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 .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 02/26/2025 is being considered by the examiner.
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) 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over TikTok EFFECT HOUSE (Introduction to effect house: Learn: Tiktok effect house. Learn | TikTok Effect House. https://effecthouse.tiktok.com/learn/guides/getting-started/introduction-to-effect-house, pp. (Create With AI, Interactions Overview, Visual Scripting Overview) (Publication Date: February 22, 2023) “TikTok Effect House”) in view of CHEN (No. US-12061880-B2 “Chen”).
Regarding claim 1, TikTok Effect House teaches “receive a user query;” (Start typing your effect idea; Create With AI: v4.4.0, Row 3); (After you've entered a prompt or selected one of the existing prompts and topics, click Generate; Create With AI: v4.4.0, Row 4);
“generate domain-specific language instructions based on the plurality of action descriptions;” (Table showcases preset subgraphs that correspond to script instructions such as visibly changes, animation playback based on face movement, hand gestures or any action descriptions; Interactions Overview: v2.1.0);
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TikTok Effect House: Interactions Overview
“select a set of modular subgraphs from a library of a plurality of modular subgraphs based on the domain-specific language instructions; (Interactions are preset subgraphs that can be added in one click to make your effect interactive; Interactions: v2.1.0, Para 1);
“assemble the set of modular subgraphs into a package by interconnecting the set of modular subgraphs; and” (A subgraph is a selection of nodes that have been grouped together into one manageable unit. Subgraphs are used as organizational tools, and can contain other subgraphs; Visual Scripting Module 2, Para 4);
“generate the visual effect by executing the package.” (Generate. A preview of the generated effect opens; Create With AI: v4.4.0, Row 4); (Submit to submit the effect as it was generated; Create With AI: v4.4.0, Row 5 ii.);
While TikTok Effect House does not teach “A computing system for generating a visual effect, the computing system comprising: processing circuitry and memory storing an effects generation model and instructions that, when executed, causes the processing circuitry to:”, “generate a plurality of action descriptions based on the user query;” and “generate domain-specific language instructions based on the plurality of action descriptions;”
However, Chen does teach “A computing system for generating a visual effect, the computing system comprising:
processing circuitry and memory storing an effects generation model and instructions that, when executed, causes the processing circuitry to:” (a system for generating computer code based on natural language input may include at least one memory storing instructions and at least one processor configured to execute the instructions to perform operations; Col 2, Line 65 – Col 3, Line 2);
“generate a plurality of action descriptions based on the user query;” (receiving a docstring representing natural language text specifying a digital programming result; generating, using a trained machine-learning model and based on the docstring, one or more computer code samples configured to produce respective candidate results; Col 3, Line 3-7);
Chen discloses a system which when receiving a docstring that relates to the user query, using the docstring to produce candidate results. This teaches the claimed subject matter of generating a plurality of action descriptions.
TikTok Effect House and Chen are analogous art as both of them are related to effect generation and natural language input.
The motivation for the above is to have accurate and efficient visual effect generation for user friendly usage.
Therefore, it would have been obvious for an ordinary skilled person in the art before the effective filing date of claimed invention to have modified TikTok Effect House by a processing circuitry and memory storing an effects generation model and instructions that, when executed, causes the processing circuitry to and generating a plurality of action descriptions based on the user query as taught by Chen.
Regarding claim 2, TikTok Effect House teaches “The computing system of claim 1, wherein the plurality of action descriptions are generated by generating one or more prompts, inputting the one or more prompts into a language model to generate one or more responses, and generating the plurality of action descriptions based on the one or more responses.” (Start typing your effect idea, or choose from available prompts and topics; Create With AI: v4.4.0, Row 3); (After you've entered a prompt or selected one of the existing prompts and topics, click Generate. A preview of the generated effect opens; Create With AI: v4.4.0, Row 4);
TikTok Effect House discloses having generated prompts or user input prompts into a language model to generate a preview of effect options. This teaches the claimed subject matter.
Regarding claim 3, TikTok Effect House teaches “The computing system of claim 1, wherein the processing circuitry is further configured to:
generate effect units based on the plurality of action descriptions; and” (Generate. A preview of the generated effect opens; Create With AI: v4.4.0, Row 4);
“assemble the set of modular subgraphs and the effect units into the package by interconnecting the set of modular subgraphs and the effect units.” (including variables and subgraphs; Visual Scripting Overview: v3.0.0, Add Variable Para 1); (connect one node to another is to drag an output port (of node A) to an inport port (of Node B), you can reroute a node for a more complex node graph; Visual Scripting Overview: v3.0.0, Connect Nodes, Para 1);
TikTok Effect House discloses connecting nodes while also disclosing variables and subgraphs that teach the claimed subject matter.
