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
The present application is a 371 application of PCT/JP2023/018213 filed on 05/16/2023 and claims benefit of foreign application JP 2022-088289 filed on 05/31/2022. Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
Information Disclosure Statement
The information disclosure statement(s) (IDS) submitted on 11/22/2024 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Specification
The abstract of the disclosure is objected to because it is presented in two paragraphs. The abstract should be in narrative form and generally limited to a single paragraph within the range of 50 to 150 words in length.
A corrected abstract of the disclosure is required and must be presented on a separate sheet, apart from any other text. See MPEP § 608.01(b) for guidelines for the preparation of patent abstracts.
The title of the invention is not descriptive. A new title is required that is clearly indicative of the invention to which the claims are directed.
The following title is suggested: “Scene Analysis Apparatus, Method, and Program for Selecting a Recognition Model”.
The lengthy specification has not been checked to the extent necessary to determine the presence of all possible minor errors. Applicant’s cooperation is requested in correcting any errors of which applicant may become aware in the specification.
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) are: “selection unit” in claims 1 and 20, and “generation unit” in claim 8.
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.
The “selection unit” structure is interpreted under 35 U.S.C. 112(f). The corresponding structure is a processor programmed to implement recognition engine selection unit 143 according to the disclosed recognition engine selection algorithm(s) corresponding to the recited function(s) (see, e.g., FIGs 10, 11, and 61), and equivalents thereof.
The “generation unit” structure is interpreted under 35 U.S.C. 112(f). The corresponding structure is a processor programmed to implement operation history analysis unit 142 according to the disclosed operation state information generation algorithm(s) corresponding to the recited function(s) (see, e.g., FIGs 10 and 61-64), and equivalents thereof.
These interpretations apply throughout the rejections below wherever the respective limitations are recited.
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
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 17-18 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.
Regarding claim 17, the term “clear” in the limitation “a clear point at which a change in a scene is clear” in claim 17 is a relative term which renders the claim indefinite. Although the specification gives examples of a “clear point,” such as “a position (frame) where the camera SW is performed or a position where the replay-in graphic appears” (¶ [0806] of the application’s pre-grant publication, US 2025/0336200 A1; see also FIG. 61), it does not provide an objective standard for determining when another scene change is sufficiently “clear” to fall within the scope of the claim. The learning model embodiment also uses training data in which a “clear point” is designated as the IN point or OUT point and distinguishes this data from cases where “a point other than the clear point” is designated (¶ [0880]-[0881] of the application’s pre-grant publication, US 2025/0336200 A1), but does not provide an objective standard for determining which scene change points qualify as “clear.” Accordingly, the scope of “a clear point at which a change in a scene is clear” cannot be determined with reasonable certainty. See MPEP § 2173.05(b).
For purposes of the prior art search and examination, “a clear point at which a change in a scene is clear” is interpreted, as best understood in view of the specification, as a point associated with an obvious scene change, such as a camera switch/cut or the appearance of a replay graph (see, e.g. ¶ [0806] and FIG. 61of the instant application’s pre-grant publication, US 2025/0336200 A1). The claim was searched under this interpretation and analogous scene boundary concepts. This interpretation doesn’t resolve the indefiniteness discussed above.
Claim 18 is also indefinite for being dependent on indefinite claim 17. Accordingly, claim 18 is rejected under 35 U.S.C. 112(b).
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(s) 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The limitations, under their broadest reasonable interpretation, cover mental process (concept performed in a human mind, including as observation, evaluation, judgment, opinion, organizing human activity and mathematical concepts and calculations). The claim(s) recite(s) steps for selecting a recognition unit from a plurality of recognition units, on a basis of a state of an operation of a user, to be used for recognition processing on content. This judicial exception is not integrated into a practical application because the steps do not add meaningful limitations to be considered specifically applied to a particular technological problem to be solved. The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the steps of the claimed invention can be done mentally and no additional features in the claims would preclude them from being performed as such except for the generic computer elements at high level of generality (e.g. processor, memory, operating system, etc.).
According to the USPTO guidelines, a claim is directed to non-statutory subject matter if:
STEP 1: the claim does not fall within one of the four statutory categories of invention (process, machine, manufacture or composition of matter), or
STEP 2: the claim recites a judicial exception, e.g. an abstract idea, without reciting additional elements that amount to significantly more than the judicial exception as determined using the following analysis:
STEP 2A (PRONG 1): Does the claim recite an abstract idea, law of nature, or natural phenomenon?
STEP 2A (PRONG 2): Does the claim recite additional elements that integrate the judicial exception into a practical application?
STEP 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception?
Using the two-step inquiry, it is clear that independent claims 1, 19, and 20 are directed to an abstract idea as shown below:
► STEP 1: Do the claims fall within one of the statutory categories?
YES. Claim 1 is directed to an apparatus (i.e. machine), claim 19 is directed to a method (i.e. process), and claim 20 is directed to a program that causes a physical computer to perform the recited functionality (i.e. manufacture).
► STEP 2A (PRONG 1): Is the claim directed to a law of nature, a natural phenomenon or an abstract idea?
Yes, the claims are directed toward a mental process and/or mathematical concepts (i.e. abstract idea).
With regard to STEP 2A (PRONG 1), the guidelines provide three groupings of subject
matter that are considered abstract ideas:
Mathematical concepts - mathematical relationships, mathematical formulas or
equations, mathematical calculations;
Certain methods of organizing human activity - fundamental economic principles or practices (including hedging, insurance, mitigating risk); commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations); managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions); and
Mental processes - concepts that are practicably performed in the human mind (including observation, evaluation, judgment, opinion).
