1. Paper -5 Multiresolution volume visualization with
a texture-based octree
ImmaBoada, IsabelNavazo,
Roberto Scopigno

2. Introduction New texture memory management policy
Octree representation of original data ,computed during preprocessing
At render time set of octree nodes selected
User defined criteria about accuracy and importance of data
View independent and takes advantage of data homogenity, importance

3. Approach
A hierarchical data organization has been adopted in the context of a texture-based volume rendering system in, where texture bricks at different resolutions can be assigned to sections of the original dataset.
An improved rendering solution, based on the use of spherical shells instead of view-aligned planes
Texel values represent density values and gradients

4. Rendering
Octree built in pre-processing phase, traversed at rendering time.
Bunch of nodes called ‘cut’ is selected
Resolution of texture brick determined at runtime
N(i)B(i) : according to homogenity, importance and degree of accuracy and surrounding regions

5. Error calculation

6. Cut selection
For each node ni at level k, we have a corresponding subtree of depth lmax −k and a corresponding voxel region of resolution 2^Lmax−k ∗2^Lmax−k ∗2^Lmax−k.
The accuracy of the texture-based representation is encoded in the node’s corresponding nodal error,
εR(ni) = εp(ni).

7. Octree traversal Error threshold Node importance Importance function
Uniformity function
E* =Eu / Imp(ni,f).
function OTcut(IN : OT_node, εu, f, Tmax, minPartSize; OUT : brick_set)
Start with root node and trace along all children till a solution is found

8. Results

9. Questions?