Regarding claim 4, TikTok Effect House teaches “The computing system of claim 3, wherein
the effect units comprise assets and entities;” (an interaction feature to an object, select the desired object in the Hierarchy panel; Interactions Overview: v2.1.0, Add an Interaction, Para 1);
“the assets include textures; and” (See image below; the animated Texture Sequence from the Assets panel into the Texture slot; Interactions Overview: v2.1.0);
“the entities include objects.” (See image below; have objects parented under a Scene Object in the Hierarchy panel; Interactions Overview: v2.1.0);
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TikTok Effect House: Interactions Overview
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TikTok Effect House: Interactions Overview
Regarding claim 5, TikTok Effect House teaches “The computing system of claim 3, wherein the processing circuitry is further configured to:
generate connection commands to establish links between the effect units and the modular subgraphs.” (Within a subgraph, notice there are sections for Input and Output. ...Connect these inputs and outputs into your nodes within the subgraph; Visual Scripting Module 2);
TikTok Effect House discloses sub graphs input and output which connect to nodes, this teaches the claimed subject matter of connection commands.
Regarding claim 6, TikTok Effect House teaches “The computing system of claim 3, wherein the action descriptions include names of the effect units and natural language descriptions of the effect units.” (First add a Cube object to the scene by clicking the Add button [+], going to 3D, and selecting Cube; Module 7); (Shows or hides the target object when the selected facial movement is detected; Detect Face Movement to Show/Hide Object);
TikTok Effect House discloses names of effect units such as the Cube object and it’s named Cube. Thus, by showing or hiding the target object, this teaches the natural language description of the visual effects.
Regarding claim 7, TikTok Effect House teaches “The computing system of claim 1, wherein modular subgraphs are modular script graphs that each accomplish independent functions or behaviors.” (A subgraph is a selection of nodes that have been grouped together into one manageable unit. Subgraphs are used as organizational tools, and can contain other subgraphs. Many complex visual scripting graphs use subgraphs to partition different functional components into identifiable packages; Visual Scripting Module 2);
TikTok Effect House discloses subgraphs that have different functional components, this teaches the claimed subject matter of subgraphs having independent functions or behaviors.
Regarding claim 8, TikTok Effect House teaches “The computing system of claim 1, wherein the visual effect is generated by rendering the visual effect on a user interface on a social media platform.” (Open Effect House, Click Create with AI; Create With AI: v4.4.0, Row 1-2); (TikTok account; Create With AI: v4.4.0);
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TikTok Effect House: Create With AI
TikTok Effect House discloses opening the effect house and clicking Create with Ai on TikTok which allows the rendering of the visual effect. Thus, teaching the claimed subject matter of generating the visual effect on a social mead platform.
Regarding claim 9, TikTok Effect House teaches “The computing system of claim 1, wherein the modular subgraphs handle functionalities including at least one of facial expression detection, gesture recognition, object detection and tracking, pose estimation, or color detection.” (Table showcases interactions that include facial movement detection, hand gesture recognition);
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TikTok Effect House image of table discloses the functionalities that allow for facial movement and hand gesture detection which teaches the claimed subject matter of at least facial expression detection and gesture recognition.
Regarding claim 10, TikTok Effect House teaches “The computing system of claim 1, wherein the processing circuitry is configured to further generate a natural language response inviting a subsequent user query to modify the visual effect.” (Workspace to further customize your newly created effect; Create With AI: v4.4.0, Row 5 i.); (Figure showcases natural language response to user to add or modify visual effect.)
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TikTok Effect House: Create With AI
TikTok Effect House image discloses a workspace where a natural language responds to user input and invites user to modify visual effect, thus teaching claimed subject matter.
Regrading claim 11, while TikTok Effect House does not teach “A computing method for generating a visual effect, the computing method comprising”, Chen teaches “A computing method for generating a visual effect, the computing method comprising:” (a method for generating computer code based on natural language input; Col 1, Line 53-54);
Claim 11 is directed to a computing method and its limitations are similar in scope and functions performed by the computing system of claim 1. Therefore, claim 11 limitations are also rejected with the same rationale as regarding claim 1.