Independent claim(s) 1, 19, and 20 comprise a mental process that can be practicably performed in the human mind (or generic computers or components configured to perform the method) and, therefore, an abstract idea.
Specifically, the claims recite evaluating the state of a user’s operation when designating a sample scene and selecting a recognition unit based on that evaluation. Such evaluation and selection constitute observations, evaluations, and judgements that can be performed in the human mind.
The limitations, as drafted in respective claims, are a simple process that, under their broadest reasonable interpretation, covers performance of the limitations in the mind or by a human. The Examiner notes that under MPEP 2106.04(a)(2)(III), the courts consider a mental process (thinking) that "can be performed in the human mind, or by a human using a pen and paper" to be an abstract idea. CyberSource Corp. v. Retail Decisions, Inc., 654 F.3d 1366, 1372, 99 USPQ2d 1690, 1695 (Fed. Cir. 2011). As the Federal Circuit explained, "methods which can be performed mentally, or which are the equivalent of human mental work, are unpatentable abstract ideas the 'basic tools of scientific and technological work' that are open to all."' 654 F.3d at 1371, 99 USPQ2d at 1694 (citing Gottschalk v. Benson, 409 U.S. 63, 175 USPQ 673 (1972)). See also Mayo Collaborative Servs. v. Prometheus Labs. Inc., 566 U.S. 66, 71, 101 USPQ2d 1961, 1965 ('"[M]ental processes[] and abstract intellectual concepts are not patentable, as they are the basic tools of scientific and technological work'" (quoting Benson, 409 U.S. at 67, 175 USPQ at 675)); Parker v. Flook, 437 U.S. 584,589, 198 USPQ 193, 197 (1978) (same).
The mere nominal recitation of a selection unit and recognition unit does not take the limitations out of the mental process grouping where the claims, under their broadest reasonable interpretation, encompass performance of the recited evaluation and selection in the human mind. See MPEP 2106.04(a)(2)(III). Thus, claims 1, 19, and 20 recite a mental process.
STEP 2A (PRONG 2): Does the claim recite additional elements that integrate the judicial exception into a practical application?
NO, the claims do not recite additional elements that integrate the judicial exception into a practical application.
With regard to STEP 2A (prong 2), whether the claim recites additional elements that integrate the judicial exception into a practical application, the guidelines provide the following exemplary considerations that are indicative that an additional element (or combination of elements) may have integrated the judicial exception into a practical application:
an additional element reflects an improvement in the functioning of a computer, or an improvement to other technology or technical field;
an additional element that applies or uses a judicial exception to affect a particular treatment or prophylaxis for a disease or medical condition;
an additional element implements a judicial exception with, or uses a judicial exception in conjunction with, a particular machine or manufacture that is integral to the claim;
an additional element effects a transformation or reduction of a particular article to a different state or thing; and
an additional element applies or uses the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception.
While the guidelines further state that the exemplary considerations are not an exhaustive list and that there may be other examples of integrating the exception into a practical application, the guidelines also list examples in which a judicial exception has not been integrated into a practical application:
an additional element merely recites the words "apply it" (or an equivalent) with the judicial exception, or merely includes instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea;
an additional element adds insignificant extra-solution activity to the judicial exception;
an additional element does no more than generally link the use of a judicial exception to a particular technological environment or field of use.
Independent claim(s) 1, 19, and 20 do not recite any of the exemplary considerations that are indicative of an abstract idea having been integrated into a practical application.
The additional elements, including the recited selection unit and recognition units, merely provide a technological environment in which the abstract idea is applied and do not impose a meaningful limit on the mental process. The claims do not require the selected recognition unit to perform recognition processing or otherwise achieve a particular technological improvement.
With respect to claim 20, merely causing a computer to implement the recited abstract idea does not integrate the exception into a practical application.
Accordingly, the claims are directed to the abstract idea.
STEP 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception?
NO, the claims do not recite additional elements that amount to significantly more than the judicial exception.
With regard to STEP 2B, whether the claims recite additional elements that provide significantly more than the recited judicial exception, the guidelines specify that the pre-guideline procedure is still in effect. Specifically, examiners should continue to consider whether an additional element or combination of elements:
adds a specific limitation or combination of limitations that are not well-understood, routine, conventional activity in the field, which is indicative that an inventive concept may be present; or
simply appends well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception, which is indicative that an inventive concept may not be present.
Independent claim(s) 1, 19, and 20 do not recite any additional elements that are not well understood, routine or conventional. The additional elements, considered individually and as an ordered combination, merely implement the abstract evaluation and selection and do not add significantly more to the judicial exception. With respect to claim 20, the recitation of a computer merely invokes a computer as a tool to perform the abstract idea and does not provide an inventive concept. Thus, claim(s) 1, 19, and 20 are not eligible subject matter under 35 U.S.C 101.
Regarding dependent claims 2-18, the additional limitations of claims 2-18 have been considered individually and in combination with the limitations of the claims from which they depend on, and they do not integrate the mental process into a practical application or add significantly more to the mental process.
Claim 2 further specifies selecting the recognition unit based on at least a moving speed, a moving direction, or a feature amount of movement of the user’s operation. These limitations merely further define the information observed and evaluated in making the selection and constitute observations and evaluations that can practically be performed in the human mind. Thus, claim 2 fails to remedy the abstract idea of claim 1.
Claim 3 further specifies selecting some recognition units among the plurality of recognition units. This limitation merely further defines the selection or judgement being made and does not integrate the abstract idea of claim 1 into a practical application. Thus, claim 3 fails to remedy the abstract idea of claim 1.
