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 .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 08/19/2024 & 12/18/2024 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Priority
Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
Specification
The disclosure is objected to because of the following informalities:
[pg. 35; ln. 22-25] – the specification makes reference to a heat map button D3 in Fig. 11. Fig. 11 shows no heat map button D3. Examiner believes this was meant to either reference the heat map button D3 in either Fig. 12 or 13.
[pg. 35; ln. 22-25] – the specification makes reference to an accumulated time tab D4 in Fig. 11. Fig. 11 shows no accumulated time tab D4. Examiner believes this was meant to either reference the heat map button D3 in either Fig. 12 or 13.
Appropriate correction is required.
Claim Objections
Claim 10 objected to because of the following informalities:
Claim 10 recites “…wherein the pre-trained AI model is trained, based on a dataset which…”. The claim language syntax is slightly unclear. The examiner believes “wherein the pre-trained AI model is trained on a dataset” may be more syntactically appropriate.
Appropriate correction is required.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are:
Claim 6 – recites the limitation, “a communication module configured to receive …”
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
“a communication module” (Fig. 1, #1100, pg. 11 {ln. 10-25} & pg. 12 {ln. 1-10}) – the communication module 1100 is described as part of the electronic device 1000, which can either be a wired (such as a LAN or USB), or wireless (WLAN (Wi-Fi) or cellular (LTE/5G)) communication for receiving image data.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 112(b)
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-16 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claims 1, 15 & 16 first recite similar limitations “setting a region of interest to obtain…”, and then further recite “outputting a selection user interface (UI) for selecting a region of interest related to the indicator”. It is unclear if applicant intends these two clauses refer to the same “a region of interest”, in which case, there would be insufficient antecedent basis as the next recitation should be “the region of interest”. If these are distinctly different “regions of interest”, which examiner believes to be the case in light of the specification [pg. 18; ln. 7-24], then they need to be identified as such. Thus, “a region of interest” is not properly defined and renders the claim language indefinite.
Subsequently, claims 2-14, which depend on claim 1 are rejected based on their dependency to claim 1.
Claim 12 recite the limitation “…wherein the UI is displayed together…”. Claim 1 first introduces the limitation “a selection user interface (UI)”, which is later referred to as “the selection UI” in claims 1 & 4. Similarly, claim 4 introduces the distinct limitation “a UI”, which is later referred to as “the UI”. It is unclear whether “the UI” of claim 12, is meant to refer to “the selection UI” introduced in claim 1, or “the UI” introduced in claim 4. If “the UI” of claim 12 is intended to be in reference to “the selection UI” of claim 1, it should be amended accordingly. If “the UI” of claim 12 is intended to reference “the UI” of claim 4, then it lacks the proper dependency to this limitation, and should instead be dependent on claim 4. In its current construction, there is insufficient antecedent basis for the limitation “the UI” of claim 12. Thus, “the UI” of claim 12 is not properly defined and renders the claim language indefinite.
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.
Claim(s) 1-8 & 11-12 are rejected under 35 U.S.C. 103 as being unpatentable over Bosch IVA 4.0 Intelligent Video Analysis Operating Manual (publ. June 2009), hereinafter referred as “IVA” in view of Li et al (CN 112818935 A), hereinafter referred to as “Li”.
