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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 November 7, 2025 has been entered.
Response to Amendment
Claims 1, 12, and 17 have been amended. Claim 11 has been canceled. Claims 1-10 and 12-20 are pending.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-10 and 12-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim(s) recite(s) the following limitations which are directed towards abstract ideas as follows:
“receiving a plurality of video frames of the video stream” of claim 1, with similar limitations recited in claims 12 and 17, is directed towards a mental process, capable of being performed in the human mind with a pen and paper as physical aids. See MPEP 2106.04(a)(2)(III).
“performing video analytics on one or more of the plurality of video frames to detect one or more objects in the video stream” of claim 1, with similar limitations recited in claims 12 and 17, is directed towards a mental process, capable of being performed in the human mind with a pen and paper as physical aids.
“performing video analytics on one or more of the plurality of video frames to detect one or more persons in the video stream” of claim 1, with similar limitations recited in claims 12 and 17, is directed towards a mental process, capable of being performed in the human mind with a pen and paper as physical aids.
“identifying an object-person association between one of the objects detected in the video stream and one of the persons detected in the video stream, resulting in an object/person pair” of claim 1, with similar limitations recited in claims 12 and 17, is directed towards a mental process, capable of being performed in the human mind with a pen and paper as physical aids.
“with the object-person pair identified, tracking the object of the object/person pair and the person of the object/person pair through subsequent video frames” of claim 1, with similar limitations recited in claims 12 and 17, is directed towards a mental process, capable of being performed in the human mind with a pen and paper as physical aids.
“determining that the object of the object/person pair becomes abandoned by the person of the object/person pair when: the object of the object/person pair remains stationary for at least a stationary time threshold; and the person of the object/person pair and the object of the object/person pair become separated from each other by at least a separation distance threshold for at least a separation time threshold, wherein the separation distance threshold is automatically scaled using a computed size of the object of the of the object/person pair measured in pixels in the video stream to correct for perspective effects in the video stream which are based on the distance of the object from the video camera” of claim 1, with similar limitations recited in claims 12 and 17, is directed towards a mental process, capable of being performed in the human mind with a pen and paper as physical aids.
“issuing an alert when the object of the object/person pair becomes abandoned by the person of the object/person pair” of claim 2 is directed towards a mental process, capable of being performed in the human mind with a pen and paper as physical aids.
Similarly, limitations of claims 3-10, 13-16, and 18-20 are directed towards a mental process by continuing watching a video from a camera, then determining, tracking, identifying and providing an alert that the object/person pair are whether within a threshold distance for a threshold amount of time.
This judicial exception is not integrated into a practical application because although additional elements of “video camera” (claims 1, 12, and 17), “controller” (claim 17) are recited in the claims are respectively noted, these additional elements do not amount to more than a recitation of the words “apply it” (or an equivalent), and are no more than mere instructions to implement an abstract idea or other exception on a computer. See MPEP 2106.05(f).
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because, as being mere generic computer components (herein a video camera network), simply perform well-understood routine and conventional activity. See MPEP 2106.05(d)(II).
Claim Rejections - 35 USC § 102
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1-6, 8-9, and 17-20 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by RUSSO et al. (US PGPUB 2020/0193166 A1).