Claim 4 further specifies that the recognition units includes two or more of graphic, camera-switching, and excitement recognition units. These limitations merely limit the recognition units being selected to particular types of recognition units and provide a particular technological environment in which the abstract selection is applied. Thus, claim 4 fails to remedy the abstract idea of claim 1.
Claims 5-7 further specify which recognition unit is selected based on whether the user’s designation is made slowly, quickly, or otherwise. These limitations merely further define the observations, evaluations, and judgements in making the selection and can practically be performed in the human mind. Thus, claim 5-7 fail to remedy the abstract idea of claim 4.
Claim 8 adds a generation unit that generates operation state information based on an operation history of the operation of the user. This limitation amounts to gathering and evaluating information concerning the user’s prior operation and generating information representing that evaluation of information. Thus, claim 8 fails to remedy the abstract idea of claim 1.
Claim 9 further specifies classifying the user’s operation into patterns based on whether an IN or OUT point is designated as slowly or quickly. This limitation constitutes an evaluation and judgement concerning observed user behavior that can practically be performed in the human mind. Thus, claim 9 fails to remedy the abstract idea of claim 8.
Claims 10-13 further specify analyzing the operation history according to predetermined rules, including evaluating movement speed, comparing searching and designation speeds, calculating average speeds and differences therebetween, and comparing the resulting values with thresholds. These limitations merely further define the rules and calculations used to evaluate and classify the user’s operations and therefore constitute mental processes and, where applicable, mathematical concepts. Thus, claims 10-13 fail to remedy the abstract idea of claim 9.
Claims 14-15 further specify evaluating the number of changes in movement direction and comparing the number with predetermined thresholds to determine an operation state pattern. These limitations merely further define the observation, evaluation, and judgement used to classify the user’s operation and can practically be performed in the human mind. Thus, claims 14-15 fail to remedy the abstract idea of claim 10.
Claims 16-18 further specify analyzing the operation history using a learning model, including use of a time series of point position feature amounts to output a designation probability and comparison of the designation probability with a threshold to determine an operation state pattern. These limitations further automate the analysis and classification of the user’s operation but do not require an improvement to the learning model or computer functionality itself, nor do they require the selected recognition unit to subsequently perform recognition processing. Accordingly, the additional limitations do not integrate the abstract idea into a practical application or otherwise remedy the abstract idea of the claims from which they depend.
Thus, since claim(s) 1-20 are: (a) directed toward an abstract idea, (b) do not recite additional elements that integrate the judicial exception into a practical application, and (c) do not recite additional elements that amount to significantly more than the judicial exception, it is clear that Claim(s) 1-20 are not eligible subject matter under 35 U.S.C 101.
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 20 does not fall within at least one of the four categories of patent eligible subject matter because claim 20 is directed to a computer program, per se, which is not a process, machine, manufacture, or composition of matter. While claim 20 nominally recites a computer in the preamble, the computer is not positively recited in the body of the claims, nor is the computer required for the functioning of the claim.
One suggestion for overcoming this rejection would be to amend claim 20 to recite “A computer readable medium, storing a selection unit…”
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1-3, 8-11, 16, and 19-20 are rejected under 35 U.S.C. 103 as being unpatentable over Gunatilake (US 2012/0117046 A1) in view of Cormican (US 2020/0301965 A1).
Regarding claim 1,
Gunatilake teaches: An information processing apparatus (¶ [0025] “the apparatus and processes of the embodiments disclosed permit automatic analysis of multimedia data.”) comprising:
a selection unit that selects a recognition unit to be used for recognition processing on a content from a plurality of recognition units (Gunatilake teaches Controller layer 130 controlling the algorithm libraries and expressly states that “the Control layer selects the appropriate audio and video algorithms to perform the API task” (¶ [0044]-[0045]; see Controller 130 in FIG. 1). Gunatilake further teaches video and audio algorithm libraries 140 and 150 that “contain algorithms developed to support the scene search capability of the engine” (¶ [0044]), including algorithms for recognizing action scenes, low motion scenes, previewing frames, and dialogue/music scenes (FIG. 1; ¶ [0097] and ¶ [0108]). Accordingly, the Controller layer 130 reasonably corresponds to the claimed selection unit, the individual audio/video analysis algorithms reasonably correspond to the claimed recognitions units, and the multimedia/video analyzed by the algorithms reasonably correspond to the claimed content.)
[a user designating/selecting a scene or portion associated with] a sample of a scene to be cut from the content (Gunatilake teaches that “The user may skim through these [frames] using touch swipe gestures” and select frames (¶ [0097]). Gunatilake further teaches video editing wherein “the frames can be cropped, mixed, tagged with metadata, and saved” (¶ [0102]). Gunatilake teaches exemplary consumer uses, including producing customized trailers and advertisements (¶ [0098]). Accordingly, the user selected frames identify portions/scenes of interest, and the video sections defined by those frames and subsequently cropped correspond to a scene to be cut from the content.).
Gunatilake does not expressly teach selecting the recognition unit “on a basis of a state of an operation of a user when the user designates a sample scene”.
In a related art, Cormican teaches: determining the “state of an operation of a user” when the user designates/selects media content (Cormican teaches determining “the start and end point coordinates of the input and the speed of movement of the input” and distinguishes user gestures based on movement speed (¶ [0086]). Cormican further teaches determining, “based upon the starting position and the speed of movement of user gesture,” the media item the user is interested (¶ [0088]), and determining “user interest based upon the drag gesture speed” (¶ [0089]). Cormican therefore teaches using the state of the user’s operation when designating/selecting media content to determine the user’s intended media interest but does not explicitly teach using that operation state to select one of a plurality of recognition units.
