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 .
Oath/Declaration
The receipt of the Oath/Declaration is acknowledged.
Drawings
The drawing(s) filed on July 26, 2023 are accepted by the Examiner.
Status of Claims
Claims 16-35 are pending in this application.
Priority
Receipt is acknowledged of papers submitted under 35 U.S.C. 119(a)-(d), which papers have been placed of record in the file.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on July 26, 2023 is in compliance with the provisions on 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Claim Amendments
Acknowledgment of receiving amendments to the claims, which were received by the Office on 11/05/2025.
Response to Arguments Applicant's arguments filed 11/05/2025 have been fully considered but they are not fully persuasive.
Regarding the 335 USC § 101 Rejections, the applicant’s arguments are persuasive and the 101 Rejection is withdrawn.
Applicant’s Remarks Pertaining to the Art Rejections:
In the remarks, applicant argues in substance:
Applicant argues: “Brown does not disclose each and every element recited in claim 16. For example, for at least the reasons described below, Brown fails to disclose "wherein the variance analysis comprises an Albedo variance analysis" as recited in claim 16.
Claim 16 has been amended to include features of original claim 20, reciting "the variance analysis comprises an Albedo variance analysis." While the Office Action rejected claim 20 over Brown, Brown does not teach or suggest Albedo-variance-based classification. The Office cites Brown paras. 49-50 for "variance" (Office Action, Page 12, lines 14-17), but Brown describes variance as part of a multi-pixel reflectance modeling with spatial analysis and region extraction, not temporal variance of Albedo intensity as a discriminant.
Brown assumes an image region corresponding to the object can be segmented and its appearance analyzed (Brown paras. 25, 47-55). Paragraph 25 of Brown explicitly processes "plurality of video frames" with region-level tracking. Brown's "variance" relates to surface reflectance modeling across multiple pixels, not temporal intensity variation usable for classification when spatial resolution may be insufficient for segmentation.
In contrast, the claimed Albedo variance analysis enables classification regardless of reliable spatial segmentation, including where the object occupies only a few pixels and spatial shape/texture cues may not be robustly available (see, for example, Fig. 3 of the original application). This capability is not present in Brown. Thus, Brown does not disclose the recited Albedo variance analysis. Accordingly, because Brown fails to disclose each and every feature of claim 16, Brown is not sufficient to establish a prima facie anticipation rejection of claim 16. Although of different scope than claim 16, independent claims 31 and 35 are patentable over Brown for at least the same reasons presented with respect to claim 16.
Examiner’s Response: Examiner respectfully disagrees with Applicant’s line of reasoning. The Examiner has thoroughly reviewed the Applicant arguments but respectfully believes that the cited reference to reasonably and properly meet the claimed limitations. 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)).
With regard to the applicant’s argument concerning “temporal intensity variation” on page 10, the claims as currently presented do not recite “temporal intensity variation.” Accordingly, it appears the applicant is improperly importing the specification into the claims.
Further regarding the 103 rejections, Appellants’ argument does not address the actual reasoning of the Examiner’s rejections. Instead Appellants attack the references singly for lacking teachings that the Examiner relied on a combination of references to show. It is well established that one cannot show nonobviousness by attacking references individually where the rejections are based on combinations of references (See In re Keller, 642 F.2d 413, 425 (CCPA 1981); In re Merck & Co., 800 F.2d 1091 (Fed. Cir. 1986)). The court requires that references must be read, not in isolation, but for what they fairly teach in combination with the prior art as a whole (Merck, 800 F.2d at 1097 (Fed. Cir. 1986)).
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) 16-17, 21, 23, 26-28, 30-31 and 35-42 are rejected under 35 U.S.C. 103 as being unpatentable over Brown et al. (US 2012/0257793 A1) herein after known as Brown in view of Sloan et al. (US 2015/0346031) herein after known as Sloan.