In regard to claim 1, RUSSO discloses a method for identifying an abandoned object in a video stream captured by a video camera (RUSSO, Abstract), the method comprising:
receiving a plurality of video frames of the video stream (RUSSO, [0096], 3D frames or images);
performing video analytics on one or more of the plurality of video frames to detect one or more objects in the video stream (RUSSO, [0098], ‘person plus object’ blob that includes a person and an object associated with the person; [0104], recognizing object(s) and a person associated with object(s) in video frames);
performing video analytics on one or more of the plurality of video frames to detect one or more persons in the video stream (RUSSO, [0098], ‘person plus object’ blob that includes a person and an object associated with the person; [0104], recognizing object(s) and a person associated with object(s) in video frames; [0106], person tracking);
identifying an object-person association between one of the objects detected in the video stream and one of the persons detected in the video stream, resulting in an object/person pair (RUSSO, [0098], ‘person plus object’ blob that includes a person and an object associated with the person);
with the object-person pair identified, tracking the object of the object/person pair and the person of the object/person pair through subsequent video frames (RUSSO, [0099], video stream may include video frames of a person holding or carrying an object; this is tracking the object of the object/person pair and the person of the object/person pair through subsequent video frames);
determining that the object of the object/person pair becomes abandoned by the person of the object/person pair when the object of the object/person pair remains stationary for at least a stationary time threshold; and the person of the object/person pair and the object of the object/person pair become separated from each other by at least a separation distance threshold for at least a separation time threshold (paragraph [0037]), wherein the separation distance threshold is automatically scaled using a computed size of the object of the object/person pair measured in pixels in the video stream to correct for perspective effects in the video stream which are based on the distance of the object from the video camera. (RUSSO, [0034], [0037], [0039],[0109], determining whether a predetermined threshold amount of time for the person remaining outside the exclusion zone has been reached or not; determining that the person has remained outside the exclusion zone for a threshold amount of time that is represented in terms of the counter incremented; if it is determined that the person has not yet remained outside the exclusion zone for the threshold amount of time, control is passed back to analyze the next 3D video frame; for example, additional video frames may be analyzed to determine that the person has re-entered the exclusion zone before the threshold has been reached; otherwise, if it is determined that the person has remained outside the exclusion zone for the threshold amount of time (for example, in terms of a predetermined number of seconds, minutes, or the like, or the equivalent number of video frames). It is noted that paragraph [0037] describes an object is left behind (separation distance) includes defining an exclusion zone and paragraph [0039] and [0061] describes the exclusion zone may be defined as a shape with a fixed, real-world size around the object for an object near the camera or far away from the camera. It further teaches the size of the exclusion zone may be learn and the exclusion covers the stationary objects. Paragraph [0091] teaches the size of object is also considered for determining the object left behind. This can read on the separation distance threshold is automatically scaled using a computed size of the object measured in pixels in the video stream).
In regard to claim 17, RUSSO discloses a security system (RUSSO, [0040] discloses using in a security setting; [0113], security entity; [0123], video surveillance system) comprising:
a video camera (RUSSO, Fig. 1, item 120, camera) for producing a video stream (RUSSO, [0053], video from camera);
a controller (RUSSO, Fig. 9, item 960, controller) operatively coupled to the video camera (RUSSO, Fig. 9, item 960 (controller) is coupled to item 965 (camera)), the controller configured to:
receive a plurality of video frames of the video stream (RUSSO, [0096], 3D frames or images);
perform video analytics on one or more of the plurality of video frames to detect one or more objects in the video stream (RUSSO, [0098], ‘person plus object’ blob that includes a person and an object associated with the person; [0104], recognizing object(s) and a person associated with object(s) in video frames);
perform video analytics on one or more of the plurality of video frames to detect one or more persons in the video stream (RUSSO, [0098], ‘person plus object’ blob that includes a person and an object associated with the person; [0104], recognizing object(s) and a person associated with object(s) in video frames; [0106], person tracking);
identify an object-person association between one of the objects detected in the video stream and one of the persons detected in the video stream, resulting in an object/person pair (RUSSO, [0098], ‘person plus object’ blob that includes a person and an object associated with the person);
track the object of the object/person pair and the person of the object/person pair through subsequent video frames (RUSSO, [0099], video stream may include video frames of a person holding or carrying an object; this is tracking the object of the object/person pair and the person of the object/person pair through subsequent video frames);
based on the track of the object of the object/person pair and the track of the person of the object/person pair, determine when the object of the object/person pair becomes abandoned by the person of the object/person pair (RUSSO, [0100], it is determined when the object is set down and separated from the person); and
