AI Particle Effect Generation via Text and Appearance Input

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Solution Overview

Problem

Traditional methods for generating particle effects in media content require significant manpower and technical expertise, resulting in limited complexity and user experience, as they typically involve pre-generated effects created by professionals using digital content creation tools.

Innovation Solution

A method and apparatus that obtain appearance information of a target object and generate a particle effect based on input information and description text, using configuration information determined from the text to create a media content with a particle effect, reducing the complexity and technical threshold for users.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Manufacturing precision

If traditional professional digital content creation tools are used to generate particle effects, then the quality and complexity of particle effects can be improved, but the ease of operation and accessibility for general users deteriorates

Engineering Contradiction:

Improveparticle effect qualityVSAvoiduser accessibility

Core Design Contradiction:

Manufacturing precisionVSEase of operation

Solution Approach 1:

The patent introduces an intermediary system that includes a particle effect generation model trained with diffusion models and neural radiance fields. This intermediary translates simple user inputs (text descriptions or basic parameters) into complex particle effect configurations, bridging the gap between user capability and effect quality without requiring users to directly operate professional DCC tools

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The patent replaces the mechanical interaction with professional DCC tools (manual parameter adjustment, complex interface operations) with an automated AI-driven system. The system uses machine learning models to automatically generate particle effects based on high-level user specifications, substituting the complex mechanical process of manual effect creation with an intelligent automated process

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Adaptability or versatility

If professional digital content creation tools are used for particle effect generation, then the complexity and richness of effects can be improved, but the device complexity and technical expertise required increases

Engineering Contradiction:

Improveeffect complexityVSAvoidtechnical threshold

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The patent segments the complex particle effect generation process into distinct functional modules: a particle effect generation model, a neural radiance field component, and a rendering system. Each module handles a specific aspect of effect creation, allowing the system to achieve high versatility while keeping the user interface simple. The segmentation enables independent optimization of each component without increasing overall system complexity for the user

Inventive Principle:

Principle #1Segmentation

3Manufacturing precision

If manual particle effect creation using DCC tools is used, then the precision and control over effects can be improved, but the productivity and efficiency of content generation deteriorates

Engineering Contradiction:

Improveeffect controlVSAvoidcontent generation efficiency

Core Design Contradiction:

Manufacturing precisionVSProductivity

Solution Approach 1:

The patent implements preliminary action by pre-training the particle effect generation model with extensive particle effect data and configurations before actual use. The neural radiance field is pre-computed based on particle positions and properties. This preliminary preparation enables the system to rapidly generate high-quality particle effects during actual content creation without requiring manual adjustment, thus maintaining precision while dramatically improving productivity

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system enables self-service by allowing particle effects to automatically adjust and optimize their own parameters based on the input specifications. The generation model automatically configures particle properties, animation curves, and rendering parameters without requiring manual intervention, enabling rapid iteration and generation of multiple effect variations for content creation

Inventive Principle:

Principle #25Self-service

Data Source

PatentUS20250106345A1A method, apparatus, device, and storage medium for media content generation

Publication Date: 2025.03.27 BEIJING ZITIAO NETWORK TECH CO LTD

AI summary

According to embodiments of the disclosure, a method, apparatus, device and storage medium for media content generation are provided. The method includes: obtaining, based on input information indicating a target object, appearance information of the target object, the appearance information at least indicating a shape and a posture of the target object; receiving a description text related to a particle display effect; determining, based on the description text, configuration information for particle display of the target object; and generating, based on the appearance information and the configuration information, a media content comprising a particle effect of the target object. In this way, a particle effect may be generated based on simple input information and description text. This advantageously reduces the difficulty of generation of the particle effect, thereby helping to produce a richer particle effect.