
Regarding claim 6, combination of Sakagami and Zhou teaches the device of
claim 1,
Sakagami further teaches wherein the controller (Sakagami, Figure 2, controlling unit 10) is further configured to:
categorize a portion of the POIs into a designated intermediate risk category by determining that: the portion of the POIs that are categorized into the designated highest risk category, are being monitored by the cameras (Sakagami, Figure 6, Page 10, bottom paragraph, The control unit 10 determines whether or not the feature amount corresponding to the selected person corresponds to the feature amount
included in the employee information 111 (step S114). If the control unit 10 determines in step S114 that the feature does not correspond (S114: NO), the control unit 10 determines whether the feature amount corresponding to the selected person corresponds to the feature amount included in the specific monitoring information 113. Is a monitoring target person (step S115). When it is determined in step S115 that it is not a monitoring target (S115: NO), the control unit 10 determines whether a predetermined reception procedure by the selected person has been detected (step S116)”); and respective locations of the portion of the POIs within the given area comprise designated intermediate risk locations; and cause the one or more respective electronic actions associated with the designated intermediate risk category to occur in relation to the portion of the POIs. (Sakagami, page 11, top paragraph, “in step S116, the control unit 10 determines, for example, the section where the user specified in step S105 exists, the section where the employee based on the tracking information of the current employee exists, the selected person, and any employee It is determined whether the user corresponding to the tracking information has performed a reception procedure based on the distance between members or the history of the tracking information. Specifically, the section identified in step S105, that is, the selected person exists in front of the counter, and any employee exists in the counter”).
Regarding claim 7, combination of Sakagami and Zhou teaches the device of claim 1,
Sakagami further teaches wherein the controller (Sakagami, Figure 2, controlling unit 10) is further configured to: categorize a further portion of the POIs into a designated lowest risk category by determining that: the portion of the POIs are being monitored by the cameras (Sakagami, Page 11, middle paragraph, the control unit 10 determines that the selected person exists in front of the counter and that a predetermined member card, a predetermined key holder, etc. are reflected in the vicinity of the selected person in the image being acquired. It may be determined that the reception procedure has been performed. Further, the control unit 10 performs an acceptance procedure when the selected person exists in front of the counter for a predetermined period (for example, 3 minutes) or longer based on the section ID history of the tracking information of the selected person”); and
respective locations of the portion of the POIs comprise designated lowest risk locations; and cause the one or more respective electronic actions associated with the designated lowest risk category to occur in relation to the portion of the POIs that are categorized into the designated highest risk category, (Sakagami, page 4, bottom paragraph, FIG. 9 shows the transition of the tracking information of the person ID “0003”.In FIG.9 The person with the person ID “0003” enters the imaging range of the imaging device 2 at 10:00 and is detected as a new person based on the captured image, thereby indicating that the person ID “0003” is “visitor”. Tracking information associated with state information is stored. Thereafter, every time the person with the person ID “0003” moves, the tracking information is updated with the section ID specified according to the position of the person area in the captured image. Page 11, middle paragraph, “In this case, when updating the section ID of the selected person, the control unit 10 adds the time information when it is first detected before the counter to the tracking information as the remark information, thereby adding the stay time. It is possible to estimate. Further, the control unit 10 determines whether or not the payment procedure is completed by identifying the operations such as money transfer on the counter, credit card presentation, sign entry, PIN input, money storage, etc. based on the image. Then, it may be determined whether or not the acceptance procedure has been performed”. NOTE: additional information about the person is checked, time stamp and confirmed that the person is a “facility user” (See page 4, bottom paragraph) and not high risk and entered the facility through front counter.).
