Fast Sprite Decomposition from Animated Graphics
Tomoyuki Suzuki, Kotaro Kikuchi, Kota Yamaguchi
2024-08-08
Summary
This paper presents a method for quickly breaking down animated graphics into individual sprites, which are the basic elements used in animations.
What's the problem?
In animated graphics, there are often many moving parts that need to be managed efficiently. Traditional methods for extracting these elements can be slow and may not produce high-quality results. This makes it difficult for designers and developers to work with animated content, especially when they need to optimize performance or reduce file sizes.
What's the solution?
The authors developed a fast sprite decomposition method that focuses on optimizing how animated graphics are broken down into sprites. They use a pre-trained model to help identify important elements quickly and rely on user input to label specific frames. By doing this, they can extract sprites more efficiently while maintaining high quality. They also created a new dataset called the Crello Animation dataset to test their method and defined metrics to measure how well the sprites were extracted.
Why it matters?
This research is significant because it allows game developers and animators to manage their graphics resources more effectively. By breaking down animations into individual components, it helps improve rendering speeds, reduces file sizes, and enables more flexible animation workflows. This can lead to better performance in games and applications that rely on animated graphics.
Abstract
This paper presents an approach to decomposing animated graphics into sprites, a set of basic elements or layers. Our approach builds on the optimization of sprite parameters to fit the raster video. For efficiency, we assume static textures for sprites to reduce the search space while preventing artifacts using a texture prior model. To further speed up the optimization, we introduce the initialization of the sprite parameters utilizing a pre-trained video object segmentation model and user input of single frame annotations. For our study, we construct the Crello Animation dataset from an online design service and define quantitative metrics to measure the quality of the extracted sprites. Experiments show that our method significantly outperforms baselines for similar decomposition tasks in terms of the quality/efficiency tradeoff.