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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on April 7, 2026 has been entered.
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 1-3, 7-19 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.
Claim 1 partially recites “select one or more encoding parameters for the feature channel according to the determine importance”…. “wherein the one or more encoding parameters include a bit depth, which is associated with at least one transform coefficient,….; and” “wherein the selected one or more encoding parameters indicate a type of encoding being either a lossless encoding or a lossy compression, and wherein encoding the feature channel further comprises: applying the lossless encoding to a feature channel having a higher determined importance, and applying the lossy compression to a feature channel having a lower determined importance”. The Examiner points out there are two different encoding parameters being referred as the selected one. First, “…the one or more encoding parameters include a bit depth…” and second, “the selected one or more encoding parameters indicate a type of encoding being either a lossless encoding or a lossy compression”. The Examiner is unclear on which one the Applicant intended to be the selected encoding parameter.
It is noted the same issues appear in independent claims 14-17.
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 1-3, 7-19 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
Claim 1 partially recites “select one or more encoding parameters for the feature channel according to the determine importance”…. “wherein the one or more encoding parameters include a bit depth, which is associated with at least one transform coefficient,….; and” “wherein the selected one or more encoding parameters indicate a type of encoding being either a lossless encoding or a lossy compression, and wherein encoding the feature channel further comprises: applying the lossless encoding to a feature channel having a higher determined importance, and applying the lossy compression to a feature channel having a lower determined importance”.
The Examiner was not able to find support in the instant application’s specification that would support the use of both encoding parameters (the encoding parameter including a bit depth associated with a transform coefficient and an encoding parameter that indicate that the encoding is either a lossless encoding or a lossy compression) at the same time/during the encoding parameter selection. The Examiner found support in paragraph 100 for the following:
“Moreover, the feature channels are not necessarily to be encoded with lossy coding. For example, some kind of lossless transmission may be applied, e.g. for the channels with a higher importance and some kind of lossy compression may be applied e.g. for channel with a lower importance. In such case, the encoding parameters specify the kind of the encoding (e.g. lossy or lossless).”
However, no support was found for the selection of both a bit depth encoding parameter and a type of encoding (lossy or lossless) during the selection stage of the encoding process by the encoding apparatus and of the decoding process by the decoding apparatus.
It is noted the same issues appear in independent claims 14-17.
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, 7, and 9-19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Kim et al. (US 2023/0082562) in view of Zhang et al. (US 2017/0064336) further in view of Wei et al. (CN 113965750 A, translation of description used).
Regarding claim 1 Kim discloses an apparatus for encoding two or more feature channels of a neural network into a bitstream, the apparatus comprising:
a memory configured to store instructions; and a processor coupled to the memory and configured to execute the instructions (memory and at least one processor – [0012]) to cause the apparatus to:
for each of the two or more feature channels, determine importance of the two or more feature channels; select one or more encoding parameters for the feature channel according to the determined importance (feature quantization/dequantization may be performed based on the importance of a feature set and/or a channel; for example, for feature sets and/or channels with relatively high importance, the quantization interval may be narrowed to minimize information loss, and, for feature sets and/or channels with relatively low importance, the quantization interval may be widened to increase the amount of information to be encoded – [0255]; extracting feature set comprising a plurality of channels from an input image using an artificial neural network-based feature extraction method, determining a quantization method of the feature set, based on importance of each of the plurality of channels, quantizing the feature set based on the determined quantization method – [0013]); and
encode the feature channel into the bitstream according to the selected one or more encoding parameters, wherein the determined importance differs for at least two feature channels among the two or more feature channels (encoding the quantized feature set, first information on the importance and second information on the quantization method; the second information may comprise the number of quantization bits of each of the plurality of channels, and the number of quantization bits may be determined based on the importance of each of the plurality of channels – [0013]; for feature sets and/or channels with relatively high importance, the quantization interval may be narrowed to minimize information loss, and, for feature sets and/or channels with relatively low importance, the quantization interval may be widened to increase the amount of information to be encoded – [0255]).
Kim discloses the encoding of feature channels based on an encoding parameter associated with the quantization process.
However, fails to explicitly disclose wherein the one or more encoding parameters include a bit depth, which is associated with at least one transform coefficient, wherein an n-bit transform coefficient is rounded down to an m-bit transform coefficient during quantization, wherein n is greater than m; and wherein the selected one or more encoding parameters indicate a type of encoding being either a lossless encoding or a lossy compression, and wherein encoding the feature channel further comprises: applying the lossless encoding to a feature channel having a higher determined importance, and applying the lossy compression to a feature channel having a lower determined importance.
