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.
Claims 1, 8, and 16 rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. The claim recites a method of decoding encoded video data, the method comprising: determining, from the encoded video data, a block of a picture; applying a neural network (NN)-based filter to the block to generate a filtered
block, wherein the NN-based filter comprises a plurality of backbone blocks and at least
one of the backbone blocks comprises an attention block configured to process non-
normalized data; determining a decoded version of the block based on the filtered block; and outputting a decoded version of the picture comprising the decoded version of the
block.
The limitation of determining, from the encoded video data, a block of a picture, determining a decoded version of the block based on the filtered block as drafted, is a process that, under its broadest reasonable interpretation, covers performance of collecting, displaying, and manipulating data (int. Ventures V. Cap One Financial). The concept described in claim 1 is pure data analyses and decision making, which is considered, by the courts, to be abstract idea. There is nothing in the claim element precludes the step from practically being performed in the mind.
The limitation of applying a neural network (NN)-based filter to the block to generate a filtered block, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of organizing and manipulating information through mathematical correlations (Digitech), selecting certain information, analyzing it using mathematical techniques, and reporting or displaying the results of analyses (SAP v. InvestPic)). The courts interpret “apply” as merely performing the abstract idea. There is nothing in the claim element precludes the step from practically being performed in the mind.
The limitation of outputting a decoded version of the picture comprising the decoded version of the block, as drafted, is a process that, under its broadest reasonable interpretation, covers performance selecting certain information, analyzing it using mathematical techniques, and reporting or displaying the results of analyses (SAP v. InvestPic)). The concept described in claim 1 is not meaningfully different than those of an idea “of itself” or mathematical relationships found by the courts to be abstract idea. There is nothing in the claim element precludes the step from practically being performed in the mind.
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. In particular, the claim recites additional elements – wherein the NN-based filter comprises a plurality of backbone blocks and at least one of the backbone blocks comprises an attention block configured to process non-normalized data. The wherein clause simply tells a person of ordinary skill about the desired function property and does not add a concrete technical implementation. The applying step merely is interpreted as performing or executing the abstract idea, rather than transforming it into a patentable invention. The computer readable medium in claim 16 merely recite generic computer implementations of the abstract idea. Accordingly, these additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. Thus, taken alone, the additional elements do not amount to significantly more than the above judicial exception (the abstract idea). Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions provide conventional implementation. The claim is directed to an abstract idea. Accordingly, claim 1 is ineligible.
Claims 2-7, 9-15, 17-20 are dependent on their respective parent claims and include all the limitations of these claims. Therefore, claims 2-7, 9-15, 17-20 recite the same abstract idea as the independent claims. The claims recite additional limitations that are merely extra-solution activity and do not meaningfully limit the claim. These limitations do not contain an inventive concept that meaningfully limits the abstract idea. As a result, claims 1-20 are not drawn to eligible subject matter as they are directed to an abstract idea without significantly more.
Claims 16-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. This claim discloses a “ computer readable medium” (in line 1) that could be broadly interpreted to include medium such as carrier waves and media distributed over a network (Please see the MPEP 2106 Section IV. Determine Whether the Claimed Invention Complies with 35 U.S.C. 101). The Applicant’s specification defines a computer readable medium to be Computer-readable media may include computer-readable storage media, which corresponds to a tangible medium such as data storage media, or communication media including any medium that facilitates transfer of a computer program from one place to another, e.g., according to a communication protocol. In this manner, computer-readable media generally may correspond to (1) tangible computer-readable storage media which is non-transitory or (2) a communication medium such as a signal or carrier wave. Based on the broadest reasonable interpretation, with consideration of the phrase “or”, the computer readable medium encompasses non-statutory media such as a signal. This rejection may be overcome by modifying the claim and the specification to recite a non-transitory computer readable medium or tangible computer readable device. Please note that “tangible” by itself will not make the claim statutory. Tangible means perceivable, and a signal can be perceived. In addition, “Non-transitory medium” is not an acceptable substitute terminology because the claim language does not reflect the interrelationship between the program and a computer. The claims should be amended to recite “non-transitory computer readable storage medium”.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1, 3-8, 10-16, 18-20 are rejected under 35 U.S.C. 103 as being unpatentable over US 20220116633 A1-Jiang et al (Hereinafter referred to as “Jiang”), in view of US 20210390410 A1-Vaswani et al (Hereinafter referred to as “Vaswani”), in further view of US 20230010160 A1-Chen et al (Hereinafter referred to as “Chen”)
Regarding claim 1, Jiang discloses a method of decoding encoded video data ([0002]), the method comprising:
determining, from the encoded video data, a block of a picture ([0032], wherein plurality of original image frames are partitioned into spatial blocks, each spatial block can be further partitioned into smaller blocks iteratively);
applying a neural network (NN)-based filter to the block to generate a filtered block ([0007], wherein using neural network with loop filters), wherein the NN-based filter comprises a plurality of backbone blocks and at least one of the backbone blocks comprises an attention block configured to process non- normalized data (According to instant applicant’s specification, [0167], discloses that Backbone is nothing more than some feature extraction. To be consistent with applicant’s specification, Jiang discloses feature extraction in fig. 4-5).
determining a decoded version of the block based on the filtered block ([0032], wherein On the decoder side, the quantized residual ŷ.sub.t is first de-quantized (e.g., through inverse transformation such as Inverse Discrete Cosine Transform (IDCT)) to obtain a recovered residual {circumflex over (r)}.sub.1, and then the recovered residual {circumflex over (r)}.sub.t is added back to the predicted frame {tilde over (x)}.sub.t to obtain a reconstructed frame by {circumflex over (x)}.sub.t={tilde over (x)}.sub.t+{circumflex over (r)}.sub.t); and outputting a decoded version of the picture comprising the decoded version of the block ([0033-0034]).