Considering claim 1, IVA disclose a surveillance video annotation and analysis wizard analyzing object movement. More specifically, IVA teach A method of setting a region of interest in an image for collecting road traffic indexes using an electronic device (the intelligent video analysis (IVA) program is an algorithm that can be used to detect properties and behaviors of moving object in a [Sec 1.4 – Intelligent Video Analysis], objects are typically people or vehicles moving in a field [Sec 4.1 – The Basics – Objects]), the method comprising:
setting a region of interest to obtain data related to movement of an object on the basis of an input of a user (a user is able to create polygonal “fields” that detect objects moving within them [Sec 4.1 – The Basics – Field]);
outputting an indicator for obtaining additional data on the basis of the input of the user (a variety of indicators can be displayed based on a user selected “task”, such as “Object in Field” which prompts a user to select a field and then displays a colored outline indicator indicating detected objects entering the field [Sec 4.5.2 – Object in Field; Fig. on pg. 26]);
outputting a selection user interface (UI) for selecting a region of interest related to the indicator (when a user selects the task “Object in Field”, a user can either select an existing field or creating a new field, and when an object passes through, a colored outline indicator will be overlayed onto the object [Sec 4.5.2 – Object in Field; Fig. on pg. 26 & Sec 4.2 – Object Outlines and Other Image Information]); and
linking the region of interest selected through the selection UI to the indicator (after selecting the task “Object in Field”, a user is directed to select a field to perform the task, thereby linking any colored outline indicator indicating a detected object to that particular field [Sec 4.5.2 – Object in Field; Fig. on pg. 26 & Sec 4.2 – Object Outlines and Other Image Information]). IVA fails to disclose the surveillance video used in their system is obtained in real-time.
Li, however, is analogous art pertinent to the field of endeavor of the present application and disclose a multi-lane congestion detection method for monitoring real-time traffic data. More specifically, Li teach displaying surveillance images collected in real time; (Li: obtaining a real-time video stream of road traffic in step 1 of Fig. 1 [¶33-34; exemplified in Fig. 4]). Furthermore, Li describe that their invention enables real-time monitoring to obtain live data of traffic flow which facilitates accurate congestion detection and prediction of congestion duration [¶23].
Therefore, it would have been obvious to one of ordinary skill before the effective filing date of the present application to utilize the teachings real-time monitoring of Li with the video analytics system outlined in IVA to arrive at the invention of the present application. The motivation for doing so would be to accurately obtain congestion information of a road segment in real-time.
Regarding claim 2, IVA in view of Li teach The method of claim 1 (as described above), more specifically, IVA teach wherein the region of interest includes a vehicle region-of-interest for measuring movement of a vehicle (IVA: objects can be filtered according to certain properties to distinguish vehicles and pedestrians [Sec 4.1 – The Basics – Objects], when selecting the task “Object in Field”, a user can configure detection conditions for objects entering a field with the properties of a vehicle to obtain movement information such as speed [Sec 4.5.2 – Object in Field]) and a pedestrian region-of-interest for measuring movement of a pedestrian (IVA: when selecting the task “Object in Field”, a user can configure detection conditions for objects entering a field with the properties of a pedestrian to obtain movement information such as speed [Sec 4.5.2 – Object in Field], particularly when “Head Detection” is configured to identify heads of pedestrians passing through a field [4.7.2 – Global Settings & Sec 4.2 – Object Outlines and Other Image Information]).
Turning to claim 3, IVA in view of Li teach The method of claim 2 (as described above), more specifically, IVA teach wherein the indicator includes a vehicle indicator that is linkable to the vehicle region-of-interest (IVA: a field for detecting vehicles can be defined over a street, which can be restricted to only detect vehicles based on defined conditions (object size, aspect ratio, speed, direction), which, when met, display uniquely colored outline around cars associated to the field [Sec 4.5.2 – Object in Field & Sec 4.2 – Object Outlines and Other Image Information]) and a pedestrian indicator that is linkable to the pedestrian region-of-interest (IVA: a field for detecting pedestrians can be defined over a sidewalk, which can be restricted to only detect pedestrians via “Head Detection”, which when met, display blue head indicators linked to the field [Sec 4.5.2 – Object in Field & Sec 4.2 – Object Outlines and Other Image Information]).