Regarding claim 16, Brown teaches a method for classification of objects in images (Brown, Figure 1, Methodology 100, paragraph 0025), the method comprising:
obtaining a plurality of temporally sequential images (Brown, Figure 1, step 102, ‘plurality of video frames’, paragraph 0025);
detecting at least one object of interest in the images (Brown, Figure 1, step 102, before the tracking the object is necessarily detected, paragraph 0025);
matching at least one detected object of interest across the plurality of the images (Brown, Figure 1, step 102, tracking, paragraph 0025) ;
applying variance analysis on the object between the temporally sequential images (Brown, paragraphs 49-50, ‘variance’); and
based on variance analysis output (Brown, paragraphs 46-55, classification is based on variance analysis output), assigning at least one label to the object of interest (Brown, Figure 1, paragraph 25, Figure 1, step 103, paragraph 47 ‘class label’), wherein the obtaining the plurality of temporally sequential images comprises tracking and following the object in an automated manner (Brown, paragraph [0003, 0004, 0010, 0036], automated tracking).
While Brown teaches ({Surface Albedo is defined as the ratio of radiosity to the irradiance (flux per unit area) received by a surface.} So, in the context of Brown, the Albedo variance analysis is taught in paragraphs 49 and 50.), Brown does not explicitly teach wherein the variance analysis comprises an Albedo variance analysis.
In reference Sloan, Sloan teaches an optical imaging system wherein the variance analysis comprises an Albedo variance analysis (Sloan, paragraph [0085, 0088-0090).
These arts are analogous since they are both related to video imaging devices. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention (AIA ) to modify the invention of Brown with wherein the variance analysis comprises an Albedo variance analysis as seen in Sloan to provide a single satellite that can detect atmospheric trace gas emissions from a single target location in a single pass as taught by Sloan in paragraph 0008.
Regarding claim 17, the combination of Brown and Sloan teaches the method according to claim 16, wherein the label identifies the object as at least one of an animate object or an inanimate object (Brown paragraph 21, …to the classification of any object (e.g., animate or inanimate)…, and paragraph 47).
Regarding claim 21, the combination of Brown and Sloan teaches the method according to claim 16, wherein the Albedo variance analysis is a surface Albedo analysis ({Surface Albedo is defined as the ratio of radiosity to the irradiance (flux per unit area) received by a surface.} So, in the context of Brown, the Albedo variance analysis is taught in paragraphs 49 and 50.).
Regarding claim 23, the combination of Brown and Sloan teaches the method according to claim 17, wherein a differentiation between the animate object and the inanimate object is performed by the Albedo variance analysis, caused by morphing or unmorphing shapes ({Surface Albedo is defined as the ratio of radiosity to the irradiance (flux per unit area) received by a surface.} So, in the context of Brown, the Albedo variance analysis is taught in paragraphs 21, 23 {… “level of deformation” … degree of change in the form (i.e. shape) of an object.}, 47 and 49-55 and Sloan, paragraph [0085, 0088-0090)).
Regarding claim 26, the combination of Brown and Sloan teaches the method according to claim 16, wherein the applying the Albedo variance analysis comprises applying the Albedo variance analysis in a statistical manner ({Surface Albedo is defined as the ratio of radiosity to the irradiance (flux per unit area) received by a surface.} So, in the context of Brown, the Albedo variance analysis is taught in paragraphs 49 and 50 and Sloan, paragraph [0085, 0088-0090).
Regarding claim 27, the combination of Brown and Sloan teaches the method according to claim 16, wherein applying the Albedo variance analysis comprises applying the Albedo variance analysis in a time-dependent manner ({Surface Albedo is defined as the ratio of radiosity to the irradiance (flux per unit area) received by a surface.} So, in the context of Brown, the Albedo variance analysis is taught in paragraphs 49 and 50 and Sloan, paragraph [0085, 0088-0090).
Regarding claim 28, the combination of Brown and Sloan teaches the method according to claim 16, wherein the images are captured by pixel array image sensors and the variance analysis comprises the detection and/or measurement of light and/or light reflection by the pixel array image sensors over time ({Surface Albedo is defined as the ratio of radiosity to the irradiance (flux per unit area) received by a surface.} So, in the context of Brown, the Albedo variance analysis is taught in paragraphs 49 and 50.).
Regarding claim 30, the combination of Brown and Sloan teaches the method according to claim 16, further comprising: prior to obtaining the images, recording a video of surroundings with at least one camera, wherein the temporally sequential images comprise consecutive frames of the video (Brown, Figure 2 and paragraphs 25, 33, 41).
Claim 31 is rejected for the same reasons as claim 16.
Claim 32 is rejected for the same reasons as claim 17.
Claim 35 is rejected for the same reasons as claim 16.
