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 § 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.
Claims 1-15 are rejected under 35 U.S.C. 103 as being unpatentable over Goonetilleke (US20090051683) “Goonetilleke”, in view of Lee et al. (“Taiwanese adult foot shape classification using 3D scanning data” Ergonomics, 58(3), 513–523.) “Lee”.
Regarding claim 1, Goonetilleke discloses a body shape analysis device (Fig. 1), comprising: a model storage unit (1501) configured to store, a plurality of body shapes (“foot shapes”) with a plurality of three-dimensional coordinate groups ([0023]), such that a three-dimensional coordinate group ([0023]) of the plurality of three-dimensional coordinate groups ([0023]) indicating an anatomical feature (102) of at least part of a body (102 is part of a body); a measurement data acquirer (601, 602, 603, 604) configured to acquire, as measurement data (1505), a measured three-dimensional coordinate group ([0023]) indicating a measured anatomical feature (102); and an evaluation determination unit (1513; “computer program” and [0045]-[0046]).
Goonetilleke does not disclose a plurality of three-dimensional homologous models, nor determining similarities in coordinates.
Lee teaches a plurality of three-dimensional homologous models (section 2.1), and determining similarities in coordinates (section 2.1).
It would have been obvious to one of ordinary skill in the art before the effective filing date to configure Goonetilleke’s model storage unit and evaluation determination unit to store a plurality of Lee’s three-dimensional homologous models to evaluate similarities in coordinates to more accurately determine body part shape matches.
Regarding claim 2, Goonetilleke discloses the body shape analysis device according to claim 1.
Goonetilleke does not disclose a position vector from a predetermined reference point.
Lee teaches in figure 4 and section 2.3, a position vector from a predetermined reference point.
It would have been obvious to one of ordinary skill in the art before the effective filing date to use Lee’s position vector and predetermined reference point in Goonetilleke’s body shape analysis device so that Goonetilleke’s evaluation determination unit can more accurately measure a body shape and compare to Lee’s three-dimensional homologous models.
Regarding claim 3, Goonetilleke discloses the body shape analysis device according to claim 1.
Goonetilleke does not disclose a plurality of clusters by cluster analysis based on cosine similarity between position vectors from a predetermined reference point to respective points in the three-dimensional homologous models.
Lee teaches a plurality of clusters by cluster analysis (section 2.4) based on cosine similarity (“Euclidean distance”) between position vectors (section 2.3) from a predetermined reference point to respective points (section 3.5) in the three-dimensional homologous models.
It would have been obvious to one of ordinary skill in the art before the effective filing date to use Lee’s cluster analysis based on cosine similarity in Goonetilleke’s model storage unit to better find a matching body shape based on shape and proportions, not size.
Regarding claim 4, Goonetilleke discloses the body shape analysis device according to claim 2.
Goonetilleke does not disclose the plurality of three-dimensional homologous models are classified into a plurality of clusters by cluster analysis based on cosine similarity between position vectors from a predetermined reference point to respective points in the three-dimensional homologous models and are stored in the model storage unit.
Lee teaches the plurality of three-dimensional homologous models are classified into a plurality of clusters by cluster analysis (section 2.4) based on cosine similarity (“Euclidean distance”) between position vectors (section 2.3) from a predetermined reference point to respective points (section 3.5) in the three-dimensional homologous models.
It would have been obvious to one of ordinary skill in the art before the effective filing date to use Lee’s cluster analysis based on cosine similarity in Goonetilleke’s model storage unit to better find a matching body shape based on shape and proportions, not size.
Regarding claim 5, Goonetilleke discloses a body shape analysis device (Fig. 1), comprising: a model storage (1501) unit configured to store, a plurality of body shapes (“foot shapes”) with a plurality of three-dimensional coordinate groups ([0023]), such that a three-dimensional coordinate group ([0023]) of the plurality of three-dimensional coordinate groups ([0023]) indicates an anatomical feature of a foot (102), and an output unit (14).
Goonetilleke does not disclose a plurality of three-dimensional homologous models, nor a plurality of clusters by cluster analysis based on cosine similarity between position vectors from a predetermined reference point to respective points in the three-dimensional homologous models.
Lee teaches a plurality of three-dimensional homologous models (section 2.1), and a plurality of clusters by cluster analysis (section 2.4) based on cosine similarity (“Euclidean distance”) between position vectors (section 2.3) from a predetermined reference point to respective points (section 3.5) in the three-dimensional homologous models.
It would have been obvious to one of ordinary skill in the art before the effective filing date to use Lee’s cluster analysis to sort feet by shape with Goonetilleke’s output unit to generate an accurate representation of a foot shape.
Regarding claim 6, Goonetilleke discloses the body shape analysis device according to claim 3.
