Rendering based on user interests is one of the hot topics in the expressive rendering of large-scale scene. Objects with high user interests should be rendered in detail

while coarse rendering does well for objects with low user interests. Traditional methods compute objects’ user interests based on their spatial distances with the user’s central focus object. In this paper

we propose a novel semantic-based approach for computing objects’ user interests. In this approach

we first construct the scene’s semantic forest model and compute the semantic distances between any two semantics in the preprocessing stage. At runtime

after the user specifies the central focus object

with its semantic and spatial information we can calculate the user’s objects of interest in the scene considering both

their semantic and spatial distances within the user’s central focus object. Finally

the objects are classified by their user interests and rendered with multiple styles. The user interests calculated by our method conform to human perception and our method can achieve real-time performance.