determine that the object of the object/person pair becomes abandoned by the person of the object/person pair when the object of the object/person pair remains stationary for at least a stationary time threshold; and the person of the object/person pair and the object of the object/person pair become separated from each other by at least a separation distance threshold for at least a separation time threshold (paragraph [0037]), wherein the separation distance threshold is automatically scaled using a computed size of the object of the object/person pair measured in pixels in the video stream to correct for perspective effects in the video stream which are based on the distance of the object from the video camera. (RUSSO, [0034], [0037], [0039],[0109], determining whether a predetermined threshold amount of time for the person remaining outside the exclusion zone has been reached or not; determining that the person has remained outside the exclusion zone for a threshold amount of time that is represented in terms of the counter incremented; if it is determined that the person has not yet remained outside the exclusion zone for the threshold amount of time, control is passed back to analyze the next 3D video frame; for example, additional video frames may be analyzed to determine that the person has re-entered the exclusion zone before the threshold has been reached; otherwise, if it is determined that the person has remained outside the exclusion zone for the threshold amount of time (for example, in terms of a predetermined number of seconds, minutes, or the like, or the equivalent number of video frames). It is noted that paragraph [0037] describes an object is left behind (separation distance) includes defining an exclusion zone and paragraph [0039] and [0061] describes the exclusion zone may be defined as a shape with a fixed, real-world size around the object for an object near the camera or far away from the camera. It further teaches the size of the exclusion zone may be learn and the exclusion covers the stationary objects. Paragraph [0091] teaches the size of object is also considered for determining the object left behind. This can read on the separation distance threshold is automatically scaled using a computed size of the object measured in pixels in the video stream).
In regard to claim 2, which depends from claim 1, RUSSO discloses further comprising issuing an alert when the object of the object/person pair becomes abandoned by the person of the object/person pair (RUSSO, [0103], a timer can be used to count a time duration or number of video frames where an object was present, if an object is present fora certain duration (such as, for example, present for 5 seconds), then an alert can be triggered).
In regard to claims 3 and 18, which depend from claims 2 and 17, respectively, RUSSO discloses wherein the alert identifies: the abandoned object of the object/person pair; and the person that abandoned the object of the object/person pair (RUSSO, [0123], saving such data to a designated computer-readable medium; the primitive data can be thought of as data stored in a database; to detect event occurrences (such as, for example, a person dropping an object on the floor, a person placing an object on a surface such as a table or floor, a person abandoning an object, a person leaving an exclusion zone or area) in it, an efficient query language may be required ).
In regard to claims 4 and 19, which depend from claims 1 and 17, respectively, RUSSO discloses further comprising: archiving an image of the abandoned object of the object/person pair and an image of the person that abandoned the object of the object/person pair when the object of the object/person pair becomes abandoned by the person of the object/person pair (RUSSO, [0123], saving such data to a designated computer-readable medium; the primitive data can be thought of as data stored in a database; to detect event occurrences (such as, for example, a person dropping an object on the floor, a person placing an object on a surface such as a table or floor, a person abandoning an object, a person leaving an exclusion zone or area) in it, an efficient query language may be required).
In regard to claims 5 and 20, which depend from claims 1 and 17, respectively, RUSSO discloses wherein after the object of the object/person pair becomes abandoned by the person of the object/person pair, the method comprises: continuing to track the abandoned object of the object/person pair; continuing to track the person that abandoned the object of the object/person pair; and based on the continued tracking of the abandoned object of the object/person pair and the person that abandoned the object of the object/person pair, determining whether the person that abandoned the object of the object/person pair returns to the abandoned object of the object/person pair, and if so, determining that the abandoned object of the object/person pair is no longer abandoned by the person of the object/person pair (RUSSO, [0109], “continued person tracking” and determining whether a predetermined threshold amount of time for the person remaining outside the exclusion zone has been reached or not; determining that the person has remained outside the exclusion zone for a threshold amount of time that is represented in terms of the counter incremented; if it is determined that the person has not yet remained outside the exclusion zone for the threshold amount of time, control is passed back to analyze the next 3D video frame; for example, additional video frames may be analyzed to determine that the person has re-entered the exclusion zone before the threshold has been reached; otherwise, if it is determined that the person has remained outside the exclusion zone for the threshold amount of time (for example, in terms of a predetermined number of seconds, minutes, or the like, or the equivalent number of video frames)).