In the disclosure Zhang teaches that it is known in the art for an encoding parameter to include a bit depth, which is associated with at least one transform coefficient, wherein an n-bit transform coefficient is rounded down to an m-bit transform coefficient during quantization, wherein n is greater than m (the quantization process may reduce the bit depth associated with some of the transform coefficients; an n-bit transform coefficient may be rounded down to an m-bit transform coefficient during quantization, where n is greater than m – [0208]).
It would have been obvious to a person with ordinary skill in the art, before the effective filing date of the claimed invention, to incorporate the teachings of Zhang into the teachings of Kim because the usage of bit depth as an encoding parameter is a well-known technique in the video coding field and would yield expected results.
However, fails to explicitly disclose wherein the selected one or more encoding parameters indicate a type of encoding being either a lossless encoding or a lossy compression, and wherein encoding the feature channel further comprises: applying the lossless encoding to a feature channel having a higher determined importance, and applying the lossy compression to a feature channel having a lower determined importance.
In his disclosure Wei teaches the selected one or more encoding parameters indicate a type of encoding being either a lossless encoding or a lossy compression, and wherein encoding the feature channel further comprises: applying the lossless encoding to a feature channel having a higher determined importance, and applying the lossy compression to a feature channel having a lower determined importance (the encoding file is obtained by encoding the encoding feature map, and entropy encoding may be used to encode the encoding feature map, and the encoding feature map may be losslessly compressed by entropy encoding to obtain the encoded file , wherein the entropy coding may adopt various existing coding methods, such as Huffman coding or arithmetic coding. Of course, it is worth noting that when the encoding feature map is encoded by entropy coding, an adaptive encoding method based on the amount of image information that channels carry useful image information is used. During encoding, the bits corresponding to each channel are determined based on the image information amount of the useful image information carried by each channel in the encoding feature map, and the bits corresponding to each channel are respectively corresponding during encoding. In addition, the bits corresponding to the channel are positively correlated with the image information amount of the useful image information carried by the channel, that is, the more the image information amount of the useful image information carried by the channel, the larger the corresponding bits of the channel; conversely, the useful image carried by the channel is larger. The smaller the amount of image information of the information, the smaller the bit corresponding to the channel – page 11, 1st paragraph).
It would have been obvious to a person with ordinary skill in the art, before the effective filing date of the claimed invention, to incorporate the teachings of Wein into the teachings of Kim because such incorporation can improve the image information of the important image content in the encoded file (page 11, last paragraph).
Regarding claim 2 Kim discloses the apparatus according to claim 1, wherein the processor is further configured to execute the instructions to cause the apparatus to: generate the two or more feature channels, including processing an input picture with one or more layers of the neural network (a feature set extracted from an input image using an artificial neural network-based feature extraction method – abstract).
Regarding claim 3 Kim discloses the apparatus according to claim 1, wherein the one or more encoding parameters further include any of coding unit size, prediction unit size, and quantization step (for feature sets and/or channels with relatively high importance, the quantization interval may be narrowed to minimize information loss, and, for feature sets and/or channels with relatively low importance, the quantization interval may be widened to increase the amount of information to be encoded – [0255]).
Regarding claim 7 Kim discloses the apparatus according to claim 1, wherein the one or more encoding parameters include a quantization step size which is a quantization parameter (QP); and the higher the importance of the feature channel, the lower the QP (Kim discloses correlation between the importance of the feature channel with quantization/dequantization; feature quantization/dequantization may be performed based on the importance of a feature set and/or a channel; for example, for feature sets and/or channels with relatively high importance, the quantization interval may be narrowed to minimize information loss, and, for feature sets and/or channels with relatively low importance, the quantization interval may be widened to increase the amount of information to be encoded – [0255]).
Regarding claim 9 Kim discloses the apparatus according to claim 1, wherein the two or more feature channels are for multiple tasks of the neural network, and the processor is further configured to execute the instructions to cause the apparatus to: determine the importance of the feature channel for each of the multiple tasks (an importance map (IM) representing the importance of the feature set and/or the channel may be defined. In the present disclosure, importance may mean a priority of data/information required to perform a predetermined machine-oriented task – [0255]; each channel may have a different importance depending on the task purpose and the surrounding environment; for example, in a surveillance system, channels present in a region of interest (ROI) may have higher importance than channels present in a background area – [0329]).
Regarding claim 10 Kim discloses the apparatus according to claim 9, wherein the determining of the importance includes estimating mutual information for each pair of the feature channels and the multiple tasks, wherein the importance includes a task importance of a task among the multiple tasks, and wherein the task importance includes a priority of the task and/or a frequency of usage of the task (an importance map (IM) representing the importance of the feature set and/or the channel may be defined. In the present disclosure, importance may mean a priority of data/information required to perform a predetermined machine-oriented task – [0255]; each channel may have a different importance depending on the task purpose and the surrounding environment; for example, in a surveillance system, channels present in a region of interest (ROI) may have higher importance than channels present in a background area – [0329]).