Regarding claim 4, IVA in view of Li teach The method of claim 3, (as described above), more specifically, IVA teach wherein a UI is displayed together with the surveillance images (IVA: a popup menu is displayed alongside the surveillance video [Sec 4.3.1 – Popup Menu in the Camera Image; Fig. on pg. 19]), the UI includes a region-of-interest icon for setting the region of interest (IVA: a “Create Field” icon is provided for designated a field for analysis [Sec 4.3.1 – Popup Menu in the Camera Image; Fig. on pg. 19]), a vehicle indicator icon for setting the vehicle indicator (IVA: the “Object in Field” icon can be clicked to allow a user to either select or create a field configured for vehicles via user or pre-defined conditions to show a colored outline indicator on identified vehicles in the field [Sec 4.5.2 – Object in Field & Sec 4.2 – Object Outlines and Other Image Information]), and a pedestrian indicator icon for setting the pedestrian indicator (IVA: the “Object in Field” icon can be clicked to allow a user to either select or create a field configured for pedestrians via user or pre-defined conditions to show a colored outline indicator on identified pedestrians in the field [Sec 4.5.2 – Object in Field & Sec 4.2 – Object Outlines and Other Image Information], furthermore, with “Head Detection” configured, heads of pedestrians passing through a field are indicated via a blue head mark [4.7.2 – Global Settings & Sec 4.2 – Object Outlines and Other Image Information]),
when the user selects the vehicle indicator icon, the selection UI displays a preset vehicle region-of-interest (IVA: a user is must define an associated field when “Object in Field” is selected [Sec 4.5.2 – Object in Field], with a predefined field already placed on the image view which a user is able to edit and adjust [Sec 4.3.1 – Popup Menu in the Camera Image]), and
when the user selects the pedestrian indicator icon, the selection UI displays a preset pedestrian region-of-interest (IVA: a user can define an associated field when “Object in Field” is selected [Sec 4.5.2 – Object in Field], again, “Head Detection” can be configured to strictly identify heads of pedestrians passing through a field [4.7.2 – Global Settings & Sec 4.2 – Object Outlines and Other Image Information], with a predefined field already placed on the image view which a user is able to edit and adjust [Sec 4.3.1 – Popup Menu in the Camera Image]).
When considering claim 5, IVA in view of Li teach The method of claim 4 (as described above), IVA, particularly, teach wherein the vehicle indicator includes a loop detector for detecting an occupancy rate within the vehicle region-of-interest (IVA: a “Crossing line” task can be designated to count a number of vehicles passing through a designated field [Sec 4.5.3 – Crossing Line]) and a direction vector for measuring an exit direction of the vehicle (IVA: a direction filter can be used to measure the direction of vehicles in a designated field [Sec 4.5.2 – Object in Field], furthermore a crossing line can measure vehicles passing forward or backwards through the line [Sec 4.5.3 – Crossing Line], while object motion flow arrows can illustrate the speed and direction of objects in a field [Sec 5.1 – IVA 4.0 Flow Basics and Image Information]) and
when the direction vector is set as a first direction and a second direction, a number of vehicles exiting from the vehicle region-of-interest in the first direction and the second direction is measured (IVA: the crossing line can count the number of times a vehicle passing through a forward or backward direction [Sec 4.5.3 – Crossing Line]).
As for claim 6, IVA in view of Li teach The method of claim 5 (as described above), IVA further teaches wherein the direction vector is displayed as an arrow indicating the exit direction (IVA: object motion flow arrows can illustrate the direction of vehicles as they enter and exit a field [Sec 5.1 – IVA 4.0 Flow Basics and Image Information]), and
when the direction vector is linked to the vehicle region-of-interest, the link between the direction vector and the vehicle region-of-interest is displayed through a linker (IVA: arrows indicating flow direction and speed are displayed in an analysis field, with the color of the arrow linking objects that trigger detection to the designated field conditions [Sec 5.1 – IVA 4.0 Flow Basics and Image Information]).
