DETAILED ACTION
Final Rejection
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 .
Response to Amendment
Applicant’s amendments, filed 05/18/2026 to claims are accepted. In this amendment, claims 1 and 4-9 have been amended. Regarding Claims 2-3: cancelled.
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 and 4-9 are rejected under 35 U.S.C. 112(b) or pre-AIA 35 U.S.C. 112, 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 pre-AIA the applicant regards as the invention.
Claims 1 and 8-9 recites the limitation "a higher closeness". The term "closeness" is considered to be indefinite because specification fail to provide any objective, distinct boundaries of higher closeness between clusters.
Remaining claims are also rejected due to dependency of the base independent claims.
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 and 4-9 are rejected under 35 U.S.C. § 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1
Each of claims 1 and 4-9 falls within one of the four statutory categories. See MPEP § 2106.03. For example each of claims 1and 4- 7 fall within category of machine, i.e., a “concrete thing, consisting of parts, or of certain devices and combination of devices.” Digitech, 758 F.3d at 1348–49, 111 USPQ2d at 1719 (quoting Burr v. Duryee, 68 U.S. 531, 570, 17 L. Ed. 650, 657 (1863)), For each of claims 8-9 fall within category of process;
Regarding Claims 1and 4-7
Step 2A – Prong 1
Exemplary claim 1 is directed to an abstract idea of assign a predetermined label to each of the clusters.
The abstract idea is set forth or described by the following italicized limitations:
1. An annotation apparatus comprising:
at least one memory storing instructions; and
at least one processor configured to execute the instructions to:
generate a plurality of clusters by grouping point cloud data corresponding to three-dimensional position information about a measurement target;
determine a presentation order of the plurality of clusters based on a degree of similarity between the generated plurality of clusters;
present the plurality of clusters in order based on the determined presentation order; and
assign a predetermined label to each of the plurality of clusters presented in the order;
wherein the at least one processor is further configured to execute the instructions to:
determine the presentation order of the plurality of clusters based on at least one of a degree of spatial similarity or a degree of visual similarity between the plurality of clusters;
determine that a higher closeness of a spatial positional relationship between the plurality of clusters corresponds to a higher degree of the spatial similarity,
determine that a higher closeness of appearances of the plurality of clusters corresponds to a higher visual similarity, and
create a graph by coupling each of the plurality of clusters with edges based on the spatial similarity between the plurality of clusters.
he italicized limitations above represent a combination of mathematical concept (i.e., a process that can be performed by mathematical relationships or rules or idea) and mental step (i.e., a process that can be performed by can be performed mentally and/or with pen and paper or a mental judgment) . Therefore, the italicized limitations fall within the subject matter groupings of abstract ideas enumerated in Section I of the 2019 Revised Patent Subject Matter Eligibility Guidance.
For example, the limitation “determine a presentation order of the plurality of clusters[..]; present the plurality of clusters in order[..]; assign a predetermined label to each of the clusters [..];determine the presentation order of the plurality of clusters [..]; determine that a higher closeness [..], determine that a higher closeness of appearances of the plurality of clusters [..], and create a graph by coupling each of the plurality of clusters [..]” are combination of mathematical concepts (i.e., a process that can be performed by mathematical relationships or rules or idea) and mental steps (i.e., a process that can be performed by can be performed mentally and/or with pen and paper or a mental judgment).
See 2106.04(a)(2)(I). Limitations are considered together as a single abstract idea for further analysis. (discussing Bilski v. Kappos, 561 U.S. 593 (2010)).
Step 2A – Prong 2
Claims 1 does not include additional elements (when considered individually, as an ordered combination, and/or within the claim as a whole) that are sufficient to integrate the abstract idea into a practical application.
The 1st additional element is “a cluster generation unit configured to generate a plurality of clusters by grouping point cloud data corresponding to three-dimensional position information about a measurement target”. This element appears to limit the “collecting data” to be performed, at least in-part, by use of a memory and to be performed, at least in-part, these additional elements appear to only add insignificant extra-solution activity (e.g., data gathering) and only generally link the abstract idea to a particular field. Therefore, this element individually or as a whole does not provide a practical application. see MPEP §§ 2106.05(g).
For example, 2nd additional first element is “An annotation apparatus comprising: at least one memory storing instructions; and at least one processor configured to execute the instructions to”. This element amounts to mere use of a generic device with computer components, which is well understood routine and conventional (see background of current discloser and IDS and PTO 892) and this element individually does not provide a practical application. In view of the above, the “additional element” individually or combine does not provide a practical application of the abstract idea. see MPEP 2106.05(d).