Regarding claim 11 Kim discloses the apparatus according to claim 10, wherein the processor is configured to execute the instructions to cause the apparatus to: select a quantization step or the bit depth as the one or more encoding parameters; the higher the importance of the feature channel, the smaller the quantization step; and the importance is given as a function of the mutual information and the task importance (feature quantization/dequantization may be performed based on the importance of a feature set and/or a channel; for example, for feature sets and/or channels with relatively high importance, the quantization interval may be narrowed to minimize information loss, and, for feature sets and/or channels with relatively low importance, the quantization interval may be widened to increase the amount of information to be encoded – [0255]).
Regarding claim 12 Kim discloses the apparatus according to claim 1, wherein the neural network is trained for one or more of picture segmentation, object recognition, object classification, disparity estimation, depth map estimation, face detection, face recognition, pose estimation, object tracking, action recognition, event detection, prediction, and picture reconstruction (the decoded video may be utilized as input information for performing AI tasks such as face recognition, behavior recognition, and lane recognition – [0080]).
Regarding claim 13 Kim discloses the apparatus according to claim 1, wherein the processor is configured to execute the instructions to cause the apparatus to:
for each feature channel, determine whether the importance of the feature channel exceeds a predetermined threshold; based on the importance of the feature channel exceeding the predetermined threshold, selecting for the feature channel the at least one encoding parameter leading to a first quality; based on the importance of the feature channel not exceeding the predetermined threshold, selecting for the feature channel the at least one encoding parameter leading to a second quality lower than the first quality (feature quantization/dequantization may be differentially performed based on the importance of the above-described feature set and/or channel. That is, a differential number of quantization bits according to importance of each feature set and/or channel may be applied. For example, in the first feature set fF0, the second region 1720 having relatively highest importance may be quantized to 12 bits. Also, in the first feature set fF0, the first region 1710 having relatively high importance may be quantized to 10 bits. In addition, in the first feature set fF0, the remaining region having relatively low importance may be quantized to 8 bits – [0264]; as the importance of the feature set and/or the channel is more subdivided (that is, as the number of bits of the importance value increases), the quantization performance may be further improved. However, as a result, the amount of information in the importance map increases, which may cause a side effect of lowering encoding/signaling efficiency – [0266]).
In regards to claim 14, any encoder technology that is present in an encoder also necessarily needs to be present, in substantially identical form in a corresponding decoder. The description of decoder technologies can be abbreviated as they are the inverse of the comprehensively described encoder technologies. Therefore, claim 14 is being rejected in the same basis as claim 1.
Claim 15 corresponds to the method performed by the apparatus of claim 1. Therefore, claim 15 is being rejected on the same basis as claim 1.
In regards to claim 16, any encoding technology that is present in an encoder also necessarily needs to be present, in substantially identical form in a corresponding decoder. The description of decoder technologies can be abbreviated as they are the inverse of the comprehensively described encoder technologies.
Claim 17 corresponds to the non-transitory computer-readable medium storing a program. Including instructions which upon execution by one or more processors cause the one or more processors to perform the method of claim 15. Therefore, claim 17 is being rejected on the same basis as claim 15.
Claim 18 corresponds to the method performed by the apparatus of claim 2. Therefore, claim 18 is being rejected on the same basis as claim 2.
Claim 19 corresponds to the method performed by the apparatus of claim 3. Therefore, claim 19 is being rejected on the same basis as claim 3.
Claim(s) 8 is/are rejected under 35 U.S.C. 103 as being unpatentable over Kim et al. (US 2023/0082562) in view of Zhang et al. (US 2017/0064336) further in view of Wei et al. (CN 113965750 A, translation of description used) further in view of Ahn et al. (US 2023/0421764).
Regarding claim 8 Kim discloses the apparatus according to claim 1. However, fails to explicitly disclose wherein the higher the importance of the feature channel, the larger the bit depth.
In his disclosure Ahn teaches wherein the higher the importance of the feature channel, the larger the bit depth (in a channel quantization step, feature map quantization may be performed by applying a different quantization method according to a class classified in the step. In this case, a different quantization method may represent that a quantization step is different; alternatively, a different quantization method may represent that a bit depth of a quantized value is different – [0229]).
It would have been obvious to a person with ordinary skill in the art, before the effective filing date of the claimed invention, to incorporate the teachings of Ahn into the teachings of Kim because the use of bit depth information is a well-known technique in the art.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MARIA E VAZQUEZ COLON whose telephone number is (571)270-1103. The examiner can normally be reached M-F 7:30 AM-3:30 PM.
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/MARIA E VAZQUEZ COLON/Examiner, Art Unit 2482
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