Image-based lightweight tree modeling

This paper presents a novel lightweight tree modeling approach for constructing large scale online virtual forestry on Web. It firstly recovers 3D skeleton of the visible trunk from two source images of a tree, then extracts the rules and parameters of tree L-system from the recovered skeleton, and parses the parametric L-system into very lightweight tree Web3D files. Comparing with rule based tree modeling methods e.g. L-system and AMAP, our method is more convenient for users without requiring botany expertise. Furthermore, our method inherits the merits of both image based tree modeling and rules based tree modeling. Comparing with such 3D modelers as 3DMAX and MAYA, our method is more efficient and economical for users to avoid their heavily manual modeling labors. More important, it can generate very lightweight Web3D tree files even with 1K-2K, which are photorealistic in shape and structure, Experimental results show that the feasibility and perspective of our proposed method in WebVR applications.