DETAILED ACTION
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 . In the event the determination of the status of the application as subject to 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.
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 23 February 2026 has been entered.
Status of Claims
Claims 1-3, 9, 11-15, 17-18, and 20-27 are currently pending and are being hereby examined herein. Claims 1, 12, 14, 18, 21, and 24 are amended. Claims 4-8, 10, 16, and 19 are canceled.
Response to Amendment / Remarks
Any reference to the prior office action refers to the final rejection dated 23 December 2025.
All objections from the prior office action are withdrawn.
The rejection of Claim 6 under 35 U.S.C. 112(a) from the prior office action is withdrawn due to Claim 6 being canceled.
Applicant’s arguments, with respect to the rejections under 35 U.S.C. 103 from the prior office action, have been considered. Firstly, U.S. Pub. No. 2020/0410739 (Shin et al., hereinafter, Shin) is not relied upon for any rejection under 35 U.S.C. 103 in this office action. Therefore, any arguments regarding Shin are moot. Secondly, Applicant’s argument that U.S. Pub. No. 2005/0153624 (Wieland et al., hereinafter, Wieland) “is silent with respect to “compare the unfiltered data stream to the first set of operational rules and the second set of creative intent rules; make a first determination, based on the unfiltered data stream complying with the first set of operational rules and based on the unfiltered data stream not complying with the second set of creative intent rules, that the robotic figure is configured to execute a first response to the user interactions represented in the unfiltered data stream” as recited by claim 1”, and similar arguments for the other independent claims, are not persuasive. The Examiner has interpreted Wieland not to disclose “wherein the first response comprises: sending instructions to the controller to cause the robotic figure to enact a preprogrammed themed action, wherein the preprogrammed themed action comprises a change in a position of a physical component of the robotic figure based on the first determination” because Wieland appears to only disclose clipping the input data and appears not to disclose an action that is “a preprogrammed themed action, wherein the preprogrammed themed action comprises a change in a position of a physical component of the robotic figure based on the first determination”, but one of ordinary skill in the art would understand Wieland does make determinations about both creative intent rules and operational rules being met in order to complete the disclosed clipping that is based on combinations of both rules (see at least [0087]-[0089]).
Joint Inventors
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1-3, 9, 11-14, 17-18, and 21-27 are rejected under 35 U.S.C. 103 as being unpatentable over Wieland in view of U.S. Pub. No. 2022/0305654 (Ishizuka et al., hereinafter, Ishizuka).
Regarding Claim 1, Wieland discloses An amusement park attraction system (see at least [0003] and [0091]: “A system and method are disclosed, which generally relate to robotic figures, and more specifically to animatronic figures.”; “For example, an operator of an amusement park ride rotates a joystick to control the head and the neck of the animatronic [figure] 108 for the viewing enjoyment of park patrons.”), comprising:
at least one input device (see at least [0080]: “In one embodiment, the user inputs the puppetted motions through a joystick or other analog input device. In another embodiment, the user inputs the puppetted motions through a keyboard. In yet another embodiment, the user inputs the puppetted motions through sensors attached to the user's body. In another embodiment, face tracking is used to input the puppetted motions. Face tracking detects movements of the face and/or head. A camera can be focused on the face and/or head to receive the puppetted motion. Sensors can also be placed on the head to receive the puppetted motion. For instance, the operator 101 can wear a headband that has sensors on it for detecting movement of the head. In yet another embodiment, the user inputs the puppetted motions through voice commands into a microphone that operates in conjunction with voice recognition software.);
a robotic figure (see at least [0003] and FIG. 1: animatronic figure 108);
a controller communicatively coupled to the robotic figure (see at least [0093] and FIG. 1: motion software module 106); and
a smoothing server communicatively coupled to the controller (see at least [0087]-[0089], [0093] and [0108]-[0111]: “ In one embodiment, the reception module 102, the translation software module 104, and the motion software module are all stored on different computers. In one embodiment, the reception module 102 does not need to be stored on a computer. Rather, the reception module 102 can be a simple input device. In another embodiment, the reception module 102 and the translation software module 104 are stored on the same computer but a different computer than the computer on which the motion software module 106 is stored. In yet another embodiment, the reception module 102 and the motion software module 106 are stored on the same computer but on a different computer than the computer on which the translation software module 104 is stored. In another embodiment, the translation software module 104 and the motion software module 106 are stored on the same computer but on a different computer than the computer on which the reception module 102 is stored. One of ordinary skill in the art will also recognize that one computer software module can perform the functions of all or some of these modules. For instance, one software module can perform the functions of the reception module and the translation software module.”), wherein the smoothing server comprises:
