Information Block Detection in Infographic Based on Spatial Proximity and Structural Similarity (Student Abstract)

Abstract The infographic is a type of visualization chart used to display information. Existing infographic understanding works utilize spatial proximity to group elements into information blocks. However, these works ignore structural features such as background color and boundary, which results in poor performance towards complex infographic. We propose Spatial and Structural Feature Extraction model to group elements based on spatial proximity and structural similarity. We introduce a new dataset towards information block detection. Experiments show that our model can effectively identify the information blocks in the infographic.