Regarding claim 7, IVA in view of Li teach The method of claim 5 (as described previously), IVA further teach wherein the pedestrian indicator includes a pedestrian measurer for counting an amount of traffic for pedestrians moving in the pedestrian region-of-interest (IVA: a crossing line function configured to only detect persons can count the number of pedestrians passing through a field of interest, which can be configured to only trigger by pedestrians [Sec 4.5.3 – Crossing line]),
the UI further includes a vector icon (IVA: Crossing line icon [Sec 4.5.3 – Crossing line] or object in field icon [Sec 4.5.2 – Object in Field]),
when a setting input of a straight line is received in the pedestrian region-of-interest after the vector icon is selected, the straight line is set to the pedestrian measurer (IVA: a crossing line function configured to only detect persons can count the number of pedestrians passing through a field of interest, which can be configured to only trigger by pedestrians via “Head Detection” [Sec 4.5.3 – Crossing line & Sec 4.2 – Object Outlines and Other Image Information]), and
when a setting input of a straight line is received in a region adjacent to the vehicle region-of-interest after the vector icon is selected, the straight line is set to the direction vector (IVA: a direction arrow can be set for fields configured to trigger by vehicles [Sec 4.5.2 – Object in Field]).
As for claim 8, IVA in view of Li teach The method of claim 1 (as described previously), with IVA further teaching wherein the region of interest further includes a speed measurement region for measuring a moving speed of a vehicle in a specific region in the surveillance image (IVA: speed of an vehicle is measured via the “flow in field” task [Sec 5.4.3 – Flow in Field]), and when the region of interest and the indicator overlap, the indicator is displayed preferentially (IVA: flow indicators (yellow circles) are shown preferentially with full opacity while the field is displayed translucently [Sec 5.4.3 – Flow in Field; Fig. on pg. 55]).
Turning to claim 11, IVA in view of Li teach The method of claim 1 (as described previously), IVA fail to explicitly recite a heatmap overlayed surveillance footage. Li, however, teach further comprising displaying a heat map on the surveillance image based on the input of the user (Li: step S613 describe overlaying a vehicle density heat map over the road traffic interest area [¶21-22]),
wherein the heat map is generated by analyzing the surveillance images for an accumulated time (Li: the accumulated time of the surveillance footage informs the current vehicle density heat map and future predictions of how long congestion will last [¶21-22]). Li further describe that their invention enables real-time monitoring to obtain live data of traffic flow which facilitates accurate congestion detection and prediction of congestion duration [¶23].
Therefore, it would have been obvious to one of ordinary skill before the effective filing date of the present application to utilize the teachings real-time monitoring of Li with the video analytics system outlined in IVA to arrive at the invention of the present application. The motivation for doing so would be to accurately obtain congestion information of a road segment in real-time.
As for claim 12, IVA in view of Li teach The method of claim 11 (as described above), with IVA further teaching wherein the UI is displayed together with the surveillance images (IVA: a popup menu is displayed alongside the surveillance video [Sec 4.3.1 – Popup Menu in the Camera Image; Fig. on pg. 19]), but does not explicitly teach entering an accumulated time into its UI.
Li, on the other hand, teach and the UI includes an accumulated time input region for inputting the accumulated time (Li: at step S613, a time period can be set [¶21-22]). Li further describe that their invention enables real-time monitoring to obtain live data of traffic flow which facilitates accurate congestion detection and prediction of congestion duration [¶23].
Therefore, it would have been obvious to one of ordinary skill before the effective filing date of the present application to utilize the teachings real-time monitoring of Li with the video analytics system outlined in IVA to arrive at the invention of the present application. The motivation for doing so would be to accurately obtain congestion information of a road segment in real-time.
Claim(s) 13-15 are rejected under 35 U.S.C. 103 as being unpatentable over Bosch IVA 4.0 Intelligent Video Analysis Operating Manual (publ. June 2009), hereinafter referred as “IVA” in view of Li et al (CN 112818935 A), hereinafter referred to as “Li”, further in view of Hranac et al (US 2014/0136089 Al), hereinafter referred to as “Hranac”.
