Hierarchical Data Organization for Effective Retrieval of Similar Shaders

Abstract

Generating a shader is an important factor for portraying realistic objects on the screen using 3D computer graphics. However, since generating a shader requires significant amounts of time and effort, the user must be able to search for a desired shader from a large shader database. This paper proposes a novel hierarchical clustering algorithm that structuralizes a shader database by clustering similar shaders in order to facilitate the shader search process. Since conventional hierarchical clustering methods do not take into account the cluster diameter and the number of shaders in a cluster, the resulting databases structure is highly likely to be a skewed tree. The proposed method represents a shader database into a graph and recursively uses a graph partitioning algorithm to perform hierarchical clustering. In this process, since the cluster diameter and the number of shaders in a cluster are taken into account preventing a single cluster from becoming excessively large, we can construct a hierarchical database structure close to a balanced state. Various experiments were conducted to verify the merits of the proposed method. The experimental results indicate that the proposed method provides a high level of accuracy as well as a structure close to a balanced state.