In view of the above, the two “additional elements” individually do not provide a practical application of the abstract idea. Furthermore, the “additional elements” in combination amount to a plurality of generic control system with computer component with software, where such computers and software amount to mere instructions to implement the abstract idea on a computer(s) and/or mere use of a generic computer component(s) as a tool to perform the abstract idea. Therefore, these elements in combination do not provide a practical application. The combination of additional elements does no more than generally link the use of the abstract idea to a particular technological environment, and for this additional reason, the combination of additional elements does not provide a practical application of the abstract idea.
Step 2B
Claims 1 does not include additional elements, when considered individually and as an ordered combination, that are sufficient to amount to significantly more than the abstract idea.
For example, the limitation of Claims “annotation apparatus”, generic computer component, which are well understood, routine and conventional (see background of current discloser, IDS and the Examiner cited prior arts) and MPEP 2106.05(d)).
The reasons for reaching this conclusion are substantially the same as the reasons given above in § Step 2A – Prong 2. For brevity only, those reasons are not repeated in this section. See MPEP §§ 2106.05(g) and MPEP §§2106.05(II).
Dependent Claims 2 and 4-7
Dependent claims 2-7 fail to cure this deficiency of independent claim 1 (set forth above) and are rejected accordingly. Particularly, claims 2 and 4-7 recite limitations that represent (in addition to the limitations already noted above) either the abstract idea or an additional element that is merely extra-solution activity, mere use of instructions and/or generic computer component(s) as a tool to implement the abstract idea, and/or merely limits the abstract idea to a particular technological environment.
For example, the limitations of Claims 2 and 4-7: claims limitations are directed to mental steps (i.e., a process that can be performed by can be performed mentally and/or with pen and paper or a mental judgment), see 2106.04(a)(2).
Regarding Claims 8-9
Claims 8-9 contains language similar to claim 1 as discussed in the preceding paragraphs, and for reasons similar to those discussed above, claims 8-9 are also rejected under 35 U.S.C. § 101(abstract idea).
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 and 4-9 is/are rejected under 35 U.S.C. 103 as being unpatentable over Niigaki et al. (US 2023/0260216) in view of Chen et al. (US 11675766)(best understood by the Examiner based on 112 indefiniteness).
Regarding Claims 1 and 8-9: Niigaki teaches an annotation apparatus comprising(abstract; 100:fig. 1; fig. 7):
a cluster generation unit (26: fig. 1) configured to generate a plurality of clusters by grouping point cloud data corresponding to three-dimensional position information about a measurement target (The cluster area generation unit 26 clusters the point clouds indicating the three-dimensional points on the object (i.e. target object: abstract)stored in the three-dimensional point cloud storage unit 24 to obtain point cloud clusters, and generates a large number of point cloud clusters through an AND or OR process between the point cloud clusters:[0050]; three-dimensional point clouds are grouped using physical information such as a distance or color as an index: [0035]);
a presentation order determination unit (32: fig. 1) configured to determine a presentation order (i.e. descending order: abstract, [0066]) of the plurality of clusters based on a degree of similarity between the generated plurality of clusters(calculation unit 32 calculates a value of a predetermined evaluation function indicating a likelihood of a point cloud cluster being the annotation target object based on the designation of a three-dimensional point for point cloud clusters obtained by clustering the point clouds: abstract, [0063]; fig. 13);
a cluster presentation unit (90: fig. 1)configured to present the plurality of clusters in order based on the determined presentation order(the interface unit 22 to display the point cloud clusters in descending order of the value of the evaluation function, and receives a selection of a point cloud cluster to be annotated: abstract; [0066]; fig. 13, [0087]); and
a label assignment unit configured to assign a predetermined label (i.e. cable, pole) (annotation is performed on a plurality of types of target objects, this means that different numbers are imparted for different types of target objects, for example, 10 being imparted to a utility pole and 20 being imparted to a cable:[0037]; [0087]-[0088], [0082],[0084],).
the presentation order determination unit determines the presentation order of the plurality of clusters based on at least one of a degree of spatial similarity (i.e. number) or a degree of visual similarity (i.e. pole, cable)between the plurality of clusters (a plurality of types of target objects, this means that different numbers are imparted for different types of target objects, for example, 10 being imparted to a utility pole and 20 being imparted to a cable: [0037]; fig. 13; point cloud clusters to be displayed in descending order: [0088]);
Niigaki silent about a label assignment unit configured to assign a predetermined label to each of the clusters presented in the order;
determine that a higher closeness of a spatial positional relationship between the plurality of clusters corresponds to a higher degree of the spatial similarity,
determine that a higher closeness of appearances of the plurality of clusters corresponds to a higher visual similarity, and
create a graph by coupling each of the plurality of clusters with edges based on the spatial similarity between the plurality of clusters.