Regarding claim 8, combination of Sakagami and Zhou teaches the device of
claim 1,
Sakagami further teaches wherein the controller (Sakagami, Figure 2, controlling unit 10), is further configured to: recategorize, using the images received from the cameras
a given POI from a first category of the given categories to a second category of the given categories based on one or more of: the given POI changing locations, as determined from the images; or a monitoring status the given POI changing, as determined from the images. (Sakagami, Figure 9, page 4, bottom paragraph, FIG. 9 shows the transition of the tracking information of the person ID “0003” in FIG. The person with the person ID “0003” enters the imaging range of the imaging device 2 at 10:00 and is detected as a new person based on the captured image, thereby indicating that the person ID “0003” is “visitor”. Tracking information associated with state information is stored. Thereafter, every time the person with the person ID “0003” moves, the tracking information is updated with the section ID specified according to the position of the person area in the captured image. At 10:07, when the specified section ID is “before counter”, it is detected that the reception procedure with the employee has been performed, and the status information is a valid “facility user” after the reception is completed. It has been updated to state information indicating that. At 10:08, the person with the person ID “0003” is not shown in the captured image and the person area is not extracted, but the state information indicates “facility user”. It is presumed that the section ID is updated as “inside the facility”. Thereafter, the tracking information of the person with the person ID “0003” is detected that the reception procedure with the employee is performed when the section ID specified at 12:02 is “before counter”, and the status information Is updated to status information indicating that it is a “scheduled to leave” after completion of reception. Thereafter, when the person with the person ID “0003” leaves and becomes invisible from the imaging range, the section ID is updated to “outside facility”.)
Regarding claim 9, Sakagami teaches the device of claim 1,
Sakagami further teaches wherein a subset of the cameras are located at access points to the given area(Sakagami, figure 1,figure 5, camera 2), and the controller is further configured to: maintain the attendee list , using respective images received from the subset of the cameras indicating respective persons entering or exiting the given area via the access points (Sakagami, Figure 5, Page 8 bottom paragraph, “The storage unit 11 stores a control program 1P. Information that the control unit 10 refers to is stored in the storage unit 11 in advance. For example, employee information 111 (refer to FIG. 5) including employee feature quantities registered in advance”. Page 9 top paragraph. The storage unit 11 also includes tracking information in which identification information (person ID) of a person recognized by the process of the control unit 10 is associated with state information indicating a usage state according to a trend of each person to be tracked. Is stored in the database (Data Base) as the tracking information group 114. The tracking information group 114 in the storage unit 11 is appropriately updated by the processing of the control unit 10”).
Regarding claim 10, Sakagami teaches the device of claim 1,
Sakagami further teaches wherein the controller has access to a memory storing registered images of the persons and respective locations of the cameras and the controller is further configured to:
determine whether the POI is being monitored by the cameras by comparing the images from the cameras with the registered images (Sakagami, page 8, middle paragraph, The user identification device 1 includes a control unit 10, a storage unit 11, an image acquisition unit 12, a recording control unit 13, a display unit 14, a notification unit 15, and a temporary storage unit 16); and determine the location of the POI using a respective location, as stored at the memory, of a camera that provided an image in which the POI was detected using the registered images. Sakagami, Figure 5, Page 8 bottom paragraph, “The storage unit 11 stores a control program 1P. Information that the control unit 10 refers to is stored in the storage unit 11 in advance. For example, employee information 111 (refer to FIG. 5) including employee feature quantities registered in advance”. Page 9 top paragraph. The storage unit 11 also includes tracking information in which identification information (person ID) of a person recognized by the process of the control unit 10 is associated with state information indicating a usage state according to a trend of each person to be tracked. Is stored in the database (Data Base) as the tracking information group 114. The tracking information group 114 in the storage unit 11 is appropriately updated by the processing of the control unit 10”).
