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
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.
Use of indicates a limitation is not explicitly disclosed by the reference alone.
Claim(s) 1, 2, 12, 16, 17, 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Gleicher, Retargetting Motion to New Characters in view of Savenko, Using motion analysis techniques for motion retargeting
Claim 1
Gleicher discloses a trajectory information processing method, performed by a computer device, the method comprising:
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obtaining respective limb trajectory information of at least two first limbs of a first object, the at least two first limbs of the first object being in a one-to-one correspondence with at least two second limbs of a second object (e.g. character A corresponding to character B; See fig. 1 above);
migrating the limb trajectory information from a first limb of the at least two first limbs of the first object to a corresponding second limb of the at least two second limbs of the second object, to obtain initial trajectory information of the second limb (applying re-targeting to the limbs of the second character; “Differently sized characters pick up an object. Their positions are determined by the position of the object. The left shows the original actress. The center shows a figure 60% as large. The right shows a figure with extremely short legs and arms and an extremely long body. The yellow cones represent footplant positions”);
determining, based on the limb trajectory information of the first limb, limb posture information of the first limb and limb interaction information between the at least two first limbs (e.g. in climbing a ladder; Section 3: Because the target character has the same parameters as the original, reusing the original motion data will cause the new character to move its limbs as the original, but not necessarily lead to a desirable result as shown in the example of Figure 2. Because the length of the limbs are different”);
determining, according to the limb posture information and the predicted posture information (e.g. end effector; Section 3.6: “a point on the character (such as an end-effector) is in a spe cific location”), single-limb constraint information between the first limb and the corresponding second limb (Section 3.6: “pre-defined constraints that can be applied to a motion through a graphical user interface or via a scripting language”);
determining, according to the limb interaction information and the predicted interaction information, limb interaction constraint information between the first object and the second object (Section 3.6: “use constraints to prevent specific changes that are unwanted, and use the objective function to avoid undesirable frequency content and unnecessary large alterations…our approach to retargetting motion to another articulated figure with different limb lengths”); and
correcting, based on the single-limb constraint information and the limb interaction constraint information, the initial trajectory information of the second limb, to obtain target trajectory information of the second limb (“Solve the non-linear constraint problem for a displacement that when added to the result of step 2 provides a motion that satisfies the constraints…( 5. optional) If the result of step 4 does not satisfy the constraints sufficiently, solve using the result of the step ( 1 m d ()+ () t t ) as the initial motion, and a denser set of control points for the new displacement.”).
Gleicher does not explicitly disclose, but Savenko discloses pre-correcting the initial trajectory information of the second limb, to obtain predicted posture information of the second limb and predicted interaction information between the at least two second limbs (section 2: “On the second step of the analysis the algorithm corrects the initial decomposition using”)
Before the effective filing date of this application, it would have been obvious to one of ordinary skill in the art to pre-correct.
One of ordinary skill in the art would have motivation to adjust constraint parameters. One of ordinary skill in the art would have had a reasonable expectation of success because both references consider motion transfer.
Claim 2
Gleicher discloses wherein migrating the limb trajectory information from the first limb of the first object to the corresponding second limb of the second object, to obtain the initial trajectory information of the second limb comprises:
determining a first limb length of the first limb, and determining a second limb length of the second limb (Section 5: “The difference between motion for morphing and standard re targetting is that the segment lengths of the target character is not constant over the motion. Therefore, it is better to use a differ ent scaling amount on each frame in Step 2. As with the constant case, we estimate the scale in the event that the limb scalings are non-uniform”); and
adjusting, for each first limb, the limb trajectory information of the first limb according to the first limb length of the first limb and the second limb length of the corresponding second limb, to obtain the initial trajectory information of the second limb (Section 5: “The same methods that are used to adapt a character to new seg ment lengths can be used when the target lengths are not constant, i.e. when the target character is morphing. A simple example of a motion generated for morphing is shown in Figure 6. A more complex example is shown in Figure 10. The difference between motion for morphing and standard re targetting is that the segment lengths of the target character is not constant over the motion. Therefore, it is better to use a differ ent scaling amount on each frame in Step 2. As with the constant case, we estimate the scale in the event that the limb scalings are non-uniform. To apply this time-varying scale to the character’s position, we scale the changes in translation between frames by the scale of the character in the frame, and add these changes together to find the characters positions.”).