Goonetilleke does not disclose the plurality of three-dimensional homologous models are classified into a plurality of clusters in an upper layer by cluster analysis based on cosine similarity and are further classified into a plurality of more detailed clusters in a lower layer by performing cluster analysis on each cluster in the upper layer based on principal component analysis of which results are dimensionally reduced to the second and the subsequent principal components excluding the first principal component.
Lee teaches the plurality of three-dimensional homologous models (section 2.1) are classified into a plurality of clusters (section 2.4) in an upper layer by cluster analysis (section 3.4) based on cosine similarity (“Euclidean distance”) and are further classified into a plurality of more detailed clusters (section 2.4 and table 4) in a lower layer by performing cluster analysis (section 3.4) on each cluster in the upper layer based on principal component analysis (section 2.4 and 3.1) of which results are dimensionally reduced to the second and the subsequent principal components (section 2.4 and 3.1) excluding the first principal component.
It would have been obvious to one of ordinary skill in the art before the effective filing date to use Lee’s principal component analysis in Goonetilleke’s body shape analysis device to filter out size variations and allow the system to generate more detailed clusters based on foot shapes and proportions.
Regarding claim 7, Goonetilleke discloses the body shape analysis device according to claim 4.
Goonetilleke does not disclose the plurality of three-dimensional homologous models are classified into a plurality of clusters in an upper layer by cluster analysis based on cosine similarity and are further classified into a plurality of more detailed clusters in a lower layer by performing cluster analysis on each cluster in the upper layer based on principal component analysis of which results are dimensionally reduced to the second and the subsequent principal components excluding the first principal component.
Lee teaches the plurality of three-dimensional homologous models (section 2.1) are classified into a plurality of clusters (section 2.4) in an upper layer (section 2.4) by cluster analysis (section 3.4) based on cosine similarity (“Euclidean distance”) and are further classified into a plurality of more detailed clusters (section 2.4 and table 4) in a lower layer by performing cluster analysis (section 3.4) on each cluster in the upper layer based on principal component analysis (section 2.4 and 3.1) of which results are dimensionally reduced to the second and the subsequent principal components (section 2.4 and 3.1) excluding the first principal component.
It would have been obvious to one of ordinary skill in the art before the effective filing date to use Lee’s principal component analysis in Goonetilleke’s body shape analysis device to filter out size variations and allow the system to generate more detailed clusters based on foot shapes and proportions.
Regarding claim 8, Goonetilleke discloses the body shape analysis device according to claim 5.
Goonetilleke does not disclose the plurality of three-dimensional homologous models are classified into a plurality of clusters in an upper layer by cluster analysis based on cosine similarity and are further classified into a plurality of more detailed clusters in a lower layer by performing cluster analysis on each cluster in the upper layer based on principal component analysis of which results are dimensionally reduced to the second and the subsequent principal components excluding the first principal component.
Lee teaches the plurality of three-dimensional homologous models (section 2.1) are classified into a plurality of clusters (section 2.4) in an upper layer (section 2.4) by cluster analysis (section 3.4) based on cosine similarity (“Euclidean distance”) and are further classified into a plurality of more detailed clusters (section 2.4 and table 4) in a lower layer by performing cluster analysis (section 3.4) on each cluster in the upper layer based on principal component analysis (section 2.4 and 3.1) of which results are dimensionally reduced to the second and the subsequent principal components (section 2.4 and 3.1) excluding the first principal component.
It would have been obvious to one of ordinary skill in the art before the effective filing date to use Lee’s principal component analysis in Goonetilleke’s body shape analysis device to filter out size variations and allow the system to generate more detailed clusters based on foot shapes and proportions.
Regarding claim 9, Goonetilleke discloses the body shape analysis device according to claim 3.
Goonetilleke does not disclose a value indicating demand for each of the plurality of three-dimensional homologous models classified into a plurality of clusters, based on a number of the three-dimensional homologous models in each cluster for a plurality of clusters classified by cluster analysis.
Lee teaches a value indicating demand (table 4 and 5; population percentages) for each of the plurality of three-dimensional homologous models (section 2.1) classified into a plurality of clusters (section 2.4 and table 4), based on a number of the three-dimensional homologous models (section 2.1) in each cluster for a plurality of clusters classified by cluster analysis (section 3.4).
It would have been obvious to one of ordinary skill in the art before the effective filing date to use Lee’s value indicating demand in Goonetilleke’s model storage unit, making it easier to determine demand for shoes based on foot shape.
Regarding claim 10, Goonetilleke discloses the body shape analysis device according to claim 4.
Goonetilleke does not disclose a value indicating demand for each of the plurality of three-dimensional homologous models classified into a plurality of clusters, based on a number of the three-dimensional homologous models in each cluster for a plurality of clusters classified by cluster analysis.
Lee teaches a value indicating demand (table 4 and 5; population percentages) for each of the plurality of three-dimensional homologous models (section 2.1) classified into a plurality of clusters (section 2.4 and table 4), based on a number of the three-dimensional homologous models (section 2.1) in each cluster for a plurality of clusters classified by cluster analysis (section 3.4).
