KinemaFX: A Kinematic-Driven Interactive System for Particle Effect Exploration and Customization

Abstract

Particle effects are widely used in games and animation to simulate natural phenomena or stylized visual effects. However, creating effect artworks is challenging for non-expert users due to their lack of specialized skills, particularly in finding particle effects with kinematic behaviors that match their intent. To address these issues, we present KinemaFX, a kinematic-driven interactive system, to assist non-expert users in constructing customized particle effect artworks. We propose a conceptual model of particle effects that captures both semantic features and kinematic behaviors. Based on the model, KinemaFX adopts a workflow powered by Large Language Models (LLMs) that supports intent expression through combined semantic and kinematic inputs, while enabling implicit preference-guided exploration and subsequent creation of customized particle effect artworks based on exploration results. Additionally, we developed a kinematic-driven method to facilitate efficient interactive particle effect search within KinemaFX via structured representation and measurement of particle effects. To evaluate KinemaFX, we illustrate usage scenarios and conduct a user study employing an ablation approach. Evaluation results demonstrate that KinemaFX effectively supports users in efficiently and customarily creating particle effect artworks.

Meta Review Overall Rating 3.5 Weakly Accept Contribution to HCI This paper presents KinemaFX, an LLM-powered interactive system leveraging semantic and kinematic inputs to help non-experts explore, customize, and compose particle effects

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