In summary, Gunatilake teaches selecting a recognition unit, from a plurality of recognition units, according to the user’s desired scene-search processing and selecting frames defining video sections that may be cut/cropped, while Cormican teaches determining the user’s intended media interest from the state of the user’s media selection operation. Gunatilake and Cormican are related in that each references concern processing multimedia/video content to identify content or scenes of interest.
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the teachings of Gunatilake to select the recognition unit, taught by Gunatilake, based on the state of the user’s operation, as taught by Cormican, when the user designates/selects a scene of interest, in order to use the user’s operation state to determine the appropriate recognition processing for the user’s indicated scene interest. Doing so would predictably reduce manual interaction and time required to edit content (see Cormican ¶ [0017]), consistent with Gunatilake’s goal of reducing complexity through automation (see Gunatilake ¶ [0008]).
With respect to the 35 U.S.C. 112(f) interpretation of the claimed “selection unit,” see the Claim Interpretation section above. Gunatilake’s programmed computer structured Controller layer 130, as modified by Cormican to perform the operation state-based selection discussed above, would have rendered obvious the programmed computer structure and algorithm corresponding to the claimed “selection unit”.
Regarding claim 2,
Gunatilake in view of Cormican teach the information processing apparatus according to claim 1, including a “selection unit” (as interpreted under 35 U.S.C. §112(f) in the Claim Interpretation section above) that selects a recognition unit to be used for recognition processing on a content from a plurality of recognition units on a basis of a state of an operation of a user.
Therefore, Gunatilake in view of Cormican teach: wherein the selection unit selects a recognition unit to be used for the recognition processing on the content (Refer to claim 1’s 103 rejection and Gunatilake and Cormican’s respective teachings.).
Cormican further teaches the basis of a state of an operation of a user include: on a basis of at least one of a moving speed, a moving direction, or a feature amount of movement of the operation of the user (Cormican teaches determining “the start and end point coordinates of the input and the speed of movement of the input” and distinguishing the user’s operation based on movement speed (¶ [0086]). Cormican further teaches determining user interest “based upon the starting position and the speed of movement” (¶ [0088]) and “based upon the drag gesture speed” (¶ [0089]). Accordingly, Cormican’s speed of movement corresponds to the claimed moving speed of the user’s operation.).
Regarding claim 3,
Gunatilake in view of Cormican teach the information processing apparatus according to claim 1, including the “selection unit,” as interpreted under 35 U.S.C. §112(f) in the Claim Interpretation section above.
Gunatilake further teaches: wherein the selection unit selects some recognition units among the plurality of recognition units (Gunatilake teaches the “video and audio algorithm libraries 140 and 150… contain algorithms developed to support the scene search capability of the engine. These algorithms… are controlled by the Controller layer 130” (¶ [0044]), and that “the Control layer selects the appropriate audio and video algorithms to perform the API task” (¶ [0045]). Accordingly, Controller layer 30 (i.e. selection unit) selects appropriate audio/video algorithms (i.e. recognition units) from the plurality of algorithms contained in libraries 140 and 150, corresponding to the claimed selection of some recognition units among the plurality of recognition units.).
Regarding claim 8,
Gunatilake in view of Cormican teach the information processing apparatus according to claim 1.
Cormican further teaches: a generation unit that generates operation state information indicating the state of the operation of the user on a basis of an operation history of the operation of the user (Cormican teaches “gesture component 210 may determine that the user gesture 455 is a swipe gesture based upon the speed of movement of the user input and the threshold value for the user associated with the gesture input” (¶ [0088]; also see description of a drag gesture (i.e. operation of a user) found in ¶ [0086]). Cormican further teaches that the user-specific threshold may be determined “based upon past user inputs and past determination between drags and swipes for the user” (¶ [0088]). Accordingly, the past user inputs and past gesture determinations reasonably correspond to an operation history of the operation of the user, and the determination of the current operation as a drag or swipe corresponds to operation state information indicating the state of the user’s operation.).
With respect to the 35 U.S.C. 112(f) interpretation of the claimed “generation unit,” see the Claim Interpretation section above. Cormican’s programmed gesture component 210 determines the state of a user’s operation using a user-specific threshold that may be based on past user inputs and past drag/swipe gesture determinations (Cormican ¶ [0086], ¶ [0088]). As applied in the Gunatilake-Cormican combination discussed above, Cormican would have rendered obvious the programmed structure and algorithm corresponding to the claimed “generation unit”.
Regarding claim 9,
Gunatilake in view of Cormican teaches the information processing apparatus according to claim 8, including the “generation unit,” as interpreted under 35 U.S.C. §112(f) in the Claim Interpretation section above.
Cormican further teaches: generating operation state information indicating a pattern among a plurality of patterns, including a first slow-operation pattern and a second quick-operation pattern. Specifically, Cormican’ gesture component 210 determines the state of a user’s operation as a drag, swipe, or other gesture based on movement speed (¶ [0086]). A drag gesture occurs when “a speed of the movement of the input is below a threshold value,” while a swipe gesture occurs when “a speed of the movement of the input is above a threshold value” (¶ [0086], ¶ [0088]). Cormican further provides an example in which “the user may slowly drag” a media item and the system determines user interest based on the drag gesture speed (¶ [0089]). Accordingly, Cormican’s determination of a below threshold drag gesture corresponds to operation state information indicating the slow operation aspect of the claimed first pattern, while its determination of an above threshold swipe gesture corresponds to operation state information indicating the quick operation aspect of the claimed second pattern.