a memory configured to store a model dataset associated with the robotic figure (see at least [0087]-[0089], [0093], and [0108]-[0111]) wherein the model dataset comprises:
a first set of operational rules that defines at least technical limitations or operational limitations of the robotic figure (see at least [0087]-[0089]: “For instance, if the operator 101 provides a puppetted instruction to move the head of the animatronic [figure] 108 too far backwards, a hard stop will be encountered. By the term hard stop, one of ordinary skill in the art will recognize that the actuators will hit a physical end stop or barrier restricting the motion of the robot. A wide variety of problems may result from hitting a hard stop. For instance, it may be possible to hit the hard stop with enough force to physically damage the robotic figure. Furthermore, other actuators that depend on the movements of the affected actuators may then also malfunction. In essence, hitting a hard stop could potentially lead to a complete malfunction of the animatronic [figure] 108. Clipping prevents a hard stop from being reached, thereby reducing the potential of a malfunction”);
a second set of creative intent rules that defines at least language limitations or gesture limitations of the robotic figure (see at least [0087]: “the composite motion may appear to be too exaggerated of a motion to appear life-like. In the sneezing example, the head may move too far forward during the combined forward motion and the sneeze to appear life-like. In order to correct this behavior, the composite motion can be clipped. The term clipping refers to the reduction of a value to fall within a predetermined limit.”); and
a set of limit values, wherein at least a portion of the set of limit values is generated based on the first set of operational rules and the second set of creative intent rules (see at least [0087]-[0089]: “clipping refers to the reduction of a value to fall within a predetermined limit”; clipping occurs for technical/operations reasons and to make life-life motions for creative reasons); and
a processor (see at least [0087]-[0089], [0093], and [0108]-[0111]) configured to:
receive, from at least one input device, an unfiltered data stream representing user interactions of a user attempting to control the robotic figure (see at least [0079]: “The puppetted show is a sequence of movements that are operator-controlled. In other words, an operator 101 manually inputs the desired movements of the animatronic [figure] 108 into the animatronic system 100”);
compare the unfiltered data stream to the first set of operational rules and the second set of creative intent rules (see at least [0087]: compared to rules that make motion life-like and rules about actuator range limits);
make a first determination, based on the unfiltered data stream complying with the first set of operational rules and based on the unfiltered data stream not complying with the second set of creative intent rules, that the robotic figure is configured to execute a first response to the user interactions represented in the unfiltered data stream (see at least [0087]: “the head may move too far forward during the combined forward motion and the sneeze to appear life-like. In order to correct this behavior, the composite motion can be clipped”);
make a second determination, based on the unfiltered data stream not complying with the first set of operation rules and based on the unfiltered data stream complying with the second set of creative intent rules, that the robotic figure is configured to execute a second response to the user interactions, wherein the second response comprises: processing the unfiltered data stream to generate a processed data stream, wherein the processing comprises determining the unfiltered data stream includes data that exceeds a limit value of the set of limit values of the model dataset, and in response, replacing the data of the unfiltered data stream with the limit value defined in the model dataset (see at least [0087]-[0089]: “In order to correct this behavior, the composite motion can be clipped. The term clipping refers to the reduction of a value to fall within a predetermined limit”; “ clipping ensures that the range limits for the actuators of the animatronic [figure] 108 that perform the movement are complied with”); selecting one or more actions for the robotic figure to perform based on the processed data stream in responding to the user interactions (see at least [0092]-[0096]: “convert the puppetted instruction into at least one physical movement instruction”); and
sending instructions to the controller to cause the robotic figure to enact the one or more actions in accordance with the processed data stream (see at least [0096]: “The animatronic system 100 then causes the animatronic [figure] 108 to raise its leg and to growl.”).
