1. Image-based Tree Branch Recovery
Yilin Wang

2. Tree modeling Rule-based Image-based
using a small set of generative rules or grammar to create branches and leaves
Image-based
reconstructing the tree directly from image samples
Tree modeling

3. A L-system consists of an axiom and productions
Example
L-system

4. Sample tree structures generated using L-system
P. Prusinkiewicz, M. James, and R. Mech. Synthetic topiary. In SIGGRAPH ’94: Proceedings of the 21st annual conference on Computer graphics and interactive techniques, pages 351–358, New York, NY, USA, ACM.
Sample tree structures generated using L-system

5. Image-based tree modeling
P. Tan, G. Zeng, J. Wang, S. B. Kang, and L. Quan. Image-based tree modeling. In SIGGRAPH ’07: ACM SIGGRAPH 2007 papers, page 87, New York, NY, USA, ACM.
Image-based tree modeling

6. P. Tan, G. Zeng, J. Wang, S. B. Kang, and L. Quan
P. Tan, G. Zeng, J. Wang, S. B. Kang, and L. Quan. Image-based tree modeling. In SIGGRAPH ’07: ACM SIGGRAPH 2007 papers, page 87, New York, NY, USA, ACM.
Bare tree example

7. Problem
“it is not easy to generate complete tree models from just 3D points because of the difficulties in determining what is missing and in filling the missing information”
Can we extract more useful information from images to refine the branch reconstruction?
Motivation

8. My project Final goal Subtasks Potential improvements
To recover the tree branches from images, and to make the procedure as automatic as possible
Subtasks
3D structure generation from source images
Reconstruction of trunk and visible branches
Recovery of occlude branches
Potential improvements
Using segmentations and gradient maps to refine branches, e.g. estimate length, density, and direction of the branch
My project

9. Thank you!