However, Chen teaches a label assignment unit configured to assign a predetermined label to each of the clusters presented in the order (the node labels for cluster's nodes are first replaced by the label of the cluster's RN (element 810) in the edge-reduction algorithm. In addition, the similarity scores between the RNs of the different clusters are set to a tuple whose elements are the similarity scores of the corresponding inter-cluster edges. Thus, for example, in version 888 of the graph 887 obtained after operations corresponding to element 810 have been performed, all the nodes of C1 have been labeled “A” (because A was the RN for C1), and the similarity score between nodes A and N (the RN of cluster C4) has been set to the tuple {0.15, 0.6} because the similarity score between nodes C and P was 0.15 and the similarity score between nodes F and N was 0.6: col. 18, l. 63-col. 19, l. 45; figs 8a-8b)
determine that a higher closeness of a spatial positional relationship between the plurality of clusters corresponds to a higher degree of the spatial similarity(version 888 of the graph 887 obtained after operations corresponding to element 810 have been performed, all the nodes of C1 have been labeled “A” (because A was the RN for C1), and the similarity score between nodes A and N (the RN of cluster C4) has been set to the tuple {0.15, 0.6} because the similarity score between nodes C and P was 0.15 and the similarity score between nodes F and N was 0.6; : col. 18, l. 63-col. 19, l. 45; figs 8a-8b),
determine that a higher closeness of appearances of the plurality of clusters corresponds to a higher visual similarity( version 888 of the graph 887 obtained after operations corresponding to element 810 have been performed, all the nodes of C1 have been labeled “A” (because A was the RN for C1), and the similarity score between nodes A and N (the RN of cluster C4) has been set to the tuple {0.15, 0.6} because the similarity score between nodes C and P was 0.15 and the similarity score between nodes F and N was 0.6; : col. 18, l. 63-col. 19, l. 45; figs 8a-8b), and
create a graph by coupling each of the plurality of clusters with edges based on the spatial similarity between the plurality of clusters(888: fig. 8B).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to the invention of Niigaki, a label assignment unit configured to assign a predetermined label to each of the clusters presented in the order; determine that a higher closeness of a spatial positional relationship between the plurality of clusters corresponds to a higher degree of the spatial similarity, determine that a higher closeness of appearances of the plurality of clusters corresponds to a higher visual similarity, and create a graph by coupling each of the plurality of clusters with edges based on the spatial similarity between the plurality of clusters.
Regarding Claim 4: Niigaki silent about set a weight for each of the edges coupling the plurality clusters based on the visual similarity between the plurality of clusters, and determine the presentation order of each of the plurality of clusters based on the set weight of each of the edges.
However, Chen teaches set a weight for each of the edges coupling the clusters based on the visual similarity between the plurality of clusters, and determines the presentation order of each of the clusters based on the set weight of each of the edges ((figs. 7-8; col. 18, l. 2-52))
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to the invention of Niigaki, et a weight for each of the edges coupling the plurality clusters based on the visual similarity between the plurality of clusters, and determine the presentation order of each of the plurality of clusters based on the set weight of each of the edges, as taught by Chen, so as to identify a representative node from a cluster.
Regarding claim 5: Chen further teaches create a minimum spanning tree of the plurality of clusters based on the set weight of each of the edges(col. 2, l. 46-67;col. 3, l.62-col.4, l. 10; figs. 7-8),
Perform a depth-first search on the minimum spanning tree to determine the presentation order of each of the plurality of clusters (find shortest paths between each pair of nodes of the cluster: 710: fig. 7)
Regarding Claim 6: Chen further teaches the depth-first search on the minimum spanning tree, prioritizing reduction in a spatial gap between the clusters(710: fig 7; fig. 8).
Regarding Claim 7: Niigaki teaches sequentially present each of the plurality of clusters in order based on determined the presentation order, and assign a label to each of the sequentially presented clusters according to a predetermined input (cluster storage unit 28 based on user designation of the three-dimensional point indicating the annotation target object and designation of the three-dimensional point not indicating the annotation target object on the GUI screen displayed by the information presenting unit: [0063]-[0064], [0077]; The cluster selection and storage designation unit 34 causes the information presenting unit 90 to display the GUI screen for displaying the point cloud clusters in descending order of the value of the evaluation function via the interface unit 22, and receives the designation of a point cloud cluster to be annotated: [0066] ).