Regarding claim 36, the combination of Brown and Sloan teaches the method according to claim 16, wherein the obtaining the plurality temporally sequential images comprises tracking and following the object in an automated manner by a camera that is configured to move accordingly (Brown, paragraph [0003, 0004, 0010, 0036], automated tracking).
Regarding claim 37, the combination of Brown and Sloan teaches the method according to claim 16, wherein the obtaining the plurality of temporally sequential images comprises tracking and following the object in an automated manner by a camera that is adjusted in its location and configured to move (Brown, paragraph [0003, 0004, 0010, 0036], automated tracking) (Brown, paragraph [0003, 0004, 0010, 0036], automated tracking).
Regarding claim 38, the combination of Brown and Sloan teaches the method according to claim 16, wherein the obtaining the plurality of temporally sequential images comprises tracking and following the object in an automated manner by a camera that is configured to move in position and/or to tilt and turn according to the tracked object (Brown, paragraph [0003, 0004, 0010, 0036], automated tracking).
Regarding claim 39, the combination of Brown and Sloan teaches the method according to claim 16, wherein the obtaining the plurality of temporally sequential images comprises tracking and following the object in an automated manner by a camera with an adjustable focal length (Brown, paragraph [0003, 0004, 0010, 0036], automated tracking).
Regarding claim 40, the combination of Brown and Sloan teaches the method according to claim 16, further comprising irritating and/or destroying the object of interest in case an inanimate object is identified (Brown, paragraph [0036], background subtraction).
Regarding claim 41, the combination of Brown and Sloan teaches the method according to claim 40, wherein the irritating and/or destroying the object of interest is performed with a laser effector (Brown, paragraph [0036], background subtraction) .
Regarding claim 42, the combination of Brown and Sloan teaches the method according to claim 41, wherein the images are provided by a camera and wherein the laser effector and the camera are coupled (Brown, paragraph [0036], background subtraction).
Claim(s) 18 is rejected under 35 U.S.C. 103 as being unpatentable over Brown et al. (US 2012/0257793 A1) herein after known as Brown in view of Sloan et al. (US 2015/0346031) herein after known as Sloan and further in view of Rasheed et al. (US 2016/0165191 A1) herein after known as Rasheed.
Regarding claim 18, the combination of Brown and Sloan teaches the method according to claim 17, but does not clearly teach wherein the inanimate object comprises an unmanned aerial vehicle.
In reference Rasheed, Rasheed teaches wherein the inanimate object comprises an unmanned aerial vehicle (Rasheed, Figure 1, surveillance system 100, paragraph 23, … the visual surveillance system 100, may include an aerial surveillance system (e.g., an airplane, a drone…), paragraph 24, …where the visual surveillance system 100 part of a moving apparatus (e.g., an unmanned arial vehicle or “UAV”)…).
These arts are analogous since they are both related to video imaging devices. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention (AIA ) to modify the invention of Brown and Sloan with wherein the inanimate object comprises an unmanned aerial vehicle as seen in Rasheed to provide more in-depth analysis of an object by measuring position, velocity, acceleration, orientation, trajectory, etc. of an object as taught by Rasheed in paragraph 24.
Claim(s) 29 is rejected under 35 U.S.C. 103 as being unpatentable over Brown et al. (US 2012/0257793 A1) herein after known as Brown in view of Sloan et al. (US 2015/0346031) herein after known as Sloan and further in view of Lai et al. (US 2020/0184260 A1) herein after known as Lai.
Regarding claim 29, the combination of Brown and Sloan teaches the method according to claim 16, but does not clearly teach wherein the variance analysis has been trained by a convolutional neural network (CNN) for providing the label.
In reference Lai, Lai teaches wherein the variance analysis has been trained by a convolutional neural network (CNN) for providing the label (Lai paragraphs 27-28).
These arts are analogous since they are both related to video imaging devices used for object detection. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention (AIA ) to modify the invention of Brown and Sloan with wherein the variance analysis has been trained by a convolutional neural network (CNN) for providing the label as seen in Lai to increase the number of identifiable objects as taught by Lai in paragraph 28.
Conclusion
THIS ACTION IS MADE FINAL. 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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HASKINS whose telephone number is (571)272-7406. The Supervisory Patent
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/TWYLER L HASKINS/Supervisory Patent Examiner, Art Unit 2639