SceneCluster: Interactive Scene Synthesis by Clustering Groups of Furniture Objects

Scene synthesis is crucial to computer graphics. However, the current interactive scene synthesis methods usually cost the user too much time and interactions to edit objects. This paper presents a new interactive scene synthesis method that alleviates the designer from interacting with the 3D scene and its objects. Designers only need to select an object group in an independent panel through coarse clustering and fine clustering. Then, the furniture objects will be automatically added to the scene. This paper proposes a two-level clustering that applies the Affinity Propagation Algorithm (APA) to groups of furniture objects such that the object groups can even be clustered without linear representations, latent encoding, etc. To fully apply the APA, we also propose quantitatively measuring how different the two layouts are, i.e., how quantitatively the arrangements of two object groups differ. Experiments first show that our method is more user-friendly and interactively efficient than other interactive synthesis methods. By comparing our method with recent automatic scene synthesis methods, we demonstrate that our methods still have competitive plausibility. We also verify that our method does not harm the diversity and generalization of 3D scenes.