Regarding claim 13, IVA in view of Li The method of claim 11 (as described previously), and while IVA teach further comprising, when a selection for the set region of interest is received (IVA: a field is either selected from an existing one or created [Sec 4.1 – The Basics – Field]), IVA fails to teach the limitation of a time series chart.
Hranac, on the other hand, is analogous art pertinent to the field of endeavor and disclose traffic visualization dashboard for obtaining roadway incident analytics. Hranac specifically teach displaying a time series chart related to the object measured in the region of interest (Hranac: a timeline section 240 displays time-series chart 242 which can display either the current day’s congestion data, a past years congestion distribution by the hour, and an incidence area showing the day’s hourly incidents and the difference between past years [¶0047; Fig. 2]). Hranac further recite that their dashboard enable a user to select a variety of information categories (anomalies, speeds, incidents, work zones) to be displayed on their interface [¶0038], and enable real-time congestion analysis for a roadway [¶0011].
Therefore, it would have been obvious to one of ordinary skill before the effective filing date of the present application to implement the dashboard of Hranac to provide a congestion analytics time-series feature to the video analysis wizard described by IVA in view of Li to arrive at the invention of the instant application. The motivation for doing so would be obtain more information about the traffic conditions of a road segment in real-time.
As for claim 14, IVA in view of Li, further in view of Hranac teach The method of claim 13 (as described above), with Li disclosing wherein information on the object displayed through the heat map, (Li: vehicle density heat map [¶21-22]). Li further describe that their invention enables real-time monitoring to obtain live data of traffic flow which facilitates accurate congestion detection and prediction of congestion duration [¶23].
Therefore, it would have been obvious to one of ordinary skill before the effective filing date of the present application to utilize the teachings real-time monitoring of Li with the video analytics system outlined in IVA to arrive at the invention of the present application. The motivation for doing so would be to accurately obtain congestion information of a road segment in real-time. Li, however, fail to teach different information in the form of a time-series chart.
Hranac, on the other hand, teach is different from information on the object displayed through the time series chart (Hranac: a timeline section 240 displays time-series chart 242 can an incidence area showing the day’s hourly incidents and the difference between past years [¶0047; Fig. 2]). Hranac further recite that their dashboard enable a user to select a variety of information categories (anomalies, speeds, incidents, work zones) to be displayed on their interface [¶0038], and enable real-time congestion analysis for a roadway [¶0011].
Therefore, it would have been obvious to one of ordinary skill before the effective filing date of the present application to implement the dashboard of Hranac to provide a congestion analytics time-series feature to the video analysis wizard described by IVA in view of Li to arrive at the invention of the instant application. The motivation for doing so would be obtain more information about the traffic conditions of a road segment in real-time.
Considering claim 15, IVA teach the computer program comprising:
setting a region of interest to obtain data related to movement of an object on the basis of an input of a user (IVA: the intelligent video analysis (IVA) program is an algorithm that can be used to detect properties and behaviors of moving object [Sec 1.4 – Intelligent Video Analysis], objects are typically people or vehicles moving in field [Sec 4.1 – The Basics – Objects]);
outputting an indicator for obtaining additional data on the basis of the input of the user (IVA: a variety of indicators can be displayed based on a user selected “task”, such as “Object in Field” which prompts a user to select a field and then displays a colored outline indicator indicating detected objects entering the field [Sec 4.5.2 – Object in Field; Fig. on pg. 26 & Sec 4.2 – Object Outlines and Other Image Information]);
outputting a selection user interface (UI) for selecting a region of interest related to the indicator (IVA: when a user selects the task “Object in Field”, a user can either select an existing field or creating a new field, and when an object passes through, a colored outline indicator will be overlayed onto the object [Sec 4.5.2 – Object in Field; Fig. on pg. 26 & Sec 4.2 – Object Outlines and Other Image Information]); and
linking the region of interest selected through the selection UI to the indicator (IVA: after selecting the task “Object in Field”, a user is directed to select a field to perform the task, thereby linking any colored outline indicator indicating a detected object to that particular field [Sec 4.5.2 – Object in Field; Fig. on pg. 26] & Sec 4.2 – Object Outlines and Other Image Information). IVA fails to disclose the surveillance video used in their system is obtained in real-time.