Regarding claim 11,
A method comprising:
maintaining, via a computing device, Sakagami, figure 2 (see modified figure 2 below), control unit 10, 1P control program),
an attendee list (Figure 2, employee information 111) of persons located within a given area (Figure 2, Tracking information 114) using images received from cameras monitoring the given area (figure 2, camera 2, image acquisition unit 12); wherein persons appearing in the images are placed on the attendee list(Sakagami Figure 6, Page 10, upper and middle paragraph, the control unit 10 sets the number of visitors in the period until the process is ended to an initial value (zero) (step S101). The control unit 10 reads the image data of the latest frame image into the temporary storage unit 16 from the image data of the plurality of images stored in the image memory by the image acquisition unit 12 (step S102). The control unit 10 extracts a person area in the image based on the read image data (step S103), and calculates a feature amount from the extracted person area (step S104).;
categorizing, via the computing device, using the images received from the cameras, the POIs into given categories based on: whether a POI is being monitored by the cameras, as determined from the POI appearing or not appearing in the images from the cameras after being added to the attendee list based on appearing in previously received images; whether a location associated with the POI is determined or not determined; and, the location associated with the POI, when determined Sakagami, Figure 6, Page 10, middle paragraph, “Based on the position and size in which the person is photographed, the control unit 10 identifies the section where the photographed person exists based on the area management information 112 (step S105). The control unit 10 selects one person among the reflected persons (step S106). The control unit 10 determines whether or not a new person has been detected based on whether or not the feature amount corresponding to the selected person matches the feature amount included in the tracking information already stored in the tracking information group 114. Judgment is made (step S107)”);
categorizing, via the computing device, a portion of the POIs into a designated highest risk category by determining that the portion of the POIs are not being monitored by the cameras after previously being monitored by the cameras due to movement of the portion of the POIs; causing, via the computing device, one or more respective electronic actions to occur in relation to respective POIs associated with a given category into which the respective POIs are categorized(Sakagami, page 4, bottom paragraph, “FIG. 9 shows the transition of the tracking information of the person ID “0003” in FIG. The person with the person ID “0003” enters the imaging range of the imaging device 2 at 10:00 and is detected as a new person based on the captured image, thereby indicating that the person ID “0003” is “visitor”. Tracking information associated with state information is stored. Thereafter, every time the person with the person ID “0003” moves, the tracking information is updated with the section ID specified according to the position of the person area in the captured image. At 10:07, when the specified section ID is “before counter”, it is detected that the reception procedure with the employee has been performed, and the status information is a valid “facility user” after the reception is completed. It has been updated to state information indicating that. At 10:08, the person with the person ID “0003” is not shown in the captured image and the person area is not extracted, but the state information indicates “facility user”. It is presumed that the section ID is updated as “inside the facility”. Thereafter, the tracking information of the person with the person ID “0003” is detected that the reception procedure with the employee is performed when the section ID specified at 12:02 is “before counter”, and the status information Is updated to status information indicating that it is a “scheduled to leave” after completion of reception. Thereafter, when the person with the person ID “0003” leaves and becomes invisible from the imaging range, the section ID is updated to “outside facility”. NOTE: when the image does not have a POI, the tracking information of the person is categorized and updated the system, until the person has left the facility and accounted for. Any movement of a person is tracked, this movement could be for any reason. If a public safety event occurs the movement of the person will be recorded based on the image. It is an application choice);
and causing, via the computing device, the one or more respective electronic actions associated with the designated highest risk category to occur in relation the portion of the POIs that are categorized into the designated highest risk category Sakagami, page 7, “In the present invention, when the state information associated with the feature amount of the person who has entered the site indicates a predetermined usage state at a predetermined time point, it is determined that an unauthorized entry has been made and the feature amount is It is stored as the feature quantity of the person to be monitored. Thereby, when a person having a feature amount stored as a monitoring target is imaged next, it is recognized that a person related to an unauthorized entry / exit has entered, and notification is made. Thereby, it becomes possible to prevent repeated illegal entry and exit”).
Sakagami teaches generating a current list of POI and updated every time a person entered based on the image.
Sakagami is silent on in response to determining, via the computing device, that the given area meets a given condition, wherein the given condition comprises a public-safety incident occurring in the given area: using, via the computing device, a current version of the attendee list, that represents persons within the given area when the public-safety incident occurs, to generate a person-of-interest (POI) list of POIs within the given area when the public-safety incident occurs;
However, Zhou teaches determining that the given area meets a given condition, wherein the given condition comprises a public-safety incident occurring in the given area (Zhou, Page 2, top paragraph, “The invention belongs to the field of intelligent building monitoring technology and rescue system monitoring, and particularly relates to a personnel number detector and a personnel number detection method NOTE: personnel number detected in real time at the time of fire or public safety event, see abstract l), : use a current version of the attendee list, that represents persons within the given area when the public-safety incident occurs to generate a person-of-interest (POI) list of POIs within the given area when the public-safety incident occurs (Zhou, page 2, middle paragraph, in particular to a personnel number detector and a personnel number detection method. an indoor count detector configured to detect the presence of a person and to monitor a change in the number of persons in the room” page 6, bottom paragraph, “an indoor counting detector 1 configured to detect the presence of people and monitor the number change of the number of people in the room, perform data storage and send data to an indoor control module, a corridor detector, a floor display and a control center for the detected real-time number change, and perform data analysis on an in-and-out moving object,”).