In regard to claim 6, which depends from claim 1, RUSSO discloses wherein identifying the object-person association comprises: determining that the object of the object/person pair and the person of the object/person pair are simultaneously present in the video stream; and determining that the object of the object/person pair and the person of the object/person pair are within a threshold distance of one another for at least a threshold amount of time (RUSSO, [0109], determining whether a predetermined threshold amount of time for the person remaining outside the exclusion zone has been reached or not; determining that the person has remained outside the exclusion zone for a threshold amount of time that is represented in terms of the counter incremented; if it is determined that the person has not yet remained outside the exclusion zone for the threshold amount of time, control is passed back to analyze the next 3D video frame; for example, additional video frames may be analyzed to determine that the person has re-entered the exclusion zone before the threshold has been reached; otherwise, if it is determined that the person has remained outside the exclusion zone for the threshold amount of time (for example, in terms of a predetermined number of seconds, minutes, or the like, or the equivalent number of video frames)).
In regard to claim 8, which depends from claim 1, RUSSO discloses wherein identifying the object-person association comprises: identifying a degree of overlap of the object of the object/person pair and the person of the object/person pair; and determining that the degree of overlap is greater than a degree of overlap threshold (RUSSO, [0109], time, distance, and exclusion zone).
In regard to claim 9, which depends from claim 1, RUSSO discloses wherein identifying the object-person association comprises: determining an estimated relative depth of the object of the object/person pair from the video camera; determining an estimated relative depth of the person of the object/person pair from the video camera; and determining that the estimated relative depth of the object of the object/person pair and the estimated relative depth of the person of the object/person pair are within a depth threshold of each other (RUSSO, [0007] and [0034], [0098], depth are used to determine if object and person are separated).
Claim Rejections - 35 USC § 103
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
Claims 12-14 are rejected under 35 U.S.C. 103 as being unpatentable over RUSSO in view of U.S. Patent Application Publication No. 2009/0033745 A1 to Yeredor et al. (hereinafter, Yeredor).
In regard to claim 12, RUSSO discloses method for identifying an abandoned object within a video stream that includes a plurality of video frames (RUSSO, Abstract), the method comprising:
receiving a plurality of video frames of the video stream (RUSSO, [0096], 3D frames or images);
performing video analytics on one or more of the plurality of video frames to detect possible objects of interest (RUSSO, [0098], ‘person plus object’ blob that includes a personand an object associated with the person; [0104], recognizing object(s) and a person associated with object(s) in video frames);
performing video analytics on one or more of the plurality of video frames to detect a person believed to be associated with each of the possible objects of interest (RUSSO, [0098], ‘person plus object’ blob that includes a personand an object associated with the person; [0104], recognizing object(s) and a person associated with object(s) in video frames; [0106], person tracking);
tracking each possible object of interest and the associated person through subsequent video frames (RUSSO, [0099], video stream may include video frames of a person holding or carrying an object);
detecting that one or more of the possible objects of interest have been abandoned by the person believed to be associated with that possible object of interest (RUSSO, [0100], it is determined when the object is set down and separated from the person) wherein detecting that the possible object of interest has been abandoned includes determining that the object of the object/person pair becomes abandoned by the person of the object/person pair when the object of the object/person pair remains stationary for at least a stationary time threshold; and the person of the object/person pair and the object of the object/person pair become separated from each other by at least a separation distance threshold for at least a separation time threshold (paragraph [0037]), wherein the separation distance threshold is automatically scaled using a computed size of the object of the object/person pair measured in pixels in the video stream to correct for perspective effects in the video stream which are based on the distance of the object from the video camera. (RUSSO, [0034], [0037], [0039],[0109], determining whether a predetermined threshold amount of time for the person remaining outside the exclusion zone has been reached or not; determining that the person has remained outside the exclusion zone for a threshold amount of time that is represented in terms of the counter incremented; if it is determined that the person has not yet remained outside the exclusion zone for the threshold amount of time, control is passed back to analyze the next 3D video frame; for example, additional video frames may be analyzed to determine that the person has re-entered the exclusion zone before the threshold has been reached; otherwise, if it is determined that the person has remained outside the exclusion zone for the threshold amount of time (for example, in terms of a predetermined number of seconds, minutes, or the like, or the equivalent number of video frames). It is noted that paragraph [0037] describes an object is left behind (separation distance) includes defining an exclusion zone and paragraph [0039] and [0061] describes the exclusion zone may be defined as a shape with a fixed, real-world size around the object for an object near the camera or far away from the camera. It further teaches the size of the exclusion zone may be learn and the exclusion covers the stationary objects. Paragraph [0091] teaches the size of object is also considered for determining the object left behind. This can read on the separation distance threshold is automatically scaled using a computed size of the object measured in pixels in the video stream).