Wieland does not explicitly disclose wherein the first response comprises: sending instructions to the controller to cause the robotic figure to enact a preprogrammed themed action, wherein the preprogrammed themed action comprises a change in a position of a physical component of the robotic figure based on the first determination.
Ishizuka, in the same field of robot controls, and therefore analogous art, teaches make a first determination, based on the unfiltered data stream complying with the first set of operational rules and based on the unfiltered data stream not complying with the second set of creative intent rules, that the robotic figure is configured to execute a first response to the user interactions represented in the unfiltered data stream, wherein the first response comprises: sending instructions to the controller to cause the robotic figure to enact a preprogrammed themed action, wherein the preprogrammed theme action comprises a change in a position of a physical component of the robotic figure based on the first determination (see at least [0081] and [0085]-[0086]: “In the case of causing the robot device 20a to hold a sword in the right hand 27a, the robot device 20a looks better when holding the sword at a higher position than at a lower position. If the user A raises his right upper arm to a high position, the synchronization control section 122 allows the robot device 20a to hold the sword at a high position. However, at the time of an actual trial, it was found that, since the user A did not actually hold a sword, it was difficult to give the user A a feeling of holding the sword. As a result, the user A did not raise his upper arm to a high position in the “sword battle mode.” Accordingly, the correction processing section 124 corrects the synchronized motion of the robot device 20a such that the user A can cause the robot device 20a to raise the right upper arm 25a high even without raising his own right upper arm to a high position”; the robot could continue to more directly copy the user’s posture from a technical perspective; however, to meet the creative intent of the mode, changes the input to a preprogrammed higher arm when the user’s arm is low).
It would have been obvious, before the effective filing date of the invention, with a reasonable expectation of success, to one having ordinary skill in the art, to combine the teachings of Wieland and Ishizuka, specifically to add the additional processing taught by Ishizuka that results in changing the robot’s actions in numerous ways (not always clipping) with the motivation of providing better entertainment (see at least Ishizuka [0004]-[0007]).
Regarding Claim 2, the Wieland and Ishizuka combination teaches the limitations of Claim 1. Furthermore, Wieland further discloses wherein the at least one input device comprises a camera, a Light Detection and Ranging (LIDAR) device, a wearable user input device, or a hand-held user input device, or any combination thereof (see at least [0080]: “ In one embodiment, the user inputs the puppetted motions through a joystick or other analog input device. In another embodiment, the user inputs the puppetted motions through a keyboard. In yet another embodiment, the user inputs the puppetted motions through sensors attached to the user's body. In another embodiment, face tracking is used to input the puppetted motions. Face tracking detects movements of the face and/or head. A camera can be focused on the face and/or head to receive the puppetted motion. Sensors can also be placed on the head to receive the puppetted motion. For instance, the operator 101 can wear a headband that has sensors on it for detecting movement of the head. In yet another embodiment, the user inputs the puppetted motions through voice commands into a microphone that operates in conjunction with voice recognition software.”).
Regarding Claim 3, the Wieland and Ishizuka combination teaches the limitations of Claim 1. Furthermore, Wieland further discloses wherein the robotic figure comprises at least one output device of the amusement park attraction system (see at least FIG. 1).