It would have been obvious to a person having ordinary skill in the art before the effective filing date to modify Sakagami’s method for determining POI list to incorporate the person number detection method as taught by Zhou, obtaining real time number of people present in the facility when a public safety event such as fire has occurred using imaged, wireless, visual and statistical analysis of data with the benefit of an accurate determination of POI’s (Zhou, abstract). It would have been obvious to a person of ordinary skill to include the well-known Zhou method of identifying persons present in a facility using the existing list of POI’s list and determining the change in the number of people present after the public safety along with Sakagami method, in order to yield the predicted results of generating accurate POI list, yet with higher accuracy (KSR).
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Figure 2, Sakagami with symbols translated.
Regarding Claim 13, Sakagami teaches the method of claim 11,
Sakagami further teaches further teaches wherein the one or more respective electronic actions associated with the designated highest risk category comprise initiating one or more calls to one or more communication devices associated with communication addresses registered in association with the portion of the POIs that are categorized into the designated highest risk category, (Sakagami, Figures 6, page 10, bottom paragraph, The control unit 10 determines whether or not the feature amount corresponding to the selected person corresponds to the feature amount included in the employee information 111 (step S114). If the control unit 10 determines in step S114 that the feature does not correspond (S114: NO), the control unit 10 determines whether the feature amount corresponding to the selected person corresponds to the feature amount included in the specific monitoring information 113. Is a monitoring target person (step S115. When it is determined in step S115 that it is not a monitoring target (S115: NO), the control unit 10 determines whether a predetermined reception procedure by the selected person has been detected (step S116). Page 11, If it is determined in step S119 that fraud has been detected (S119: YES), the control unit 10 adds information indicating that notification is to be made to the tracking information (step S120), and the display unit 14 and the notification unit 15 Then, the display device 4 and the notification device 5 are notified by image and voice (step S121). “)
Regarding Claim 14, Sakagami teaches the method of claim 11,
Sakagami further teaches wherein the one or more respective electronic actions associated with the designated highest risk category comprise connecting one or more public-safety answering point (PSAP) calls from one or more registered communication addresses, associated with the portion of the POIs that are categorized into the designated highest risk category, to one or more communication devices associated with one or more first responders. (Sakagami, Page 8, upper paragraph, “Further, in the example shown in FIG. 1, the user identification device 1 is connected to a moving image recording device 3, a display device 4, and a notification device 5. As a result, the user identification device 1 automatically detects unauthorized use according to the content of the trend indicated by the status information of each person, and causes the display device 4 and the notification device 5 to
notify the presence or content of unauthorized use. To the employee or the like, or the moving image data captured by the imaging device 2 is recorded in the moving image recording device 3. By automatically performing notification or recording, employees can immediately take appropriate measures against unauthorized use”.).
Regarding Claim 15, Sakagami teaches the method of claim 11,
Sakagami further teaches wherein the one or more respective electronic actions associated with the designated highest risk category comprise providing information collected during one or more public-safety answering point (PSAP) calls, from one or more registered communication addresses, associated with the portion of the POIs, that are categorized into the designated highest risk category, to one or more communication devices associated with one or more first responders (Sakagami, Page 11,Figure 7, bottom paragraph, “If it is determined in step S119 that fraud has been detected (S119: YES), the control unit 10 adds information indicating that notification is to be made to the tracking information (step S120), and the display unit 14 and the notification unit 15 Then, the display device 4 and the
notification device 5 are notified by image and voice (step S121). The control unit 10 further retains the tracking information corresponding to the fraud detection condition in the storage unit 11 as the specific monitoring information 113 (step S122), and advances the processing to the next step S124. Note that the process of step S122 may be omitted depending on the contents of the fraud detection condition. For example, in the tracking information of the selected person, the state information indicates a state where the reception procedure has not
been completed, but the associated section ID is near the facility, the process of step S122 May be omitted. This is because such a user should be notified in order to prompt the reception procedure”.).