Response to Argument
Applicant’s arguments with respect 101 rejection, specially claims 1 and 4-9, The applicant did not agree with it, see, pages 7-9
In response, the Examiner respectfully disagree because limitations of claims, specifically claim 1 represent a combination of mathematical concept (i.e., a process that can be performed by mathematical relationships or rules or idea) and mental step (i.e., a process that can be performed by can be performed mentally and/or with pen and paper or a mental judgment).. Therefore, the limitations, specifically claim1, above fall within the subject matter groupings of abstract ideas enumerated in Section I of the 2019 Revised Patent Subject Matter Eligibility Guidance. In view of the above, the three “additional elements” individually do not provide a practical application of the abstract idea. Furthermore, the “additional elements” in combination amount to a generic computer component with software, where such computers and software amount to mere instructions to implement the abstract idea on a computer(s) and/or mere use of a generic computer component(s) as a tool to perform the abstract idea. Therefore, these elements in combination do not provide a practical application. The combination of additional elements does no more than generally link the use of the abstract idea to a particular technological environment, and for this additional reason, the combination of additional elements does no more than generally link the use of the abstract idea to a particular technological environment, and for this additional reason, the additional element does not provide a practical application of the abstract idea. Claim invention only recite the idea of a solution or outcome “outputting an analysis result” and do not include any details about how the “outputting a analysis result” is accomplished. See MPEP 2106.05(f). As such 101 rejection is maintained.
Applicant’s arguments with respect 102 rejection, specially claims 1, The applicant did not agree with it, see, pages 9-12, Applicant argus that “neither Niigaki nor Chen teaches a processor configured to "create a graph by coupling each of the plurality of clusters with edges based on a degree of spatial similarity between the plurality of clusters” ; “neither Niigaki nor Chen discloses or suggest a processor configured to "create a graph by coupling each of the plurality of clusters with edges based on a degree of spatial similarity between the plurality of clusters," as recited in claim 1.”
In response, the Examiner respectfully disagree because current clam rejection based on border reasonable interpretation and best understood by the Examiner based on 112 indefiniteness, as such Niigaki teaches the presentation order determination unit determines the presentation order of the plurality of clusters based on at least one of a degree of spatial similarity (i.e. number) or a degree of visual similarity (i.e. pole, cable)between the plurality of clusters (a plurality of types of target objects, this means that different numbers are imparted for different types of target objects, for example, 10 being imparted to a utility pole and 20 being imparted to a cable: [0037]; fig. 13; point cloud clusters to be displayed in descending order: [0088]); and Chen teaches a label assignment unit configured to assign a predetermined label to each of the clusters presented in the order (the node labels for cluster's nodes are first replaced by the label of the cluster's RN (element 810) in the edge-reduction algorithm. In addition, the similarity scores between the RNs of the different clusters are set to a tuple whose elements are the similarity scores of the corresponding inter-cluster edges. Thus, for example, in version 888 of the graph 887 obtained after operations corresponding to element 810 have been performed, all the nodes of C1 have been labeled “A” (because A was the RN for C1), and the similarity score between nodes A and N (the RN of cluster C4) has been set to the tuple {0.15, 0.6} because the similarity score between nodes C and P was 0.15 and the similarity score between nodes F and N was 0.6: col. 18, l. 63-col. 19, l. 45; figs 8a-8b); determine that a higher closeness of a spatial positional relationship between the plurality of clusters corresponds to a higher degree of the spatial similarity(version 888 of the graph 887 obtained after operations corresponding to element 810 have been performed, all the nodes of C1 have been labeled “A” (because A was the RN for C1), and the similarity score between nodes A and N (the RN of cluster C4) has been set to the tuple {0.15, 0.6} because the similarity score between nodes C and P was 0.15 and the similarity score between nodes F and N was 0.6; : col. 18, l. 63-col. 19, l. 45; figs 8a-8b); determine that a higher closeness of appearances of the plurality of clusters corresponds to a higher visual similarity( version 888 of the graph 887 obtained after operations corresponding to element 810 have been performed, all the nodes of C1 have been labeled “A” (because A was the RN for C1), and the similarity score between nodes A and N (the RN of cluster C4) has been set to the tuple {0.15, 0.6} because the similarity score between nodes C and P was 0.15 and the similarity score between nodes F and N was 0.6; : col. 18, l. 63-col. 19, l. 45; figs 8a-8b), and create a graph by coupling each of the plurality of clusters with edges based on the spatial similarity between the plurality of clusters(888: fig. 8B). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to the invention of Niigaki, a label assignment unit configured to assign a predetermined label to each of the clusters presented in the order; determine that a higher closeness of a spatial positional relationship between the plurality of clusters corresponds to a higher degree of the spatial similarity, determine that a higher closeness of appearances of the plurality of clusters corresponds to a higher visual similarity, and create a graph by coupling each of the plurality of clusters with edges based on the spatial similarity between the plurality of clusters. As such 103 rejection is maintained.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
a) Covell et al. (US 9137529) disclose a new mapping is obtained that improves a measure of association between clusters and labels. The new mapping is used to generate a new prediction model. This process is repeated in order to iteratively refine the machine learning modes generated.