Regarding Claim 9, the Wieland and Ishizuka combination teaches the limitations of Claim 1. Furthermore, Wieland further discloses wherein, to process the unfiltered data stream to generate the processed data stream, the processor is configured to: determine that the unfiltered data stream includes erratic data, and in response, introduce additional data to the unfiltered data stream to smooth the erratic data (see at least [0110]-[0112], [0117]-[0121], and [0131]: “The filter module 502 filters the user-inputted motion according to one of a variety of filters”; “In essence, the filter module 502 filters motions to appear more life-like. For instance, when the user 101 inputs an instruction to move the head of the animatronic [figure] 108 in a particular direction, the head may normally move so as to reflect both the gross low-frequency turning motion as well as any high frequency jerking or stuttering motion the operator inadvertently added. The filter module 502 filters the motion of the head so that high frequency content is blocked and low frequency content is passed through. Therefore, the head of the animatronic [figure] 108 will move in a relatively smooth motion.”).
Regarding Claim 11, the Wieland and Ishizuka combination teaches the limitations of Claim 1. Furthermore, Wieland further discloses select, from the model dataset, the one or more actions from a plurality of actions defined within the model dataset, wherein the one or more actions are associated with the user interactions represented within the processed data stream (see at least [0008] and FIG. 5: “A motion software module receives the at least one fixed show physical movement instruction, receives the at least one puppetted physical movement instruction, and calculates a composite animated instruction from the at least one fixed show physical movement instruction and the at least one puppetted physical movement instruction so that at least one actuator can effectuate at least one component of the animatronic figure in a life-like manner”).
Regarding Claim 12, most limitations are substantially similar to Claim 1; therefore, Claim 12 is rejected for the same reasons as Claim 1. Additionally, Wieland discloses A method of operating a smoothing server of an amusement park attraction system (see at least [0003] and [0005]: “A system and method are disclosed, which generally relate to robotic figures, and more specifically to animatronic figures”); analyzing the unfiltered data stream, based on a model dataset associated with the robotic figure (see at least FIG. 5); selecting, from the model dataset, one or more actions from a plurality of actions defined within the model dataset for the robotic figure, wherein the one or more actions are associated with the user interactions represented within the processed data stream (see at least [0008] and FIG. 5: “A motion software module receives the at least one fixed show physical movement instruction, receives the at least one puppetted physical movement instruction, and calculates a composite animated instruction from the at least one fixed show physical movement instruction and the at least one puppetted physical movement instruction so that at least one actuator can effectuate at least one component of the animatronic figure in a life-like manner”).
Regarding Claim 13, the Wieland and Ishizuka combination teaches the limitations of Claim 12. Furthermore, Ishizuka further teaches (with the same motivation to combine as Claim 1) receiving, from the at least one input device of the amusement park attraction system, an additional unfiltered data stream representing additional user interactions of the user attempting to control the robotic figure; analyzing the additional unfiltered data stream based on the model dataset associated with the robotic figure; making a third determination based on the additional unfiltered data stream and the model dataset associated with the robotic figure, that the robotic figure is configured to execute a third response to the additional user interactions; and sending additional instructions to the controller of the robotic figure to cause the robotic figure to enact a second preprogrammed themed action (see at least [0091]: “Note that the correction processing section 124 of the robot device 20a may correct the synchronized motion of the robot device 20a on the basis of the motion of the opponent robot device 20b. The correction processing section 124 acquires a captured image of the opponent from the imaging unit 106, and when it is determined that the robot device 20a is likely to receive a hit of the opponent's attack, for example, the correction processing section 124 may forcibly stop the synchronization control section 122 performing the synchronized motion and then take action to avoid being hit”).
Regarding Claim 14, the Wieland and Ishizuka combination teaches the limitations of Claim 12. Furthermore, Wieland further discloses wherein the set of limit values defines minimum and maximum allowed values for one or more operational parameters of the robotic figure (see at least [0087]-[0089] and [0109]-[0112]: “For instance, a motor has a limit on the velocity the motor can produce. If the animatronic [figure] 108 attempts to reach or surpass this velocity limit, the motor may simply malfunction”; “limit the torque required by the actuators”; “clipping ensures that the range limits for the actuators of the animatronic [figure] 108 that perform the movement are complied with”; “The clipping module can also determine any combination of position, velocity, and/or acceleration being clipped”; “The filter module 502 can filter the user-inputted motion according to a band-pass filter, which passes a limited range of frequencies. The band-pass filter can be a combination of a low-pass filter and a high-pass filter to only pass through certain low frequency content and certain high frequency content”; “The filtering of the motions of the animatronic [figure] 108 produces motions that are life-like. Real world motions produced by living creatures occur at different frequencies than others. For instance, most living creatures move their eyes more quickly than their heads.”).