Jiang fails to disclose NN-based filter comprises a plurality of backbone blocks and at least one of the backbone blocks comprises an attention block configured to process non- normalized data
However, in the same field of endeavor, Vaswani discloses NN-based filter comprises a backbone block and at least one of the backbone blocks comprises an attention block configured to process non- normalized data (fig. 1 shows a backbone that comprise a self attention layer; [0062], wherein while the backbone neural network can be a ResNet-based backbone with one or more of the convolutional layers replaced with local self-attention layers. For example, the backbone can be a ResNet-50 or a ResNet-101 backbone with the last two, three, or four, convolutional layers replaced with local self-attention layers)
Therefore, it would have been obvious to one of ordinary skilled in the art before the effective filing date of the claimed invention to modify the method disclosed by Jiang to disclose NN-based filter comprises a backbone block and at least one of the backbone blocks comprises an attention block configured to process non- normalized data as taught by Vaswani, to improve the speed, the effectiveness, or both of the training process ([0071], Vaswani).
Jiang and Vaswani fail to disclose NN-based filter comprise a plurality of backbone blocks.
However, in the same field of endeavor, Chen discloses a NN-based filter comprise a plurality of backbone blocks ([0095], wherein a plurality of feature extraction subnetworks are available).
Therefore, it would have been obvious to one of ordinary skilled in the art before the effective filing date of the claimed invention to modify the method disclosed by Jiang and Vaswani to disclose NN-based filter comprises a plurality of backbone blocks and at least one of the backbone blocks comprises an attention block configured to process non- normalized data as taught by Chen, thereby improving processing accuracy of the neural network for the multimodal data ([0100], Chen).
Regarding claim 3, Vaswani discloses the method of claim 1, wherein the attention block processes the non-normalized data without a normalization layer (Fig 1, shows no normalization layer).
Regarding claim 4, Jiang discloses the method of claim 1, wherein the NN-based filter comprises a plurality of convolution layers (jiang, [0055], plurality convolution layers, and the attention block is configured to receive inputs from the one or more convolution layers ([0061], Jiang).
Regarding claim 5, jiang discloses the method of claim 1, wherein the attention block comprises a plurality of convolutions layers configured to generate query, key, and value inputs ([0045]).
Regarding claim 6, Vaswani discloses the method of claim 1, wherein the plurality of backbone blocks consists of 24 blocks ([0062], resnet 50 has 50 blocks), and the 24 backbone blocks consist of 2 backbone blocks that include attention blocks ([0062], wherein 2-4 are replaced with attention layers).
Regarding claim 7, Jiang discloses the method of claim 1, wherein the method of decoding is performed as part of a video encoding process ([0032]).
Regarding claim 8, analyses are analogous to those presented for claim 1 and are applicable for claim 8, Device with memory and processors (Jiang, fig 2).
Regarding claim 10, analyses are analogous to those presented for claim 3 and are applicable for claim 10.
Regarding claim 11, analyses are analogous to those presented for claim 4 and are applicable for claim 11.
Regarding claim 12, analyses are analogous to those presented for claim 5 and are applicable for claim 12.
Regarding claim 13, analyses are analogous to those presented for claim 6 and are applicable for claim 13.
Regarding claim 14, Jiang discloses the device of claim 8, further comprising a display configured to display decoded video data ([0025]).
Regarding claim 15, Jiang discloses the device of claim 8, wherein the device comprises one or more of a camera, a computer, a mobile device, a broadcast receiver device, or a set-top box ([0019]).
Regarding claim 16, analyses are analogous to those presented for claim 1 and are applicable for claim 16.
Regarding claim 18, analyses are analogous to those presented for claim 3 and are applicable for claim 18.
Regarding claim 19, analyses are analogous to those presented for claim 4 and are applicable for claim 19.
Regarding claim 20, analyses are analogous to those presented for claim 6 and are applicable for claim 20.
Claim(s) 2, 9, and 17 are rejected under 35 U.S.C. 103 as being unpatentable over US 20220116633 A1-Jiang et al (Hereinafter referred to as “Jiang”), in view of US 20210390410 A1-Vaswani et al (Hereinafter referred to as “Vaswani”), in further view of US 20230010160 A1-Chen et al (Hereinafter referred to as “Chen”), in further view of US 20220160433 A1-Rafii-Tari et al (hereinafter referred to as “Rafi”).
Regarding claim 2, Jiang discloses the method of claim 1 (see claim 1),
Jiang, Vaswani, and Chen fail to discloses wherein the attention block performs only multiplication and addition operations.
However, in the same field of endeavor, Rafi discloses determining, from the encoded video data, a block of a picture ([0055]); applying a neural network (NN)-based filter to the block to generate a filtered block([0040]), wherein the NN-based filter comprises a backbone block ([0040]) and attention block ([0052]) determining a decoded version of the block based on the filtered block [0055] and outputting a decoded version of the picture comprising the decoded version of the block ([0055]); wherein the attention block performs only multiplication and addition operations ([0053], wherein common attention techniques are dot-product attention, which uses the dot product between vectors to determine attention. Dot product uses multiplication and addition)
Therefore, it would have been obvious to one of ordinary skilled in the art before the effective filing date of the claimed invention to modify the method disclosed by Jiang, Vaswani, and Chen to disclose wherein the attention block performs only multiplication and addition operations as taught by Rafi, thereby improving real time communication ([0061], Rafi).
Regarding claim 9, analyses are analogous to those presented for claim 2 and are applicable for claim 9.
Regarding claim 17, analyses are analogous to those presented for claim 2 and are applicable for claim 17.
Conclusion
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LERON . BECK
Examiner
Art Unit 2487
/LERON BECK/ Primary Examiner, Art Unit 2487