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 .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on October 23, 2024 complies with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
35 USC § 101 Statutory Analysis
The claims do not recite any of the judicial exceptions enumerated in the 2019 Revised Patent Subject Matter Eligibility Guidance. Further, the claims do not recite any method of organizing human activity, such as a fundamental economic concept or managing interactions between people. Finally, the claims do not recite a mathematical relationship, formula, or calculation. Thus, the claims are eligible because they do not recite a judicial exception.
Claim Rejections - 35 USC § 102
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 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 the appropriate paragraphs of 35 U.S.C. §102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1-20 are rejected under 35 U.S.C. §102(a)(1) as being anticipated by Wang et al. (U.S. Patent Application Publication No. US 2016/0133025 A1) (hereafter referred to as “Wang”).
With regard to claim 1, Wang describes receiving an image captured by a camera (see Figure 9, element 910 and refer for example to paragraph [0103]); converting an input received by a user to a location of a plurality of partial regions in the image (refer for example to paragraphs [0027] through [0029] and [0031]), rotation angle of the objects in each of the plurality of the partial regions (refer for example to paragraphs [0065] and [0071]), and a size of the plurality of the partial regions (refer for example to paragraphs [0032] and [0033]), the plurality of partial regions associated with at least one label name (refer for example to paragraphs [0048] through [0054], where the LBP code of the cells or corresponds to applicant’s “plurality of partial regions associated with at least one label name”); generating a structure information associated the at least one label name, the structure information comprising the location, the rotation angle and the size of the plurality of the partial region, the structure information associated with the image (refer for example to paragraphs [0032] and [0033] which describe dividing the image into cells with a predetermined size, refer to paragraphs [0027] through [0029] and [0031] which describe the location or position, refer to paragraphs [0065] and [0071] which describe the rotation angle of the objects in each of the plurality of the partial regions, refer for example to paragraphs [0032] and [0033] which describe the size of the plurality of the partial regions, and refer to paragraphs [0048] through [0054] which describe the plurality of partial regions associated with at least one label name, where the LBP code of the cells or corresponds to applicant’s “plurality of partial regions associated with at least one label name”, all of which describe “the structure information associated with the image); and outputting the structure information (see Figure 9, element 930 and refer for example to paragraph [0103]).
As to claim 2, Wang describes wherein the location contained in the structure information is indicated by a central coordinate of the partial region in the image (refer for example to paragraph [0028] and [0029]).
In regard to claim 3, Wang describes wherein the location is indicated by a peak coordinate of the partial region in the image (refer to paragraph [0028] and [0029].
With regard to claim 4, Wang describes wherein the object is a person or a vehicle (refer for example to paragraphs [0041], [0044], [0047] and [0048] which discuss that the object is a person in the crowd).
As to claim 5, Wang describes wherein the location, the rotation angle and the size are indicated by the input (refer for example to paragraphs [0027] through [0029] and [0031]), rotation angle of the objects in each of the plurality of the partial regions (refer for example to paragraphs [0065] and [0071]), and a size of the plurality of the partial regions (refer for example to paragraphs [0032] and [0033]).
In regard to claim 6, Wang describes wherein the conversion of the input comprises converting each of a plurality of the input to each of a plurality of the location, each of a plurality of the rotation angles and each of a plurality of the size (refer for example to paragraphs [0032], [0033], [0065] and [0071]).
With regard to claim 7, Wang describes wherein the input is an operation in the image displayed by a display device (see Figure 9, element 930 and refer for example to paragraph [0103]).
As to claim 8, Wang describes wherein one of the objects is a head (refer for example to paragraphs [0041] and [0044]), and wherein the input indicates a rotation angle of the head included in the image (refer for example to paragraph [0071]).
In regard to claim 9, Wang describes wherein the output of the structure information comprises outputting the structure information as training data for training a model to detect an object in an image (refer for example to paragraph [0047] and to paragraphs [0051] through [0055]).
With regard to claim 10, Wang describes at least one memory storing instructions and at least one processor configured to execute the instructions to perform operations (see Figure 9, element 920 and refer for example to paragraph [0103]) comprising receiving an image captured by a camera (see Figure 9, element 910 and refer for example to paragraph [0103]); converting an input received by a user to a location of a plurality of partial regions in the image (refer for example to paragraphs [0027] through [0029] and [0031]), rotation angle of the objects in each of the plurality of the partial regions (refer for example to paragraphs [0065] and [0071]), and a size of the plurality of the partial regions (refer for example to paragraphs [0032] and [0033]), the plurality of partial regions associated with at least one label name (refer for example to paragraphs [0048] through [0054], where the LBP code of the cells or corresponds to applicant’s “plurality of partial regions associated with at least one label name”); generating a structure information associated the at least one label name, the structure information comprising the location, the rotation angle and the size of the plurality of the partial region, the structure information associated with the image (refer for example to paragraphs [0032] and [0033] which describe dividing the image into cells with a predetermined size, refer to paragraphs [0027] through [0029] and [0031]) which describe the location or position, refer to paragraphs [0065] and [0071] which describe the rotation angle of the objects in each of the plurality of the partial regions, refer for example to paragraphs [0032] and [0033] which describe the size of the plurality of the partial regions, and refer to paragraphs [0048] through [0054] which describe the plurality of partial regions associated with at least one label name, where the LBP code of the cells or corresponds to applicant’s “plurality of partial regions associated with at least one label name”, all of which describe “the structure information associated with the image); and outputting the structure information (see Figure 9, element 930 and refer for example to paragraph [0103]).