continuing to track the abandoned object (RUSSO, [0103], determining that the separate object is present in the scene for a certain duration or certain number of video frames);
tracking the person believed to be associated with the abandoned object to see if the person returns to the abandoned object (RUSSO, [0012] and [0061], determining that the person has been separated from the object for the predetermined threshold comprises includes: determining that the object is present in the scene for a certain duration; defining an exclusion zone around the object and within the scene; and determining, based at least in part on person tracking, that the person has left the exclusion zone; if the person has left the exclusion zone for a threshold set time, it is determined the object has been abandoned); and
raising an alert when the person believed to be associated with the abandoned object does not return to the abandoned object within a threshold period of time (RUSSO, [0103], a timer can be used to count a time duration or number of video frames where an object was present, if an object is present fora certain duration (such as, for example, present for 5 seconds), then an alert can be triggered).
RUSSO does not specifically disclose wherein identifying the object-person association comprises: tracking a direction of travel of the object of the object/person pair and tracking a direction of travel of the person of the object/person pair across two or more video frames; and determining that the direction of travel of the object of the object/person pair and the direction of travel of the person of the object/person pair deviate by less than a travel direction deviation threshold. Yeredor, however, discloses/makes obvious disclose wherein identifying the object-person association comprises: tracking a direction of travel of the object of the object/person pair and tracking a direction of travel of the person of the object/person pair across two or more video frames; and determining that the direction of travel of the object of the object/person pair and the direction of travel of the person of the object/person pair deviate by less than a travel direction deviation threshold (Yeredor, [0025], the first object remains in the video scene without movement fora pre-defined period of time (direction of travel is zero); the second object exits the video scene. It is assumed that the individual (second object) left the video scene without the suitcase (first object) and is now about leave the wider area around the video scene. Following the identification of the previous sub-events, referred to collectively as the video scene characteristics, the event will be identified by the system as a situation in which an unattended suitcase was left in the security-sensitive area. Thus, the unattended suitcase will be considered as a suspicious object. Consequently, the system of the present invention generates, displays, and or distributes an alarm indication. Likewise, in an alternative embodiment a first object, such as a suitcase or person monitored is already present and monitored within the video scene. Such objectcan be lost luggage located within the airport. Such object can bea person monitored. The object may merge into a second object The second object can be a person picking up the luggage, another person to whom the first person joins or a vehicle to which the first person enters. The first object (now merged with the second object) may move from its original position and exist the scene or move in a prohibited direction so predetermined). It would have been obvious to one having ordinary skill in the art before the effective filing date of the invention to combine the teachings of Yeredor with the teachings of RUSSO to identify a security issue and/or help facilitate a lost item (Yeredor, [0025]).
In regard to claim 13, which depends from claim 12, RUSSO discloses wherein the alert identifies: the abandoned object of the object/person pair; and the person that abandoned the object of the object/person pair (RUSSO, [0123], saving such data to a designated computer-readable medium; the primitive data can be thought of as data stored in a database; to detect event occurrences (such as, for example, a person dropping an object on the floor, a person placing an object on a surface such as a table or floor, a person abandoning an object, a person leaving an exclusion zone or area) in it, an efficient query language may be required ).