Gunatilake and Cormican fail explicitly disclose: wherein the generation unit generates the operation state information indicating a state of a pattern of any of states of a plurality of patterns including a state of a first pattern in which an IN point or an OUT point of the sample scene is designated to stop slowly and a state of a second pattern in which the IN point or the OUT point of the sample scene is designated quickly.
However, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to further configure the generation unit taught by Gunatilake as previously modified by Cormican such that Cormican’s speed-based drag and swipe classifications are used as respective operation-state patterns when the user designates an IN and OUT point of a sample scene. As seen in claim 1, Gunatilake teaches user selection of frames corresponding to video sections and further teaches that “sections of the video as defined by the frames can be cropped (¶ [0097], ¶ [0102]), thereby providing user-designated positions defining video portions for subsequent editing. Cormican teaches classifying user’s operation as a drag or swipe based on whether the movement speed is below or above a threshold and using the resulting gesture to determine the user’s media selection or interest (¶ [0086]-[0089]). Such a modification would predictably enable the system to generate different operation state patterns based on the way the user designates the boundaries of a video scene (i.e. IN and OUT points of the sample scene), thereby providing operation state information for selecting appropriate recognition processing.
Regarding claim 10,
Gunatilake in view of Cormican teaches the information processing apparatus according to claim 9, including the “generation unit,” as interpreted under 35 U.S.C. §112(f) in the Claim Interpretation section above.
Cormican further teaches: use of a predetermined rule for determining the state of a user’s operation. Specifically, Cormican teaches determining whether a user gesture is a drag or swipe gesture based on the speed of movement of the user input relative to a threshold value (¶ [0086], ¶ [0088]-[0089]). Cormican further teaches that the threshold may be determined “based upon past user inputs and past determination between drags and swipes for the user” (¶ [0088]). Thus, Cormican teaches both a predetermined rule base for determining an operation state and use of past user-operation information, which reasonably corresponds to the claimed operation history. However, Cormican does not expressly teach the relationship in which the operation history is analyzed on the predetermined rule base to generate the operation state information.
Thus, Gunatilake and Cormican fail to explicitly disclose: wherein the generation unit analyzes the operation history on a predetermined rule base, and generates the operation state information.
However, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to further configure the generation unit resulting from the teachings of Gunatilake as previously modified by Cormican to analyze the operation history using Cormican’s predetermined speed-thresholding rule (corresponding to the claimed “predetermined rule”) and generate the corresponding operation state information, since Cormican already teaches using past inputs to determine the threshold applied in classifying user operations (¶ [0086], ¶ [0088]-[0089]). Applying Cormican’s predetermined rule to the historical user operation information would have predictably provided a consistent rule-based model for analyzing user operation history and generating corresponding operation state information.
Regarding claim 11,
Gunatilake in view of Cormican teaches the information processing apparatus according to claim 10, including the “generation unit,” as interpreted under 35 U.S.C. §112(f) in the Claim Interpretation section above.
Cormican further teaches: wherein the generation unit generates the operation state information on a basis of magnitude of a moving speed of a point position operated by the user (Cormican teaches the “gesture component 210 determines the start and end point coordinates of the input and the speed of movement of the input” to determine whether the user’s operation “is a drag, a swipe, or other type of gesture” (¶ [0086]). Cormican further teaches determining a swipe gesture classification when the movement speed is above a threshold and a drag gesture classification when the movement speed is below the threshold (¶ [0088]-[0089]). Accordingly, the coordinates of the user’s touch input correspond to the claimed point position, and Cormican’s gesture classification information corresponds to the claimed operation state information. Thus, Cormican’s determination of the gesture classification reasonably corresponds to generating the operation state information on a basis of magnitude of a moving speed of a point position operated by the user, as claimed.).
Regarding claim 16,
Gunatilake in view of Cormican teaches the information processing apparatus according to claim 9, including the “generation unit,” as interpreted under 35 U.S.C. §112(f) in the Claim Interpretation section above.
Cormican further teaches: wherein the generation unit analyzes the operation history by using a learning model, and generates the operation state information (Cormican teaches that gesture component 210 may “implement a machine learning model to differentiate between different types of user gestures” (¶ [0057]). Cormican further teaches that the machine learning model is “trained based on a training set reflecting different user actions” (¶ [0058]). Cormican further explains that the training agent may associate user-specific input tendencies with particular users, including distinctions based on how quickly a user swipes as compared to dragging (¶ [0059]). Accordingly, Cormican teaches using historical user operation information as input to a learning model to determine the type of a subsequent user operation, corresponding to the claimed operation of analyzing the operation history by using a learning model, and generating the operation state information.
Regarding claim 19,
Gunatilake in view of Cormican teaches: An information processing method comprising: selecting a recognition unit to be used for recognition processing on a content from a plurality of recognition units on a basis of a state of an operation of a user when the user designates a sample scene to become a sample of a scene to be cut from the content for the same reasons discussed above with respect to claim 1.
Regarding claim 20,
Gunatilake in view of Cormican teaches: a selection unit that selects a recognition unit to be used for recognition processing on a content from a plurality of recognition units on a basis of a state of an operation of a user when the user designates a sample scene to become a sample of a scene to be cut from the content for the same reasons discussed above with respect to claim 1, including the “selection unit,” as interpreted under 35 U.S.C. §112(f) in the Claim Interpretation section above..
Gunatilake further teaches: A program for causing a computer to function (Gunatilake teaches computer software implementation of the VideoLens Media Engine (¶ [0037]), including Controller layer 130 and audio/video algorithm libraries 140 and 150, as discussed above with respect to claim 1 and depicted in FIG. 1; see ¶ [0015] “computer program products for performing automated analysis of multimedia data are disclosed and claimed herein”.).
