Open AccessSingle Image–Based 3D Tree and Growth Models Reconstruction
Author(s) -
Kim Jaehwan,
Jeong IlKwon
Publication year - 2014
Publication title -
etri journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.295
H-Index - 46
eISSN - 2233-7326
pISSN - 1225-6463
DOI - 10.4218/etrij.14.0113.0069
Subject(s) - tree (set theory) , decision tree model , computer science , interval tree , tree structure , k ary tree , segment tree , process (computing) , artificial intelligence , image (mathematics) , parametric statistics , similarity (geometry) , computer vision , algorithm , mathematics , decision tree , binary tree , mathematical analysis , statistics , operating system
In this paper, we present a new, easy‐to‐generate system that is capable of creating virtual 3D tree models and simulating a variety of growth processes of a tree from a single, real tree image. We not only construct various tree models with the same trunk through our proposed digital image matting method and skeleton‐based abstraction of branches, but we also animate the visual growth of the constructed 3D tree model through usage of the branch age information combined with a scaling factor. To control the simulation of a tree growth process, we consider tree‐growing attributes, such as branching orders, branch width, tree size, and branch self‐bending effect, at the same time. Other invisible branches and leaves are automatically attached to the tree by employing parametric branch libraries under the conventional procedural assumption of structure having a local self‐similarity. Simulations with a real image confirm that our system makes it possible to achieve realistic tree models and growth processes with ease.