In regard to claim 14, which depends from claim 13, RUSSO discloses further comprising: archiving an image of the abandoned object of the object/person pair and an image of the person that abandoned the object of the object/person pair when the object of the object/person pair becomes abandoned by the person of the object/person pair (RUSSO, [0123], saving such data to a designated computer-readable medium; the primitive data can be thought of as data stored in a database; to detect event occurrences (such as, for example, a person dropping an object on the floor, a person placing an object on a surface such as a table or floor, a person abandoning an object, a person leaving an exclusion zone or area) in it, an efficient query language may be required).
Claim 10 is rejected under 35 U.S.C. 103 as being unpatentable over RUSSO in view of U.S. Patent Application Publication No. 2018/0046863 A1 to Chen et al. (hereinafter, Chen).
In regard to claim 10, which depends from claim 1, RUSSO does not specifically disclose comprising: tracking one or more objects in the video stream, resulting in one or more tracked objects; failing to identify a missing one of the previously tracked objects in one or more video frames; identifying a new tracked object in a subsequent video frame after failing to identify the missing one of the previously tracked objects; determining that the new tracked object corresponds to the missing one of the previously tracked objects; and re-identifying the new tracked object as the missing one of the previously tracked objects.
Chen, however, discloses/makes obvious tracking one or more objects in the video stream, resulting in one or more tracked objects; failing to identify a missing one of the previously tracked objects in one or more video frames; identifying a new tracked object in a subsequent video frame after failing to identify the missing one of the previously tracked objects; determining that the new tracked object corresponds to the missing one of the previously tracked objects; and re-identifying the new tracked object as the missing one of the previously tracked objects (Chen, [0005] — [0006], tracked object becomes lost and is then detected and tracked again).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the invention to combine the teachings of Chen with the teachings of Russoto maintain lost object trackers in video analytics (Chen, [0002]), which would help in returning the lost object to its owner.
Claim 15 is rejected under 35 U.S.C. 103 as being unpatentable over RUSSO in view of U.S. Patent Application Publication No. 2020/0043174 A1 to TOGASHI et al. (hereinafter, TOGASHI).
In regard to claim 15, which depends from claim 12, RUSSO does not specifically disclose wherein when the person believed to be associated with the abandoned object does not return to the abandoned object within a threshold period of time, continuing to track the person believed to be associated with the abandoned object and provide a current location of the person believed to be associated with the abandoned object.
TOGASHI, however, discloses/makes obvious wherein when the person believed to be associated with the abandoned object does not return to the abandoned object within a threshold period of time, continuing to track the person believed to be associated with the abandoned object and provide a current location of the person believed to be associated with the abandoned object (TOGASHI, [0032], tracking the target person after they have left behind the object).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the invention to combine the teachings of TOGASHI with the teachings of Russoin order to provide a system that makes it possible to reduce the burden on the user from the work for identifying a person who has left an abandoned item and tracking the movement of the person (TOGASHI, [0013]).
Claim 16 is rejected under 35 U.S.C. 103 as being unpatentable over RUSSO in view of U.S. Patent Application Publication No. 2019/0028759 Al to Yuan etal. (hereinafter, Yuan).
In regard to claim 16, which depends from claim 12, RUSSO does not specifically disclose further comprising: detecting that the abandon object has been moved by a new person other than the person believed to be associated with the abandoned object; associating the new person with the abandoned object; archiving an image of the new person; tracking the abandoned object; tracking the new person; and raising an alert that the abandoned object has been moved by the new person.
Yuan, however, discloses/makes obvious detecting that the abandon object has been moved by a new person other than the person believed to be associated withthe abandoned object; associating the new person with the abandoned object; archiving an image of the new person; tracking the abandoned object; tracking the new person; and raising an alert that the abandoned object has been moved by the new person (Yuan, [0082], if the identified person left a package, the location of the package and any activity that occurs near the package may be tracked ).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the invention to combine the teachings of Yuan with the teachings of Russoin order to make it easy to identify a thief if a package is stolen (Yuan, [0082]).