Accordingly, Gunatilake in view of Cormican teaches or suggests the claimed “program for causing a computer to function as” the recited selection unit.
Claims 4-7 are rejected under 35 U.S.C. 103 as being unpatentable over Gunatilake (US 2012/0117046 A1) in view of Cormican (US 2020/0301965 A1), and in further view of Stojancic et al. (US 2019/0354763 A1; hereafter “Stojancic”).
Regarding claim 4,
Gunatilake in view of Cormican teach the information processing apparatus according to claim 1, including a plurality of recognition units.
Gunatilake in view of Cormican fail to explicitly disclose: wherein the plurality of recognition units include two or more of a graphic recognition unit that performs recognition processing on a graphic as a recognition target, a camera switching (SW) recognition unit that performs recognition processing on switching of a camera as a recognition target, and an excitement recognition unit that performs recognition processing on excitement as a recognition target.
In a related art, Stojancic teaches: at least two of the recited recognition units. Specifically, Stojancic teaches video analysis for detecting distinctive visual elements including a “moving logo or text” and further teaches detecting “changes in camera angles” and cuts as visual delineators for identifying the start and/or end of video highlights (¶ [0132]-[0133]). Accordingly, Stojancic’s detection of logos/text corresponds to the claimed graphic recognition unit, and its detection of changes in camera angles corresponds to the claimed camera switching (SW) recognition unit.).
Gunatilakek, Cormican, and Stojancic are related in that each concerns processing multimedia/video content to identify content or scenes of interest.
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the teachings of Gunatilake as modified by Cormican by including Stojancic’s graphic and camera-angle-change recognition techniques among Gunatilake’s selectable video-analysis algorithms. Gunatilake expressly teaches adding new search methods to its algorithm library (Gunatilake ¶ [0046] “Its capabilities can be enhanced over time via the addition of new search methods to its algorithm library.”), and Stojancic teaches these known techniques for identifying the start and/or end of video portions. Such a modification would predictably provide additional recognition techniques for locating scene boundaries based on detected graphics and camera switching.
Regarding claim 5,
Gunatilake in view of Cormican and Stojancic teach the information processing apparatus according to claim 4, including the “selection unit,” as interpreted under 35 U.S.C. §112(f) in the Claim Interpretation section above.
Gunatilake in view of Cormican and Stojancic fail to explicitly disclose: wherein the selection unit selects the graphic recognition unit and the camera SW recognition unit in a case where the state of the operation of the user is a state where an IN point or an OUT point of the sample scene is designated to stop slowly.
However, Cormican further teaches: determining a drag gesture when “a speed of the movement of the input is below a threshold value” (¶ [0086]) and further teaches that “the user may slowly drag” a search result item, with gesture component 210 determining “user interest based upon the drag gesture speed” (¶ [0089]). Accordingly, Cormican teaches a below-threshold slow drag operation, corresponding to the slow-operation aspect of the claimed state in which the IN point or OUT point is “designated to stop slowly”, but does not explicitly disclose selecting the claimed graphic recognition unit and camera switching recognition unit in response to such an operation.
Stojancic further teaches: the corresponding graphic and camera switching recognition techniques for identifying video boundaries, as seen with respect to claim 4. Specifically, Stojancic teaches video analysis for detecting distinctive visual elements including a “moving logo or text” and further teaches detecting “changes in camera angles” and cuts, with the system detecting such visual delineators “so as to identify start and/or end of highlights” (¶ [0132]-[0133]). Stojancic further teaches recording “the start and end times” of an identified highlight in an identifier (¶ [0159]), and that the identifier may include time codes indicating where the highlight resides in the source video and that the corresponding highlight may be obtained by cropping the source video (¶ [0122]-[0123]). . Accordingly, Stojancic’s detection of logos/text corresponds to the claimed graphic recognition, its detection of changes in camera angles corresponds to the claimed camera switching (SW) recognition and its identified start and end positions teach start and end boundaries of a video portion corresponding to the positional function of the claimed In and Out points, although Stojancic does not itself teach that those points are designated by the user’s slow operation.).
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to further modify the teachings of Gunatilake as previously modified by Cormican and Stojancic such that Cormican’s relatively slow operation is used to designate a start or end point of a video scene corresponding to the video portion start/end points (i.e. IN and OUT points) taught by Stojancic, and Gunatilake’s controller 130 (corresponding to the selection unit, as seen in claim 1) then selects Stojancic’s graphic recognition and camera SW recognition techniques. Gunatilake explicitly teaches that its controller 130 selects appropriate audio and video analysis algorithms to perform the API task (¶ [0045]) and that its capabilities may be “enhanced over time via the addition of new search methods to its algorithm library” (Gunatilake ¶ [0046]). The modification would predictably provide multiple visual cues, including detected graphics and camera changes, for identifying the start or end of the scene indicated by the user’s operations, thereby further automating selection of the appropriate recognition processing and facilitating subsequent extraction or cropping of the indicated scene.
Regarding claim 6,
Gunatilake in view of Cormican and Stojancic teach the information processing apparatus according to claim 4, including the “selection unit,” as interpreted under 35 U.S.C. §112(f) in the Claim Interpretation section above.
Gunatilake in view of Cormican and Stojancic fail to explicitly disclose: wherein the selection unit selects the excitement recognition unit in a case where the state of the operation of the user is a state where an IN point or an OUT point of the sample scene is designated quickly.