It would have been obvious to one of ordinary skill in the art before the effective filing date to use Lee’s value indicating demand in Goonetilleke’s model storage unit, making it easier to determine demand for shoes based on foot shape.
Regarding claim 11, Goonetilleke discloses the body shape analysis device according to claim 5.
Goonetilleke does not disclose a value indicating demand for each of the plurality of three-dimensional homologous models classified into a plurality of clusters, based on the number of the three-dimensional homologous models in each cluster for a plurality of clusters classified by cluster analysis.
Lee teaches a value indicating demand (table 4 and 5; population percentages) for each of the plurality of three-dimensional homologous models (section 2.1) classified into a plurality of clusters (section 2.4 and table 4), based on a number of the three-dimensional homologous models (section 2.1) in each cluster for a plurality of clusters classified by cluster analysis (section 3.4).
It would have been obvious to one of ordinary skill in the art before the effective filing date to use Lee’s value indicating demand in Goonetilleke’s model storage unit, making it easier to determine demand for shoes based on foot shape.
Regarding claim 12, Goonetilleke discloses the body shape analysis device according to claim 6.
Goonetilleke does not disclose a value indicating demand for each of the plurality of three-dimensional homologous models classified into a plurality of clusters, based on the number of the three-dimensional homologous models in each cluster for a plurality of clusters classified by cluster analysis.
Lee teaches a value indicating demand (table 4 and 5; population percentages) for each of the plurality of three-dimensional homologous models (section 2.1) classified into a plurality of clusters (section 2.4 and table 4), based on a number of the three-dimensional homologous models (section 2.1) in each cluster for a plurality of clusters classified by cluster analysis (section 3.4).
It would have been obvious to one of ordinary skill in the art before the effective filing date to use Lee’s value indicating demand in Goonetilleke’s model storage unit, making it easier to determine demand for shoes based on foot shape.
Regarding claim 13, Goonetilleke discloses the body shape analysis device according to claim 7.
Goonetilleke does not disclose a value indicating demand for each of the plurality of three-dimensional homologous models classified into a plurality of clusters, based on the number of the three-dimensional homologous models in each cluster for a plurality of clusters classified by cluster analysis.
Lee teaches a value indicating demand (table 4 and 5; population percentages) for each of the plurality of three-dimensional homologous models (section 2.1) classified into a plurality of clusters (section 2.4 and table 4), based on a number of the three-dimensional homologous models (section 2.1) in each cluster for a plurality of clusters classified by cluster analysis (section 3.4).
It would have been obvious to one of ordinary skill in the art before the effective filing date to use Lee’s value indicating demand in Goonetilleke’s model storage unit, making it easier to determine demand for shoes based on foot shape.
Regarding claim 14, Goonetilleke discloses the body shape analysis device according to claim 8.
Goonetilleke does not disclose a value indicating demand for each of the plurality of three-dimensional homologous models classified into a plurality of clusters, based on a number of the three-dimensional homologous models in each cluster for a plurality of clusters classified by cluster analysis.
Lee teaches a value indicating demand (table 4 and 5; population percentages) for each of the plurality of three-dimensional homologous models (section 2.1) classified into a plurality of clusters (section 2.4 and table 4), based on a number of the three-dimensional homologous models (section 2.1) in each cluster for a plurality of clusters classified by cluster analysis (section 3.4).
It would have been obvious to one of ordinary skill in the art before the effective filing date to use Lee’s value indicating demand in Goonetilleke’s model storage unit, making it easier to determine demand for shoes based on foot shape.
Regarding claim 15, Goonetilleke discloses a body shape analysis method (Fig. 15), comprising: a plurality of body shapes (102) with a plurality of three-dimensional coordinate groups ([0023]), such that a three-dimensional coordinate group ([0023]) indicates an anatomical feature (features of 102) of a foot (102); acquiring, as measurement data (1505), a measured three-dimensional coordinate group ([0023]) indicating an anatomical feature (features of 102).
Goonetilleke does not disclose determining, among a plurality of three-dimensional homologous models, the three-dimensional homologous model similar to the three-dimensional homologous model, based on evaluation for
similarity in coordinates.
Lee teaches determining, among a plurality of three-dimensional homologous models (section 2.1), the three-dimensional homologous model similar to the three-dimensional homologous model, based on evaluation for
similarity in coordinates (section 2.1).
It would have been obvious to one of ordinary skill in the art before the effective filing date to use Lee’s three-dimensional homologous models and coordinate similarity evaluation in Goonetilleke’s body shape analysis method to find a more accurate body part shape match.
Conclusion
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/ANNA JOSEPHINE SAUNDERS/Examiner, Art Unit 2855
/PETER J MACCHIAROLO/Supervisory Patent Examiner, Art Unit 2855
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