Response to Arguments
Applicant's arguments filed October 23, 2025 have been fully considered but they are not persuasive.
Claim Rejections – 35 U.S.C. 101
Applicant argues, based on the amended limitation “the separation distance threshold is automatically scaled using a computed size of the object of the object/person pair measured in pixels in the video stream to correct for perspective effects”, on page 10, that pixel-based scaling limitation is inherently technological and cannot be performed mentally. It should be noted that the amended limitation is after the term “wherein” which is just a phrase for providing an information regarding the separation distance threshold. The examiner’s position is that the mental process is based on the provided information of a separation distance threshold to determine if the person of the object/person pair and the object of the object/person pair become separated from each other. There are no pixel counting requires computer processing, automatic scaling algorithms, nor perspective correction processing in the claims as argued.
Applicant further argues, on page 11, that the claims solve the concrete technological problem of perspective distortion in video surveillance systems by using pixel-based measurements to dynamically scale separation distance thresholds. Examiner respectfully disagrees. The claims themselves do not reflect the disclosed improvement (examiner assumes the specification provides the improvement, but will look into it if it is necessary). Examiner refers to the second and last paragraphs of MPEP 2106.04(d)(1) that “… if the specification sets forth an improvement in technology or a technical field, the claim must be evaluated to ensure that the claim it self reflects the disclosed improvement…”. Therefore, the claims are not clearly integrated into a practical application and hence, are directed towards a mental process, capable of being performed in the human mind with a pen and paper as physical aids. Therefore, the claimed invention is directed to an abstract idea without significantly more and claim rejections under 35 USC 101 is proper.
Claim Rejections – 35 U.S.C. 102 and 103
Applicant argues that Russo teaches generic “blob” abstraction and distance measurements form a camera for person/object tracking purposes while the claimed invention teaches specific pixel-base size measurement to automatically scale separation distance thresholds for perspective correction. Examiner respectfully disagrees. First, “blob” does not mean that the object does not have a size. Second, Russo teaches all measurements including the distance from object to camera or size of the object, are based on the pixel (see paragraph [0054]).
Applicant argues that Russo’s size determination serves fundamentally different technical purpose. The claimed invention’s size determination is dynamic threshold scaling based on pixel measurements for perspective correction to compensate for camera distance effects. Examiner respectfully disagrees. The general purpose for both Russo and the claimed invention is to determine the object left behind (separation distance). As stated in the rejection above, Russo teaches determining the distance of an object being far or near the camera based on the size of the exclusion zone including object and this information is partially used to determine whether the person has left an object behind (paragraphs [0039] and [0061]). Of course, the distance of an object from the camera is dynamically calculated until the object is stationary. Further, Russo teaches “By using the depth information and the expected height of people and the expected size or height of objects, various implementations can compensate for the smaller people and object images, and still have a functioning system that detects objects left behind by people (last sentence of paragraph [0034]).
In response to applicant's argument that the references fail to show certain features of the invention, it is noted that the features upon which applicant relies (i.e, perspective distortion in video surveillance systems where objects appear different sizes based on their distance from the camera) are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993). Even if this limitation is included, Russo teaches this limitation as addressed in #2 above.
In response to applicant's argument that the references fail to show certain features of the invention, it is noted that the features upon which applicant relies (i.e, pixel-based measurement…; automatic scaling algorithms….; dynamic perspective correction…) are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993). Even if this limitation is included, Russo teaches this limitation as addressed in #2 above.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
US Patent 11164007 teaches a method and system for detecting the owner of an abandoned object from a surveillance video where the size of the region can be decided heuristically based on the distance of the camera from the objects or the average size of any object/person in the scene (paragraph [0053]).
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/BENNY Q TIEU/Supervisory Patent Examiner, Art Unit 2682