However, Cormican further teaches: determining a swipe gesture when the speed of the movement of the user input is above a threshold value (Cormican ¶ [0086], ¶ [0088]) and further teaches determining the media item in which the user is interested based in part on the speed of movement (¶ [0088]). Accordingly, Cormican’s above-threshold swipe gesture corresponds to the quick operation aspect of the claimed state in which the IN point or OUT point is “designated quickly.” However, Cormican does not explicitly disclose that the quick operation is used to designate an IN point or OUT point of a video scene, or that excitement recognition processing is selected in response to such designation.
Stojancic further teaches: identifying the start and end point of highlights/video portions (Stojancic ¶ [0132]-[0133]) and recording the start and end times of an identified highlight/video portions in an identifier (¶ [0159]). Stojancic further teaches that the identifier may include time codes indicating where the highlight resides in the source video and that the corresponding highlight may be obtained by cropping the source video (¶ [0122]-[0123]). Accordingly, Stojancic’s identified start and end positions teach start and end boundaries of a video portion corresponding to the claimed IN and OUT points of a video scene, although Stojancic does not itself teach that those points are designated by the user’s quick operation. Stojancic further teaches determining an “excitement level” indicating how exciting or interesting an event or highlight is (¶ [0054]), ¶ [0125]), corresponding to the claimed excitement recognition. This interpretation is consistent with the instant specification, which describes the excitement recognition engine as performing recognition on excitement and determining an excitement score indicating a degree of excitement (See instant application’s pre-grant publication (US 2025/0336200 A1) paragraphs [0122], [0126], and [0274]-[0276]).
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the teachings of Gunatilake as previously modified by Cormican and Stojancic such that Cormican’s relatively quick user operation is used to designate a start or end point of a video scene corresponding to the video portion start/end points (i.e. IN and OUT points) taught by Stojancic, and Gunatilake’s controller 130 (corresponding to the selection unit, as seen in claim 1) selects Stojancic’s excitement recognition processing for the indicated scene. Gunatilake teaches that its controller 130 selects the appropriate audio and video algorithms to perform the API task (¶ [0045]) and that its capabilities may be enhanced “via the addition of new search methods to its algorithm library” (¶ [0046]). Such a modification would predictably enable the system to determine the degree of excitement associated with a quickly indicated video scene, thereby providing additional user-based recognition information for identifying and processing the indicated scene and further automating selection of the appropriate recognition processing.
Regarding claim 7,
Gunatilake in view of Cormican and Stojancic teach the information processing apparatus according to claim 4, including the “selection unit,” as interpreted under 35 U.S.C. §112(f) in the Claim Interpretation section above.
Gunatilake, Cormican, and Stojancic collectively further teach portions of the following limitation:
wherein the selection unit selects the recognition unit determined in advance or the recognition unit designated by the user (Gunatilake further teaches that its Controller layer “selects the appropriate audio and video algorithms to perform the API task” (Gunatilake ¶ [0045]). Gunatilake further teaches that a “ user query may specify a desire to find action scenes, low motion scenes, previewing frames, dialogue/music scenes,” or other content features (¶ [0108], also see ¶ [0097]), such that the controller selects an appropriate algorithm corresponding to the user-designated search function (¶ [0045]-[0046], ¶ [0054], ¶ [0108]). Gunatilake also teaches that “its capabilities can be enhanced over time via the addition of new search methods to its algorithm library” (¶ [0046]).)
in a case where the state of the operation of the user is not a state where an IN point or an OUT point of the sample scene is designated to stop slowly or is not a state where the IN point or the OUT point of the sample scene is designated quickly (Cormican further teaches a slow operation state in which a drag gesture is determined when “a speed of the movement of the input is below a threshold value” and a quick operation state in which a swipe gesture is determined when “a speed of the movement of the input is above a threshold value” (Cormican ¶ [0086]-[0089]), corresponding respectively to the slow and quick operation aspects of the claimed “designated to stop slowly” and “designated quickly” states. Cormican further teaches other user operation states, including tap and press-and-hold gestures (¶ [0084]-[0085]), and teaches that “the type of preview requested… may be based upon the type of user gesture” (¶ [0092]). Stojancic further teaches identifying the start and/or end of video highlights (Stojancic ¶ [0132]-[0133]) and recording corresponding start and end times (¶ [0159]), which provide start/end boundaries corresponding to the positional function of the claimed IN and OUT points, as discussed above with respect to claims 5 and 6.)
In summary, Cormican teaches distinguishing among multiple user-operation states and associating different processing with the determined gesture type (Cormican ¶ [0084]-[0086], ¶ [0092]); Stojancic teaches identifying start and end boundaries of video portions (Stojancic ¶ [0132]-[0133], ¶ [0159]); and Gunatilake teaches selecting an appropriate audio/video algorithm according to the requested processing function (Gunatilake ¶ [0045]-[0046], ¶ [0054], ¶ [0108]).
However, Gunatilake in view of Cormican and Stojancic does not explicitly disclose the claimed relationship as a whole: wherein the selection unit selects the recognition unit determined in advance or the recognition unit designated by the user in a case where the state of the operation of the user is not a state where an IN point or an OUT point of the sample scene is designated to stop slowly or is not a state where the IN point or the OUT point of the sample scene is designated quickly.
