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 .
Priority
Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
Claim Objections
Claims 1 and 15 are objected to because of the following informalities: there should be an instance of the term “and” following the last semicolon in each claim and the “extracting”/“extract” step that follows the “if” clause should be amended to more clearly relate to the “if” clause instead of being recited as a separate step. See paragraph 31 of the specification. For example, “processing settings; extract one or more updated first feature vectors; compare” in claim 15 could be changed to “processing settings[[;]] and extract one or more updated first feature vectors; and compare”.
Appropriate correction is required.
Claim Rejections - 35 USC § 112
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.
Claims 1-15 are rejected under 35 U.S.C. 112(b) as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor regards as the invention.
Claim 1 recites “A computer-implemented method for determining similarity in appearance of objects in image frames of at least one video sequence, the method comprising: ... extracting, from the first image area, one or more first feature vectors describing the appearance of the first object; ... extracting, from the second image area, one or more second feature vectors describing the appearance of the second object” (emphasis added). Claim 15 recites substantially similar limitations in the body thereof and does not recite any “appearance” in the preamble like claim 1. Both “the appearance of the first object” and “the appearance of the second object” lack a proper antecedent basis because claim 15 provides no antecedent basis at all and the preamble of claim 1 does not clarify which appearance specifically corresponds to each of the first and second appearances being claimed. For purposes of applying prior art, “the appearance” is interpreted as “[[the]] an appearance”. Dependent claims 2-14 are rejected for inheriting and not curing the deficiencies of claim 1.
Claims 1 and 15 recite extracting “one or more updated first feature vectors” (emphasis added). It is not clear which feature vectors correspond to the “updated first feature vectors”. The preceding step of re-processing the first raw image data is not recited as explicitly generating or producing any updated feature vectors. For purposes of applying prior art, the re-processing is interpreted as generating the updated first feature vectors which are subsequently extracted and compared to the one or more second feature vectors. Dependent claims 2-14 are rejected for inheriting and not curing the deficiencies of claim 1.
Claim 8 recites “the step of extracting one or more first feature vectors and/or extracting one or more second feature vectors comprises applying a machine learning model, such as a neural network” and claim 11 recites “wherein the first image processing settings and second image processing settings comprise settings related to gain and/or exposure compensation and/or white balance and/or color adjustment, such as local tone mapping” (emphasis added). The phrase “such as” renders the claims indefinite because it is unclear whether the limitations following the phrase, i.e., “neural network” and “local tone mapping”, are part of the claimed inventions of claims 8 and 11. See MPEP § 2173.05(d). Using the language “such as” amounts to merely providing an example without concretely and positively reciting an additional limitation. For purposes of applying prior art, the phrases “a machine learning model, such as a neural network” and “color adjustment, such as local tone mapping” are interpreted as “a machine learning model, the machine learning including a neural network” and “a color adjustment setting,the color adjustment setting including a local tone mapping”. Dependent claim 9 is rejected for inheriting and not curing the deficiencies of claim 8.
Claim 11 recites “wherein the first image processing settings and second image processing settings comprise settings related to gain and/or exposure compensation and/or white balance and/or color adjustment, such as local tone mapping” (emphasis added). On its face, the phrase “related to” implies that the first image processing settings and second image process settings do not include gain, exposure compensation, white balance, color adjustment, and/or tone mapping, but instead include some unspecified setting(s) that is/are merely “related” to such settings. However, the claims do not provide sufficient context to understand the meaning of “related”. Paragraph 31 of the specification describes these settings as examples of processing settings, however there is no explanation found in the specification to explain the meaning of “related to” in the context of claim 11. Accordingly, the specification indicates that these settings are the possible processing settings. Therefore, for purposes of prior art, claim 11 is interpreted as reciting “wherein the first image processing settings and second image processing settings comprise settings including a gain setting and/or an exposure compensation setting and/or a white balance setting and/or a color adjustment setting, the color adjustment setting including a local tone mapping”.
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.
Claim 14 is rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. The claim does not fall within at least one of the four categories of patent eligible subject matter because it is not directed to a process, machine, manufacture, or composition of matter.