Claim 12 is directed to a computing method and its limitations are similar in scope and functions performed by the computing system of claim 2. Therefore, claim 12 limitations are also rejected with the same rationale as regarding claim 2.
Claim 13 is directed to a computing method and its limitations are similar in scope and functions performed by the computing system of claim 3. Therefore, claim 13 limitations are also rejected with the same rationale as regarding claim 3.
Claim 14 is directed to a computing method and its limitations are similar in scope and functions performed by the computing system of claim 4. Therefore, claim 14 limitations are also rejected with the same rationale as regarding claim 4.
Claim 15 is directed to a computing method and its limitations are similar in scope and functions performed by the computing system of claim 5. Therefore, claim 15 limitations are also rejected with the same rationale as regarding claim 5.
Claim 16 is directed to a computing method and its limitations are similar in scope and functions performed by the computing system of claim 6. Therefore, claim 16 limitations are also rejected with the same rationale as regarding claim 6.
Claim 17 is directed to a computing method and its limitations are similar in scope and functions performed by the computing system of claim 7. Therefore, claim 17 limitations are also rejected with the same rationale as regarding claim 7.
Claim 18 is directed to a computing method and its limitations are similar in scope and functions performed by the computing system of claim 8. Therefore, claim 18 limitations are also rejected with the same rationale as regarding claim 8.
Claim 19 is directed to a computing method and its limitations are similar in scope and functions performed by the computing system of claim 9. Therefore, claim 19 limitations are also rejected with the same rationale as regarding claim 9.
Regarding claim 20, while TikTok Effect House does not teach “A computing system for generating a visual effect, the computing system comprising: processing circuitry and memory storing an effects generation model and instructions that, when executed, causes the processing circuitry to:”, Chen teaches “A computing system for generating a visual effect, the computing system comprising:
processing circuitry and memory storing an effects generation model and instructions that, when executed, causes the processing circuitry to:” (a system for generating computer code based on natural language input may include at least one memory storing instructions and at least one processor configured to execute the instructions to perform operations; Col 2, Line 65 – Col 3, Line 2);
However, TikTok Effect House does teach “receive a user query;” (Start typing your effect idea; Create With AI: v4.4.0, Row 3); (After you've entered a prompt or selected one of the existing prompts and topics, click Generate; Create With AI: v4.4.0, Row 4);
“select a set of modular subgraphs from a library of a plurality of modular subgraphs based on the user query;” (Interactions are preset subgraphs that can be added in one click to make your effect interactive; Interactions: v2.1.0, Para 1);
“assemble the set of modular subgraphs into a package by interconnecting the set of modular subgraphs; and” (A subgraph is a selection of nodes that have been grouped together into one manageable unit. Subgraphs are used as organizational tools, and can contain other subgraphs; Visual Scripting Module 2, Para 4);
“generate the visual effect by executing the package, wherein” (Generate. A preview of the generated effect opens; Create With AI: v4.4.0, Row 4); (Submit to submit the effect as it was generated; Create With AI: v4.4.0, Row 5 ii.);
“the modular subgraphs handle functionalities including at least one of facial expression detection, gesture recognition, object detection and tracking, pose estimation, or color detection.” (Table showcases interactions that include facial movement detection, hand gesture recognition; Interactions Overview: v2.1.0);
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TikTok Effect House image of table discloses the functionalities that allow for facial movement and hand gesture detection which teaches the claimed subject matter of at least facial expression detection and gesture recognition.
The motivation for the above is to have accurate and efficient visual effect generation for user friendly usage.
Therefore, it would have been obvious for an ordinary skilled person in the art before the effective filing date of claimed invention to have modified TikTok Effect House by a processing circuitry and memory storing an effects generation model and instructions that, when executed, causes the processing circuitry as taught by Chen.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
US-20240378399-A1 (Gandhi) – Discloses receiving a natural language query from a client device, the query including a textual description of one or more actions to be performed using an application on the client device, generating a prompt for a large language model (LLM) based on the natural language query; providing the prompt to the LLM to obtain program code, which when executed, causes the application to perform the one or more actions, the first program code being implemented in a domain specific language (DSL) designed to facilitate program synthesis via the LLM.
How to create an augmented reality filter for TikTok. Wired (Rogers) – Discloses TikTok’s software for creating filters, called Effect House.
TikTok opens its AR development tool called Effect House (VR Owl) – Discloses brief overview of TikTok Effect House as an AR development tool.
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/B.D.P./Examiner, Art Unit 2612
/Said Broome/Supervisory Patent Examiner, Art Unit 2612
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