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to further modify the teachings of Gunatilake as previously modified by Cormican and Stojancic such that, when the user’s operation at a start or end point of a video scene, as taught by Stojancic, corresponds to one of Cormican’s other user-operation states (e.g. tap or press-and-hold gesture), rather than Cormican’s below-threshold slow drag or above-threshold quick swipe states, corresponding respectively to the slow and quick operation aspects of the claimed “designated to stop slowly” and “designated quickly” states, Gunatilake’s Controller layer 130 selects an algorithm corresponding to a recognition function designated by the user, as taught by Gunatilake. Thus, Cormican’s other gesture states provide an operation state that is not the slow or quick operation state, Sojancic provides the corresponding video start/end boundary, and Gunatilake provides the user-designated recognition algorithm selection. Such a modification would predictably apply Gunatilake’s user-designated algorithm selection to an additional user operation state at a video start/end boundary, thereby providing greater flexibility in selecting appropriate recognition processing for different user interactions with a video scene boundary.
Claim 12 is rejected under 35 U.S.C. 103 as being unpatentable over Gunatilake (US 2012/0117046 A1) in view of Cormican (US 2020/0301965 A1), and in further view of Hammendorp et al. (US 2016/0139794 A1; hereafter “Hammendorp”).
Regarding claim 12,
Gunatilake in view of Cormican teaches the information processing apparatus according to claim 11, including the “generation unit,” as interpreted under 35 U.S.C. §112(f) in the Claim Interpretation section above.
Cormican teaches: determining the state of a user’s operation based on movement speed, as previously seen in claim 11’s 103 rejection. Specifically, Cormican teaches that gesture component 210 distinguishes a drag gesture from a swipe gesture based on whether “a speed of the movement input is below a threshold value” or above the threshold (¶ [0086], ¶ [0088]).
Gunatilake in view of Cormican fail to explicitly disclose: wherein the generation unit generates the operation state information on a basis of a magnitude relationship between magnitude of a moving speed of the point position at a time of searching at which the user searches for the IN point or the OUT point of the sample scene and magnitude of a moving speed of the point position at a time of designation at which the IN point or the OUT point of the sample scene is designated.
In a related art, Hammendorp teaches that a user may begin “with a relatively fast swiping gesture speed, and gradually slow the swiping gesture, changing directions if necessary, to hone in on the desired portion of the media file” (¶ [0052]). Hammendorp further teaches using “relatively slow speeds (e.g., below the threshold speed), to fine tune and precisely move the playhead to the desired point in time of the media file” (¶ [0057]), wherein the resulted selected frame may become a “new in- or out-point” (¶ [0059]). This corresponds to the claimed use of different moving speed magnitudes associated with locating and designating an IN or OUT point, although Hammendorp does not expressly teach generating operation state information based on the claimed magnitude relationship between those speeds.
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to further modify the teachings of Gunatilake as previously modified by Cormican by generating the operation state information based on the relationship between the movement speeds associated with locating and precisely designating an IN or OUT point, as taught by Hammendorp. Cormican already teaches determining the state of a user’s operation based on movement speed, and Hammendorp teaches varying movement speed from relatively fast movement used to locate a desired portion to relatively slow movement used to precisely position an IN or OUT point. Such a modification would predictably improve the determination of the user’s operation state while facilitating accurate selection of desired video boundaries.
Claim 14 is rejected under 35 U.S.C. 103 as being unpatentable over Gunatilake (US 2012/0117046 A1) in view of Cormican (US 2020/0301965 A1), and in further view of Park et al. (US 8,629,851 B1; hereafter “Park”).
Regarding claim 14,
Gunatilake in view of Cormican teaches the information processing apparatus according to claim 10, including the “generation unit,” as interpreted under 35 U.S.C. §112(f) in the Claim Interpretation section above.
Cormican further teaches: determining the state of a user’s operation based on characteristics of the user’s movement, as previously seen in claim 10’s 103 rejection. Specifically, Cormican’s gesture component 210 determines whether a use operation is a drag, swipe, or other gesture based on movement speed (¶ [0086]-[0089]).
However, Gunatilake in view of Cormican fails to explicitly disclose: wherein the generation unit generates the operation state information on a basis of at least one of a number of times of switching of a moving direction of a point position operated by the user or a number of times of switching at a time of designation at which the IN point or the OUT point of the sample scene is designated.
In a related art, Park teaches: a gesture recognition method, device, and system (see Park’s Abstract, and column 1 lines 41-67) that includes “tracking position data of a conductive object,” “determining direction data of the conductive object from the position data,” and “counting a number of times there is a change in direction by the conductive object,” wherein the direction data and number of direction changes are used to determine the corresponding gesture (claim 1; see also FIGS. 3A-4). Park further teaches that “direction order counter (DOC) 334… may indicate the number of direction change(s) associated with the finger movement” (Column 4 lines 51-54; see also FIG. 3B). Accordingly, Park teaches determining a user’s operation based on the claimed “number of times of switching of a moving direction of a point position operated by the user.”
Although Park is not specifically directed to recognition systems in video analysis, Park is relevant to the claimed user operation analysis because, like Cormican, Park’s system determines a user’s gesture based on characteristics of the user’s point movement.
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to further modify the teachings of Gunatilake as previously modified by Cormican such that Cormican’s determination of the user’s operation state additionally uses the number of changes in movement direction, as taught by Park. Doing so would predictably provide an additional movement characteristic for determining the state of a user’s operation.
Allowable Subject Matter
Claims 13, 15, and 17-18 are rejected under 35 U.S.C 101, and claims 17-18 are rejected under 35 U.S.C. 112(b), but these claims would be allowable if the 101 and 112(b) issues were resolved and the claims were rewritten in independent form, including all of the limitations of the base claim and any intervening claims.
Conclusion
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/SDB/
Samuel D. Baynes
Examiner, Art Unit 2665
/Stephen R Koziol/Supervisory Patent Examiner, Art Unit 2665
Prosecution Insights