Claim 12
Gleicher discloses wherein correcting, based on the single-limb constraint information and the limb interaction constraint information, the initial trajectory information of the second limb, to obtain the target trajectory information of the second limb comprises:
determining a weight parameter of the single-limb constraint information and a weight parameter of the limb interaction constraint information (Section 6: “weighted sum of squares…constraints receive a smaller weighting”);
determining (“We have emphasized finding (and using) constraints that we believe are applicable over a wide range of motions.”), according to the limb interaction constraint information (e.g. “a point on the character (such as an end-effector) is in a spe cific location (useful for footplants or grabbing an object);”), the single-limb constraint information (e.g. “a parameter’s value is in a range (useful for joint limits)”), and the respective weight parameters, target constraint information corresponding to the second limb; and
correcting, based on the target constraint information corresponding to the second limb, the initial trajectory information of the second limb, to obtain the target trajectory information of the second limb (“Our non-linear least-squares solver iteratively improves on an estimate of the solution”).
Claim 16
The same teachings and rationales in claim 1 are applicable to claim 16 as the additional device components recite generic computing functionality disclosed by Atheron.
Claim 17
The same teachings and rationales in claim 1 are applicable to claim 17.
Claim 20
Examiner’s Interpretation:
Machine readable media can encompass forms of signal transmission media that falls outside of the four statutory categories of invention. MPEP 2106; citing In re Nuijten, 500 F.3d 1346, 84 USPQ2d 1495 (Fed. Cir. 2007). A claim whose BRI covers both statutory and non-statutory embodiments embraces subject matter that is not eligible for patent protection and therefore is directed to non-statutory subject matter. MPEP 2106.
Claim 20 as drafted recites A non-transitory computer-readable storage medium
The broadest reasonable interpretation of the claimed medium in view of Applicant’s specification covers only eligible subject matter.
Claim Mapping:
The same teachings and rationales in claim 1 are appliable to claim 20.
Allowable Subject Matter
Claim(s) 3-14, 15, 18-19 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 a statement of reasons for the indication of allowable subject matter:
Regarding claim(s) 3-11, 18-19 the cited prior art does not suggest obtaining candidate offset information of each iteration…pre-correcting, for each iteration, the initial trajectory information of the second limb based on the candidate offset information of the iteration, to obtain the predicted posture information of the second limb and the predicted interaction information between the at least two second limbs,
Regarding claim(s) 13, 14 Gelicher’s weighting does not consider determining the weight parameter of the single-limb constraint information and the weight parameter of the limb interaction constraint information comprises: determining, according to the limb start position and the limb end position of the first limb, the weight parameter of the single-limb constraint information; and determining, according to the weight parameter of the single-limb constraint information, the weight parameter of the limb interaction constraint information
Regarding claim(s) 15, Gleicher considers multiple joints (e.g. a skeleton), but does not suggest the single-limb constraint information is constraint information between the first joint chain and the second joint chain; and
the limb interaction constraint information is constraint information between a first interaction relationship and a second interaction relationship, the first interaction relationship being an interaction relationship between at least two first joint chains, and the second interaction relationship being an interaction relationship between at least two second joint chains.
Additional Prior Art
Additional prior art relevant to Applicant’s disclosure but not relied upon:
Atherton (US 2024/0070949) considers predicting trajectories.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to RYAN M GRAY whose telephone number is (571)272-4582. The examiner can normally be reached on Monday through Friday, 9:00am-5:30pm (EST).
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/RYAN M GRAY/Primary Examiner, Art Unit 2611
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