As to claim 11, Wang describes wherein the location contained in the structure information is indicated by a central coordinate of the partial region in the image (refer for example to paragraph [0028] and [0029]).
In regard to claim 12, Wang describes wherein the conversion of the input comprises converting each of a plurality of the input to each of a plurality of the location, each of a plurality of the rotation angles and each of a plurality of the size (refer for example to paragraphs [0032], [0033], [0065] and [0071]).
With regard to claim 13, Wang describes wherein the input is an operation in the image displayed by a display device (see Figure 9, element 930 and refer for example to paragraph [0103]).
As to claim 14, Wang describes wherein one of the objects is a head (refer for example to paragraphs [0041] and [0044]), and wherein the input indicates a rotation angle of the head included in the image (refer for example to paragraph [0071]).
In regard to claim 15, Wang describes wherein the output of the structure information comprises outputting the structure information as training data for training a model to detect an object in an image (refer for example to paragraph [0047] and to paragraphs [0051] through [0055]).
With regard to claim 16, Wang describes a non-transitory computer-readable medium storing a program causing a computer to execute a control method (see Figure 9, element 920 and refer for example to paragraph [0103]), the control method comprising receiving an image captured by a camera (see Figure 9, element 910 and refer for example to paragraph [0103]); converting an input received by a user to a location of a plurality of partial regions in the image (refer for example to paragraphs [0027] through [0029] and [0031]), rotation angle of the objects in each of the plurality of the partial regions (refer for example to paragraph [0065]), and a size of the plurality of the partial regions (refer for example to paragraph [0032]), the plurality of partial regions associated with at least one label name (refer for example to paragraphs [0048] through [0054], where the LBP code of the cells or corresponds to applicant’s “plurality of partial regions associated with at least one label name”); generating a structure information associated the at least one label name, the structure information comprising the location, the rotation angle and the size of the plurality of the partial region, the structure information associated with the image (refer for example to paragraphs [0032] and [0033] which describe dividing the image into cells with a predetermined size, refer to paragraphs [0027] through [0029] and [0031]) which describe the location or position, refer to paragraph [0065] and [0071] which describe the rotation angle of the objects in each of the plurality of the partial regions, refer for example to paragraphs [0032] and [0033] which describe the size of the plurality of the partial regions, and refer to paragraphs [0048] through [0054], which describe the plurality of partial regions associated with at least one label name, where the LBP code of the cells or corresponds to applicant’s “plurality of partial regions associated with at least one label name”, all of which describe “the structure information associated with the image); and outputting the structure information (see Figure 9, element 930 and refer for example to paragraph [0103]).
As to claim 17, Wang describes wherein the conversion of the input comprises converting each of a plurality of the input to each of a plurality of the location, each of a plurality of the rotation angles and each of a plurality of the size (refer for example to paragraphs [0032], [0033], [0065] and [0071]).
In regard to claim 18, Wang describes wherein the input is an operation in the image displayed by a display device (see Figure 9, element 930 and refer for example to paragraph [0103]).
With regard to claim 19, Wang describes wherein one of the objects is a head (refer for example to paragraphs [0041] and [0044]), and wherein the input indicates a rotation angle of the head included in the image (refer for example to paragraph [0071]).
As to claim 20, Wang describes wherein the output of the structure information comprises outputting the structure information as training data for training a model to detect an object in an image (refer for example to paragraph [0047] and to paragraphs [0051] through [0055]).
Relevant Prior Art
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Hotta (‘934), (‘027), (‘924) and (‘266), Liu, Wang, and Oami all disclose systems similar to applicant’s claimed invention.
Contact Information
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Jose L. Couso whose telephone number is (571) 272-7388. The examiner can normally be reached on Monday through Friday from 5:30am to 1:30pm.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Matthew Bella, can be reached on 571-272-7778. The fax phone number for the organization where this application or proceeding is assigned is (571) 273-8300.
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/JOSE L COUSO/Primary Examiner, Art Unit 2667
May 7, 2026
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