b) Vineet et al. (Fast Minimum Spanning Tree for Large Graphs on the GPU, 2009)
c) Hebert et al. (US 20160103958) disclose traversal can start at the first member of the cluster and a representative sequence can be sampled at every T. Representative sequences for a candidate cluster can be selected such that representative sequences are approximately the same distance from each other, in this case, the threshold distance. As such, small clusters (with a diameter less than the threshold) may only have a single representative sequence. Representatives for large clusters are produced through organization of the sequences in a candidate cluster into a minimum spanning tree, a network structure representing the shortest path between any two sequences, and sampling from the tree. A minimum spanning tree can be generated for each candidate cluster using Prim's Algorithm [47] and can be updated with the addition of sequences to the candidate cluster. To test the membership of a new sequence to existing clusters a series of steps can be taken to reduce the search space:
d) Fuchs et al. (US 2020/0285890) disclose a Euclidean distance or an L-norm distance) between the identified point 972 and each of the centroids 974. Using the calculated distance metrics, the cluster analyzer 918 may identify the centroid 974 to which the point 972 is most proximate (e.g., in terms of Euclidean distance or L-norm distance): [0137]), (The cluster analyzer 918 may calculate or determine a distance metric (974B(X): fig. 9g).
e) Berger et al. (US 11798173 ) disclose the graph are points from the semantic labeled point cloud and edges of the graph connect nodes with respective points that satisfy a pairwise criteria. Each of the points of the point cloud can be considered as a node in a graph, which can be connected to its k nearest neighborhood points through bidirectional edges. In some implementations, edges are defined with respective weights and only edges with weights that meet a threshold are created in the graph, i.e., the threshold on the weight may be the pairwise criteria satisfied by a pair of points whose nodes are connected by an edge in the graph. For example, edge weights may be defined as a difference (e.g., Diff(node1, node2) between a respective values (e.g., position, normals, colors, lidar intensity, etc.) for two points/nodes: col. 8, l. 41-62; Col. 14, l. 16-31; fig. 6
d) Mcgaughy et al. (US 7,836,419) disclose graphical representation of merging a group of graphs to their corresponding circuit partitions according to an embodiment of the present invention. As shown in FIG. 12, on the left hand side, there are three graphs. The first graph includes the vertices P5, P6, P7, P8, and P9. The second graph includes the vertices P2, P3, and P4, and the third graph includes only the vertex P1. From the group of graphs, a corresponding group of minimum spanning trees is generated using a depth-first search method. The group of minimum spanning trees is illustrated in the middle of FIG. 12. Note that a minimum spanning tree has no loop. Each circuit partition is represented by a vertex in a minimum spanning tree. All vertices in a minimum spanning tree are circuit partitions to be merged together. The first spanning tree includes the vertices P5, P6, P7, P8, and P9. The second spanning tree includes the vertices P2, P3, and P4, and the third spanning tree includes only the vertex P1. The edges in a graph are followed to identify all circuit partitions within a minimum spanning tree to be combined together to form a new circuit partition. On the right hand side of FIG. 12, after all the circuit partitions in a minimum spanning tree have been merged, there are only three partitions, namely a first partition that includes previous circuit partitions P5, P6, P7, P8, and P9. A second partition includes the previous circuit partitions P2, P3, and P4;
Contact Information
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MOHAMMAD K ISLAM whose telephone number is (571)270-0328. The examiner can normally be reached M-F 9:00 a.m. - 5:00 p.m..
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Shelby A Turner can be reached at 571-272-6334. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/MOHAMMAD K ISLAM/Primary Examiner, Art Unit 2857
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