Li, however, teach displaying surveillance images collected in real time; (Li: obtaining a real-time video stream of road traffic in step 1 of Fig. 1 [¶33-34; exemplified in Fig. 4]). Furthermore, Li describe that their invention enables real-time monitoring to obtain live data of traffic flow which facilitates accurate congestion detection and prediction of congestion duration [¶23].
Therefore, it would have been obvious to one of ordinary skill before the effective filing date of the present application to utilize the teachings real-time monitoring of Li with the video analytics system outlined in IVA to arrive at the invention of the present application. The motivation for doing so would be to accurately obtain congestion information of a road segment in real-time. Li, however, fails to explicitly recite a non-transitory computer-readable recording medium.
Hranac, on the other hand, teach A non-transitory computer-readable recording medium on which a computer program executed by a computer is recorded, (Hranac: computer environment 160 includes a processors 162 and memory modules 164 [¶0029; Fig. 1]). Hranac is combinable with IVA because it is from the related field of endeavor. It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention to combine the memory of Hranac with the invention of IVA and Li.
The motivation for doing so would have been combining prior art methods, the method of IVA and the memory of Hranac, according to known methods, it is well known in the art to store instructions on a computer readable medium, to yield predictable results, a computer implemented method performed by a processor and a memory storing the instructions. Further, a person of ordinary skill in the art would know that in combination each element, the method of IVA and the memory of Hranac, merely perform the same functions as it does separately and would have recognized that the results of the combination are predictable.
Therefore, it would have been obvious to combine Hranac with IVA to obtain the invention as specified in claim 15.
Claim 16 is rejected under 35 U.S.C. 103 as being unpatentable over Bosch IVA 4.0 Intelligent Video Analysis Operating Manual (publ. June 2009), hereinafter referred as “IVA” in view of Li et al (CN 112818935 A), hereinafter referred to as “Li”, further in view of O’Gorman et al (US 2015/0287214 A1), hereinafter referred to as “O’Gorman”.
Regarding claim 16, IVA teach being configured to set a region of interest for collecting road traffic indexes in the image data on the basis of the image data (IVA: the intelligent video analysis (IVA) program is an algorithm that can be used to detect properties and behaviors of moving object [Sec 1.4 – Intelligent Video Analysis], objects are typically people or vehicles moving in a field [Sec 4.1 – The Basics – Objects]),
set a region of interest to obtain data related to movement of an object on the basis of an input of a user (IVA: a user is able to create polygonal “fields” that detect objects moving within them [Sec 4.1 – The Basics – Field]), output an indicator for obtaining additional data on the basis of the input of the user (IVA: a variety of indicators can be displayed based on a user selected “task”, such as “Object in Field” which prompts a user to select a field and then displays a colored outline indicator indicating detected objects entering the field [Sec 4.5.2 – Object in Field; Fig. on pg. 26 & Sec 4.2 – Object Outlines and Other Image Information]), output a selection user interface (UI) for selecting a region of interest related to the indicator (when a user selects the task “Object in Field”, a user can either select an existing field or creating a new field, and when an object passes through, a colored outline indicator will be overlayed onto the object [Sec 4.5.2 – Object in Field; Fig. on pg. 26& Sec 4.2 – Object Outlines and Other Image Information]), and link the region of interest selected through the selection UI to the indicator (IVA: after selecting the task “Object in Field”, a user is directed to select a field to perform the task, thereby linking any colored outline indicator indicating a detected object to that particular field [Sec 4.5.2 – Object in Field; Fig. on pg. 26 & Sec 4.2 – Object Outlines and Other Image Information]). IVA fails to disclose the surveillance video used in their system is obtained in real-time.