Software expressed as code or a set of instructions detached from any medium is an idea without physical embodiment. See Microsoft Corp. v. AT&T Corp., 550 U.S. 437, 449, 82 USPQ2d 1400, 1407 (2007); see also Benson, 409 U.S. 67, 175 USPQ2d 675 (An "idea" is not patent eligible). The MPEP provides a list of non-limiting examples of claims that are not directed to any of the statutory categories including products that do not have a physical or tangible form, such as information (often referred to as “data per se”) or a computer program per se (often referred to as “software per se”) when claimed as a product without any structural recitations. MPEP 2106.03, subsection I.
Claim 14 recites “A computer program having instructions which, when executed by a computing device or computing system, cause the computing device or computing system to carry out the method for determining similarity in appearance of objects according to claim 1” (emphasis added). Claim 1 is directed to “A computer-implemented method” comprising a series of steps, which constitutes a program method or set of instructions in the context of claim 14. Under the broadest reasonable interpretation, claim 14 is thus directed to a computer program per se where the instructions thereof correspond to the method steps of claim 1. Therefore, claim 14 is not eligible.
To necessitate withdrawal of the rejection, the examiner recommends amending claim 14 to recite “A non-transitory computer-readable medium storing a computer program having instructions which, when executed by a computing device or computing system, cause the computing device or computing system to carry out the method for determining similarity in appearance of objects according to claim 1.” Support for the suggested amendment is found in paragraphs 37 and paragraph 43 of the specification, which respectively disclose that the “computer program may be stored on any suitable type of storage media, such as non-transitory storage media” and that the “system may include one or more memory units, such as a random access memory (RAM) and/or a read-only memory (ROM), or any suitable type of memory.”
Allowable Subject Matter
Claims 1 and 15 would be allowable if rewritten to overcome the objections for minor informalities and the rejections under 35 U.S.C. 112(b) set forth in this Office action.
Claims 2-13 would be allowable if rewritten to overcome the rejections under 35 U.S.C. 112(b) set forth in this Office action, to include all of the limitations of the base claim and any intervening claims and to cure the objection for minor informalities set forth in this Office action with respect to the subject matter of claim 1.
Claim 14 would be allowable if rewritten to overcome the rejection sunder 35 U.S.C. 101 and the rejections under 35 U.S.C. 112(b) set forth in this Office action, to include all of the limitations of the base claim and any intervening claims and to cure the objection for minor informalities set forth in this Office action with respect to the subject matter of claim 1.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
U.S. Pat. Appl. Pub. No. 20170091439 to Sharma et al. discloses a method comprising processing raw image data (par. 31, “The acceptable value threshold may be defined, for example, based on a percentage or other comparison to an initial calculated confidence value, or based on particular measured parameter from the sensor data.” A “raw” image is an image captured directly by an image sensor.) and determining if the one or more first feature vectors and the one or more second feature vectors (par. 85, “ReID-feature vectors ReID1 to ReIDN”) differ by more than a first threshold, and if the first image processing settings differ from the second image processing settings by more than a second threshold (par. 31, “The acceptable value threshold may be defined, for example, based on a percentage or other comparison to an initial calculated confidence value, or based on particular measured parameter from the sensor data. For example, in one or more embodiments, the acceptable value threshold may be defined as a function of one or more types of sensor data, or may be different based on the types or values of sensor data monitored.”, par. 97, “Between the frames 412 and 416, the luminance, or color mapping, tone, or resolution has changed, whereby the appearance or image conditions of the image crop 418 is different from those of crop 416”. The acceptable value threshold may be defined by a confidence or a measured parameter such as ambient lighting, where a lower confidence corresponds to a difference in ambient lighting between sensor data from two sequentially-captured images, e.g., a first login image and a subsequent, second login image. See Sharma at par. 22.). However, Sharma does not teach every feature of pending independent claims of the instant application.
U.S. Pat. Appl. Pub. No. 20230119685 to Kim et al. discloses processing raw image data and comparing extracted features to a first threshold to determine a degree of overlap and a second threshold to determine a similarity, which is related to the raw image processing of the independent claims. See Kim et al. at Figure 2.
Deep learning based occluded person re-identification: A survey to Peng et al. is pertinent because the pending claims are a particular application of person re-identification and the survey cites relevant developments in the field of occluded person re-identification.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to RYAN P POTTS whose telephone number is (571)272-6351. The examiner can normally be reached M-F, 9am-5pm EST.
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/RYAN P POTTS/Examiner, Art Unit 2672
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