Regarding Claim 16, Sakagami teaches the method of claim 11,
Sakagami further teaches, further comprising: categorizing a further portion of the PO Is into a designated intermediate risk category by determining that: the further portion of the PO Is are being monitored by the cameras; (Sakagami, Figure 6, Page 10, bottom paragraph, The control unit 10 determines whether or not the feature amount corresponding to the selected person corresponds to the feature amount
included in the employee information 111 (step S114). If the control unit 10 determines in step S114 that the feature does not correspond (S114: NO), the control unit 10 determines whether the feature amount corresponding to the selected person corresponds to the feature amount included in the specific monitoring information 113. Is a monitoring target person (step S115). When it is determined in step S115 that it is not a monitoring target (S115: NO), the control unit 10 determines whether a predetermined reception procedure by the selected person has been detected (step S116)”); and respective locations of the portion of the POIs within the given area comprise designated intermediate risk locations; and cause the one or more respective electronic actions associated with the designated intermediate risk category to occur in relation to the portion of the POIs. (Sakagami, page 11, top paragraph, “in step S116, the control unit 10 determines, for example, the section where the user specified in step S105 exists, the section where the employee based on the tracking information of the current employee exists, the selected person, and any employee It is determined whether the user corresponding to the tracking information has performed a reception procedure based on the distance between members or the history of the tracking information. Specifically, the section identified in step S105, that is, the selected person exists in front of the counter, and any employee exists in the counter”).
Regarding Claim 17, Sakagami teaches the method of claim 11,
Sakagami further teaches further comprising:
categorizing a further portion of the PO Is into a designated lowest risk category
by determining that: the further portion of the PO Is are being monitored by the cameras; (Sakagami, Page 11, middle paragraph, the control unit 10 determines that the selected person exists in front of the counter and that a predetermined member card, a predetermined key holder, etc. are reflected in the vicinity of the selected person in the image being acquired. It may be determined that the reception procedure has been performed. Further, the control unit 10 performs an acceptance procedure when the selected person exists in front of the counter for a predetermined period (for example, 3 minutes) or longer based on the section ID history of the tracking information of the selected person”) ; and
respective locations of the portion of the POIs comprise designated lowest risk locations; and cause the one or more respective electronic actions associated with the designated lowest risk category to occur in relation to the portion of the POIs that are categorized into the designated highest risk category, (Sakagami, page 4, bottom paragraph, FIG. 9 shows the transition of the tracking information of the person ID “0003”.In FIG.9 The person with the person ID “0003” enters the imaging range of the imaging device 2 at 10:00 and is detected as a new person based on the captured image, thereby indicating that the person ID “0003” is “visitor”. Tracking information associated with state information is stored. Thereafter, every time the person with the person ID “0003” moves, the tracking information is updated with the section ID specified according to the position of the person area in the captured image. Page 11, middle paragraph, “In this case, when updating the section ID of the selected person, the control unit 10 adds the time information when it is first detected before the counter to the tracking information as the remark information, thereby adding the stay time. It is possible to estimate. Further, the control unit 10 determines whether or not the payment procedure is completed by identifying the operations such as money transfer on the counter, credit card presentation, sign entry, PIN input, money storage, etc. based on the image. Then, it may be determined whether or not the acceptance procedure has been performed”. NOTE: additional information about the person is checked, time stamp and confirmed that the person is a “facility user” (See page 4, bottom paragraph) and not high risk and entered the facility through front counter.).
Regarding Claim 18, Sakagami teaches the method of claim 11,
Sakagami further teaches further comprising:
recategorizing, using the images received from the cameras, a given POI from a
first category of the given categories to a second category of the given categories based
on one or more of: the given POI changing locations, as determined from the images; or a monitoring status the given POI changing, as determined from the images. (Sakagami, Figure 9, page 4, bottom paragraph, FIG. 9 shows the transition of the tracking information of the person ID “0003” in FIG. The person with the person ID “0003” enters the imaging range of the imaging device 2 at 10:00 and is detected as a new person based on the captured image, thereby indicating that the person ID “0003” is “visitor”. Tracking information associated with state information is stored. Thereafter, every time the person with the person ID “0003” moves, the tracking information is updated with the section ID specified according to the position of the person area in the captured image. At 10:07, when the specified section ID is “before counter”, it is detected that the reception procedure with the employee has been performed, and the status information is a valid “facility user” after the reception is completed. It has been updated to state information indicating that. At 10:08, the person with the person ID “0003” is not shown in the captured image and the person area is not extracted, but the state information indicates “facility user”. It is presumed that the section ID is updated as “inside the facility”. Thereafter, the tracking information of the person with the person ID “0003” is detected that the reception procedure with the employee is performed when the section ID specified at 12:02 is “before counter”, and the status information Is updated to status information indicating that it is a “scheduled to leave” after completion of reception. Thereafter, when the person with the person ID “0003” leaves and becomes invisible from the imaging range, the section ID is updated to “outside facility”).