Li, however, teach that their system (Li: obtaining a real-time video stream of road traffic in step 1 of Fig. 1 [¶33-34; exemplified in Fig. 4]). Furthermore, Li describe that their invention enables real-time monitoring to obtain live data of traffic flow which facilitates accurate congestion detection and prediction of congestion duration [¶23].
Therefore, it would have been obvious to one of ordinary skill before the effective filing date of the present application to utilize the teachings real-time monitoring of Li with the video analytics system outlined in IVA to arrive at the invention of the present application. The motivation for doing so would be to accurately obtain congestion information of a road segment in real-time. IVA in view of Li, however, fails to recite an electronic device with a communication module or an explicitly described processor.
O’Gorman, on the other hand, is analogous art pertinent to the field of endeavor of the present application and disclose a monitoring apparatus for tracking object movements and generating activity maps. O’Gorman teach An electronic device (O’Gorman: a unified activity map generation circuit 104, which can include a CPU [¶0080; Fig. 1]) comprising:
a communication module (Examiner notes that this limitation is being interpreted under 35 U.S.C. § 112(f) – O’Gorman: the network can 110 may be the internet, intranet, LAN [¶0079]) configured to receive image data captured by a camera (O’Gorman: the network receives video data from cameras 10-1 … 10-N [¶0079-81; Fig. 1]); and
a processor (O’Gorman: a unified activity map generation circuit 104, which can include a CPU comprised of one or more processors [¶0080; Fig. 1]). Thus, in accordance with the KSR rationales (see MPEP § 2143), the prior art includes all of the claimed elements in the present application, with the only difference being the lack of combination. Furthermore, one of ordinary skill in the art could have easily combined the elements by known methods and that each element would merely perform the same function as it does separately. Furthermore, one of ordinary skill would recognize that the combination would be predictable, as utilizing the base device and disclosed LAN of O’Gorman would allow one to execute the video analytics program disclosed by IVA in view of Li to observe and analyze a traffic scene in real-time.
Allowable Subject Matter
Claims 9 & 10 would be allowable if rewritten to overcome the rejection(s) under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), 2nd paragraph, set forth in this Office action and to include all of the limitations of the base claim and any intervening claims.
Concerning claim 9, the currently cited prior art fail to teach a selection window “wherein information is selectable through the information selection window is determined according to a type of the region of interest.” While the closest prior art, IVA disclose a plurality of selection windows, none of them are configured to offer a user to select according to a particular type of region of interest. Whiting et al (US 9460613 B1) is analogous art pertinent to the field of endeavor and teach distinct pedestrian and vehicle detection zones that are able to be selected or drawn on by a user, however there is no recitation about an interface for selecting zone type specific information. For these listed reasons, no prior art of record teaches towards the invention described in claim 9 as a whole.
Accordingly, claim 10 would be allowable for its dependency on the allowable subject matter disclosed in claim 9.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Whiting et al (US 9460613 B1) disclose detection and analysis system for obtaining information about pedestrians and vehicles in user-designated regions of interest.
Cardona et al (US 2023/0377078 A1) disclose a system for displaying various kinds of information like incident risk via surveilling road segments.
Venetianer et al (US 2004/0105570 A1) teach a GUI for assigning video tripwires to obtain movement information of objects passing through an image region in real time.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Michael M. Sofroniou whose telephone number is (571)272-0287. The examiner can normally be reached M-F: 8:30 AM - 5:00 PM.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, John M. Villecco can be reached at (571) 272-7319. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/MICHAEL M SOFRONIOU/Examiner, Art Unit 2661
/JOHN VILLECCO/Supervisory Patent Examiner, Art Unit 2661
Prosecution Insights