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 .
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 11 is rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter.
Specifically, claim 11 recites a “program”, which is non-statutory subject matter. The additional language “for causing a computer to implement [calculating and adjusting]” is interpreted as a computer being optional to the claim, rather than intrinsic or inherent.
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 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 of this title, 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.
Claims 1-2, 5-6 and 10-11 are rejected under 35 U.S.C. 103 as being unpatentable over Souza US2009/0226067 in view of Wheeler US2008/0175509; also relying on Wikipedia article “Network Theory” as a term-definition reference
As for claim 1, Souza teaches
An information processing device comprising:
an [image] determination network (Fig 6A is a workflow of decision-making steps which is an implementation of a Network, see “Network theory – Wikipedia” reference for terminology explanation; note that the claim does not specifically require a neural network; thus any workflow or subset of a workflow in the present claims can be mapped to a Network) that calculates an [image] matching degree between an input image before being subjected to super-resolution processing and the input image after being subjected to the super-resolution processing (Fig 6A el 250 [0045] the “residual error” is is calculated as a formula based on a difference between a previous low-resolution result, i.e. input image, and the currently calculated high-resolution result); and
a super-resolution network that adjusts a generation force of the super-resolution processing based on the [image] matching degree (fig 6A, incrementing k = k+1 if the error has not reached the target minimum; the iteration count “k” can be called “a generation force”, since it determines how many iterations are performed to generate the final result, i.e. “more iterations” = “more generation force”)
Souza doesn’t specifically teach, Wheeler however teaches
super-resolution of an image with a human face (Wheeler, Fig 1, [0035] teaches a super-resolution method specifically of an image containing a human face)
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Souza and Wheeler as they both pertain to the art of image super-resolution. One of ordinary skill in the art at the time of the invention would have been motivated to combine said teachings, in order to apply advanced methods of super-resolution specifically to images of human subjects.
As for claims 10 and 11, please see discussion of analogous claim 1 above.
As for claim 2, the combination of Souza and Wheeler teaches
the super-resolution network selects and uses a generator in which the human face matching degree satisfies an acceptance criterion from a plurality of generators having different generation force levels (Fig 6A: each new iteration could be called “a different generator”, thus we have “a plurality of generators”, each with a corresponding iteration count)
As for claim 4, the combination of Souza and Wheeler teaches
the super-resolution network determines whether or not the human face matching degree satisfies the acceptance criterion in order from a generator having the higher generation force level, and selects and uses a generator determined to satisfy the acceptance criterion first (Fig 6A: once the error reaches the target minimum, the iterations stop, this can be called “selecting” the final iteration and ultimate count of iterations)
As for claim 5, the combination of Souza and Wheeler teaches
a generation force control value calculation unit that calculates a generation force control value indicating a lowering width from the current generation force level based on the human face matching degree (NOTE “lowering width” is not explicitly defined in Applicant original disclosure as a particular term, nor is it a commonly recognized term in the art; thus it is here understood as “a parameter that influences the super-resolution”; as discussed above, the parameter k indicates the ultimate number of iterations for the final super-resolution result),
wherein the lowering width is larger as the human face matching degree is lower (if the error rate is lower, i.e. the similarity of result to input is higher - then number of iterations will be lower).
As for claim 6, the combination of Souza and Wheeler teaches
the super-resolution network performs super-resolution processing on the input image by using feature information of a human face criterion image (“feature information” is taken broadly and understood as any image data, such as – image pixels).
Allowable Subject Matter
Claims 3 and 7-9 is objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
The following is the Examiner’s statement of reasons for indicating allowable subject matter:
Features in the claim are not found in prior art, in conjunction with the entire scope of the claim. Specifically,
As for claim 3, it teaches a generative-adversarial network, including specific calculations and steps not disclosed in any of the references discussed above.
As for claim 7, it teaches an additional human face criterion image, a step of selecting this image from a plurality of reference images, based on the prior-recited matching degree.
As for claims 8 and 9, they depend on claim 7 discussed above, incorporating all of the limitations of claim 7.
Contact Information
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MARK ROZ whose telephone number is (571)270-3382. The examiner can normally be reached on M-F 8:00am-4:30pm.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Andrew Moyer can be reached on (571)272-9523. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see http://pair-direct.uspto.gov. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative or access to the automated information system, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/MARK ROZ/
Primary Examiner, Art Unit 2669