Regarding Claim 17, Claim 17 is substantially similar to Claim 9; therefore, rejected for the same reasons as Claim 9.
Regarding Claim 18, most limitations are substantially similar to Claim 1 and/or Claim 12; therefore, Claim 18 is rejected for the same reasons as Claim 1 and Claim 12. Additionally, Wieland discloses A non-transitory, computer-readable medium storing instructions executable by a processor of a smoothing server of an amusement park attraction system (see at least [0092]-[0093] and FIG. 1).
Regarding Claim 21, the Wieland and Ishizuka combination teaches the limitations of Claim 1. Furthermore, Wieland further discloses wherein the technical limitations or operational limitations of the robotic figure are associated with operational parameters of a plurality of physical components of the robotic figure (see at least [0087]-[0089]: “For instance, a motor has a limit on the velocity the motor can produce. If the animatronic [figure] 108 attempts to reach or surpass this velocity limit, the motor may simply malfunction”; “limit the torque required by the actuators”; “clipping ensures that the range limits for the actuators of the animatronic [figure] 108 that perform the movement are complied with”; “The clipping module can also determine any combination of position, velocity, and/or acceleration being clipped.”).
Regarding Claim 22, the Wieland and Ishizuka combination teaches the limitations of Claim 21. Furthermore, Wieland further discloses wherein the operational parameters comprise velocity, acceleration, displacement, orientation, voltage, power, pressure, flow rate, positioning, movement, and/or action envelopes (see at least [0087]-[0089]: “The clipping module can also determine any combination of position, velocity, and/or acceleration being clipped”).
Regarding Claim 23, the Wieland and Ishizuka combination teaches the limitations of Claim 21. Furthermore, Wieland further discloses wherein the plurality of physical components comprises joints, motors, actuators, pistons, appendages, or a combination thereof (see at least [0087]-[0089]: “For instance, a motor has a limit on the velocity the motor can produce. If the animatronic [figure] 108 attempts to reach or surpass this velocity limit, the motor may simply malfunction”; “limit the torque required by the actuators”; “clipping ensures that the range limits for the actuators of the animatronic [figure] 108 that perform the movement are complied with”; “The clipping module can also determine any combination of position, velocity, and/or acceleration being clipped”).
Regarding Claim 24, the Wieland and Ishizuka combination teaches the limitations of Claim 12. Furthermore, Wieland further discloses wherein the language limitations or the gesture limitations comprise content designated as inappropriate (see at least [0087]: “the composite motion may appear to be too exaggerated of a motion to appear life-like. In the sneezing example, the head may move too far forward during the combined forward motion and the sneeze to appear life-like.”; not appearing life-like is inappropriate).
Regarding Claim 25, the Wieland and Ishizuka combination teaches the limitations of Claim 14. Furthermore, Wieland further discloses wherein the one or more operational parameters are associated with a plurality of physical components of the robotic figure (see at least [0087]-[0089]: “For instance, a motor has a limit on the velocity the motor can produce. If the animatronic [figure] 108 attempts to reach or surpass this velocity limit, the motor may simply malfunction”; “limit the torque required by the actuators”; “clipping ensures that the range limits for the actuators of the animatronic [figure] 108 that perform the movement are complied with”; “The clipping module can also determine any combination of position, velocity, and/or acceleration being clipped.”).
Regarding Claim 26, the Wieland and Ishizuka combination teaches the limitations of Claim 25. Furthermore, Wieland further discloses wherein the operational parameters comprise velocity, acceleration, displacement, orientation, voltage, power, pressure, flow rate, positioning, movement, and/or action envelopes (see at least [0087]-[0089]: “The clipping module can also determine any combination of position, velocity, and/or acceleration being clipped”).