Regarding Claim 19, Sakagami teaches the method of claim 11,
Sakagami further teaches wherein a subset of the cameras are located at access points to the given area (Sakagami, figure 1, figure 5, camera 2),, and the method further comprises: maintaining the attendee list using respective images received from the subset of the cameras indicating respective persons entering or exiting the given area via the access points. (Sakagami, Figure 5, Page 8 bottom paragraph, “The storage unit 11 stores a control program 1P. Information that the control unit 10 refers to is stored in the storage unit 11 in advance. For example, employee information 111 (refer to FIG. 5) including employee feature quantities registered in advance”. Page 9 top paragraph. The storage unit 11 also includes tracking information in which identification information (person ID) of a person recognized by the process of the control unit 10 is associated with state information indicating a usage state according to a trend of each person to be tracked. Is stored in the database (Data Base) as the tracking information group 114. The tracking information group 114 in the storage unit 11 is appropriately updated by the processing of the control unit 10”.).
Regarding Claim 20, Sakagami teaches the method of claim 11,
Sakagami further teaches wherein the computing device has access to
a memory storing registered images of the persons and respective locations of the
cameras, and the method further comprises: determining whether the POI is being monitored by the cameras by comparing the images from the cameras with the registered images (Sakagami, page 8, middle paragraph, The user identification device 1 includes a control unit 10, a storage unit 11, an image acquisition unit 12, a recording control unit 13, a display unit 14, a notification unit 15, and a temporary storage unit 16.);; and determining the location of the POI using a respective location, as stored at the memory, of a camera that provided an image in which the POI was detected using the registered images. (Sakagami, Figure 5, Page 8 bottom paragraph, “The storage unit 11 stores a control program 1P. Information that the control unit 10 refers to is stored in the storage unit 11 in advance. For example, employee information 111 (refer to FIG. 5) including employee feature quantities registered in advance”. Page 9 top paragraph. The storage unit 11 also includes tracking information in which identification information (person ID) of a person recognized by the process of the control unit 10 is associated with state information indicating a usage state according to a trend of each person to be tracked. Is stored in the database (Data Base) as the tracking information group 114. The tracking information group 114 in the storage unit 11 is appropriately updated by the processing of the control unit 10”.).
Conclusion
Citation of Pertinent Prior Art
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Revaud et al. (US 2020/0110966 A1) recites “A method for detecting a point of interest (POI) change in a pair of inputted POI images. A first processor of the method: generates triplets of training POI images using a base of training POI images and trains a convolutional neural network (CNN) of three-stream Siamese type based on the triplets of training POI images. A second processor of the method: computes, for each image of the pair of inputted POI images, a descriptor of that image using a stream of the CNN of three-stream Siamese type, computes a similarity score based on the descriptors of the images of the pair of inputted POI images using a similarity score function, and selectively detects the POI change based on the similarity score. A third processor of the method generates the base of training POI images to include an initial set of POI images and a set of synthetic POI images” (Abstract).
ZHANG JINJIANG (CN 114971536 A) discloses “The invention discloses an intelligent prevention and control system for an intelligent community, and belongs to the technical field of intelligent management. The system comprises an entrance personnel management subsystem, an entrance vehicle charging management subsystem, a public area video monitoring subsystem, a unit building face access control subsystem, a cloud visitor management subsystem, a community monitoring center, an overhead parabolic subsystem and a non-motor vehicle management system; each subsystem exists with independent mode, collects the cloud server rather than internet access according to the data of each subsystem collection and carries out analysis processes, for the resident of community provides convenient for people, benefit the people, benefits the people service, builds comfortable ecological environment, makes sustainable wisdom community, provides accurate service for the resident simultaneously, satisfies the application demand of district resident and property, has improved district safety precaution grade”).
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Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/DILARA SULTANA/Examiner, Art Unit 2858
/EMAN A ALKAFAWI/Supervisory Patent Examiner, Art Unit 2858
4/24/2026
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