Regarding Claim 27, the Wieland and Ishizuka combination teaches the limitations of Claim 25. Furthermore, Wieland further discloses wherein the plurality of physical components comprises joints, motors, actuators, pistons, appendages, or a combination thereof (see at least [0087]-[0089]: “For instance, a motor has a limit on the velocity the motor can produce. If the animatronic [figure] 108 attempts to reach or surpass this velocity limit, the motor may simply malfunction”; “limit the torque required by the actuators”; “clipping ensures that the range limits for the actuators of the animatronic [figure] 108 that perform the movement are complied with”; “The clipping module can also determine any combination of position, velocity, and/or acceleration being clipped”).
Claim 15 is rejected under 35 U.S.C. 103 as being unpatentable over Wieland in view of Ishizuka in further view of U.S. Pub. No. 2022/0184802 (Rinke et al., hereinafter, Rinke) and U.S. Pub. No. 2023/0053308 (Zavesky et al., hereinafter, Zavesky).
Regarding Claim 15, the Wieland and Ishizuka combination teaches the limitations of Claim 14. The Wieland and Ishizuka combination does not explicitly teach wherein, prior to receiving the unfiltered data stream, the method comprises: using a machine learning technique to determine the set of limit values from the set of operational rules and the second set of creative intent rules.
Rinke, in the same field of robot controls, and therefore analogous art, teaches using a machine learning technique to determine the set of limit values from the first set of operational rules… (see at least [0012]: “the optimizer is or includes a neural network configured for the machine learning and to take as input the unfiltered control parameters and output the filtered control parameters”).
It would have been obvious, before the effective filing date of the invention, with a reasonable expectation of success, to one having ordinary skill in the art, to combine the teachings of Wieland and Ishizuka with determining limits using machine learning of Rinke. One of ordinary skill would have been motivated to do so because to reduce the time a designer spends reducing unwanted vibrations in robots (see at least Rinke [0003]-[0004]).
Zavesky, in the same field of data processing, and therefore analogous art, teaches using a machine learning technique to determine the set of limit values from… the second set of creative intent rules (see at least [0055] and [0057]: “the movements of non-human beings (e.g., animals) could be learned from video footage and used to recreate those non-human beings in a media without requiring physical access to the non-human beings. For instance, a film may include scenes of a character interacting with a potentially dangerous wild animal (e.g., a shark or a tiger). Rather than bring a trained or captive animal on set, video footage of representative instances of the animal in the wild may be examined and mined for movement data that can be used to create a generic, but realistic and wholly digital version of the animal, which may then be inserted into the film”; “movements and mannerisms of a specific character or individual could be mapped onto an animatronic figure in a theme park or the like. The mannerisms of the animatronic figure could even be adapted dynamically based on context (e.g., if the audience includes children, avoid any gestures that could be considered rude or otherwise objectionable)”).
It would have been obvious, before the effective filing date of the invention, with a reasonable expectation of success, to one having ordinary skill in the art, to combine the teachings of Wieland, Ishizuka, and Rinke with using machine learning to create life-life movement data of Zavesky. One of ordinary skill would have been motivated to do so to create media that is consistent with expectations (see at least Zavesky [0003]-[0004]).
Claim 20 is rejected under 35 U.S.C. 103 as being unpatentable over Wieland in view of Ishizuka in further view of U.S. Pub. No. 2011/0169726 (Holmdahl et al., hereinafter, Holmdahl).
Regarding Claim 20, the Wieland and Ishizuka combination teaches the limitations of Claim 18. The Wieland and Ishizuka combination does not explicitly teach wherein to select the one or more actions, the instructions comprise: identify the user interactions from the processed data stream; and select the one or more actions from the plurality of actions defined within the model dataset, wherein the one or more selected actions are associated with the identified user interactions within a set of creative intent rules of the model dataset.
Holmdahl, in the same field of interpreting and filtering user inputs, and therefore analogous art, teaches wherein to select the one or more actions, the instructions comprise: identify the user interactions from the processed data stream (see at least [0119]-[0123] and [0146]-[0149]: “The gestures recognition engine 190 may include a collection of gesture filters 191. A filter may comprise code and associated data that can recognize gestures or otherwise process depth, RGB, or skeletal data. Each filter 191 may comprise information defining a gesture along with parameters, or metadata, for that gesture. For instance, a throw, which comprises motion of one of the hands from behind the rear of the body to past the front of the body, may be implemented as a gesture filter 191 comprising information representing the movement of one of the hands of the user from behind the rear of the body to past the front of the body, as that movement would be captured by a depth camera. Parameters may then be set for that gesture. Where the gesture is a throw, a parameter may be a threshold velocity that the hand has to reach, a distance the hand must travel (either absolute, or relative to the size of the user as a whole), and a confidence rating by the recognizer engine that the gesture occurred. These parameters for the gesture may vary between applications, between contexts of a single application, or within one context of one application over time.”; “Thus, inputs to a filter such as filter 191 may comprise things such as joint data about a user's joint position, like angles formed by the bones that meet at the joint, RGB color data from the scene, and the rate of change of an aspect of the user. As mentioned, parameters may be set for the gesture. Outputs from a filter 191 may comprise things such as the confidence that a given gesture is being made, the speed at which a gesture motion is made, and a time at which the gesture occurs.”; “The computing environment 212 may include a processor 195 that can process the depth image to determine what targets are in a scene, such as a user 18 or an object in the room.”; “ A filter 519 comprises information defining a gesture 526 (hereinafter referred to as a "gesture"), and may comprise at least one parameter 528, or metadata, for that gesture 526. For instance, a throw, which comprises motion of one of the hands from behind the rear of the body to past the front of the body, may be implemented as a gesture 526 comprising information representing the movement of one of the hands of the user from behind the rear of the body to past the front of the body, as that movement would be captured by the depth camera. Parameters 528 may then be set for that gesture 526. Where the gesture 526 is a throw, a parameter 528 may be a threshold velocity that the hand has to reach, a distance the hand must travel (either absolute, or relative to the size of the user as a whole), and a confidence rating by the recognizer engine 190 that the gesture 526 occurred.”); and select the one or more actions from the plurality of actions defined within the model dataset, wherein the one or more actions are associated with the identified user interactions within the second set of creative intent rules of the model dataset (see at least [0028], [0037], [0038], [0125], and FIG. 1: “For example, as shown in FIG. 1, the user 18 may make a bowling motion in a physical space to cause the player avatar 19 to make a bowling motion in the game space. Other movements by the user 18 may also be interpreted as controls or actions, such as controls to walk, select a ball, position the avatar on the bowling lane, swing the ball, etc.”, “The computing environment may store or otherwise have access to input gesture database 260. The input gesture database 260 may contain an inventory of gesture data, such as a structured collection of records and/or data associated with the gesture data captured or received by the computing environment 218, such as captured data 270 that can be received over the network 250.”; “The gesture set identification module 228 and gesture set evolution module 229 may analyze or manipulate the gesture data received to identify gesture sets and evolve those sets of input gestures.”; “The computing environment 212 may use the default or evolved gesture sets such as that shown in FIG. 2 to interpret movements of the skeletal model and to control an application based on the movements. The computing environment 212 can model and display a representation of a user”).
It would have been obvious, before the effective filing date of the invention, with a reasonable expectation of success, to one having ordinary skill in the art, to combine the teaching of Wieland and Ishizuka with the explicit identification taught by Holmdahl. One of ordinary skill would have been motivated to combine so that gestures from people with a variety of backgrounds, experiences, etc. can be readily recognized for control applications (see at least Holmdahl [0049]-[0050]).
Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to ALEXANDRA ROBYN MORFORD whose telephone number is (571)272-6109. The examiner can normally be reached Monday - Friday 8:00 AM - 4:00 PM ET.
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/A.R.M./Examiner, Art Unit 3658
/JASON HOLLOWAY/Primary Examiner, Art Unit 3658
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